diff --git a/qdrant-landing/content/ai-agents/ai-agents-features.md b/qdrant-landing/content/ai-agents/ai-agents-features.md index a452c17df..f7c0d983a 100644 --- a/qdrant-landing/content/ai-agents/ai-agents-features.md +++ b/qdrant-landing/content/ai-agents/ai-agents-features.md @@ -48,7 +48,7 @@ features: description: Qdrant’s architecture is optimized for high-throughput embedding processing, minimizing CPU load and preventing performance bottlenecks. This enables AI agents in Agentic RAG workflows to execute complex, multi-step tasks efficiently, ensuring smooth operation even at scale. link: text: Distributed Deployment - url: /documentation/operations/distributed_deployment/ + url: /documentation/distributed_deployment/ - id: 4 icon: src: /icons/outline/speedometer-blue.svg diff --git a/qdrant-landing/content/articles/agentic-builders-guide.md b/qdrant-landing/content/articles/agentic-builders-guide.md index cdf2927f2..ae498e8c9 100644 --- a/qdrant-landing/content/articles/agentic-builders-guide.md +++ b/qdrant-landing/content/articles/agentic-builders-guide.md @@ -109,13 +109,13 @@ Once you’ve built a fast, accurate, secure, and scalable agent, how do you kno Your agent’s ability to complete complex tasks is only as good as the context it can retrieve. It is crucial to closely and continuously monitor the agent’s performance with grounding checks to spot and prevent hallucinations, recall@k to ensure relevance in search, and MMR parameters for diversity. -#### [**Performance-Cost Tradeoff**](https://qdrant.tech/documentation/operations/optimize/) +#### [**Performance-Cost Tradeoff**](https://qdrant.tech/documentation/ops-optimization/optimize/) In production agents, efficiency is one of, if not the, most important metric to track. First, in enterprise environments you must meet strict latency budgets. Evaluations also let you track the cost per task by tracking token usage and end-to-end compute time. Finally, you can track the effectiveness of your memory layer by monitoring cache hit rates for your memory banks. ![Tradeoff Triangle](/articles_data/agentic-builders-guide/tradeoff-triangle.png) -#### [**Guardrails & Fallbacks**](https://qdrant.tech/documentation/operations/security/) +#### [**Guardrails & Fallbacks**](https://qdrant.tech/documentation/security/) Just like humans, agents aren’t perfect. A production agentic system should expect and anticipate failures and have guardrails to handle them gracefully. You can also use a human in the loop when confidence scores are below a chosen threshold or the query touches on a high-stakes or sensitive topic. To handle a wide range of queries, your agent should use hybrid search. Hybrid search combines the power of semantic search for understanding meaning with the precision of keyword search for exact matches, giving you the best of both worlds. @@ -125,7 +125,7 @@ The same agent that speeds through a toy dataset with 10,000 points will become We’ll talk about three concepts you can take advantage of to improve your scale, but if you want even more information on how to scale, check out this [article](https://qdrant.tech/documentation/database-tutorials/large-scale-search/) on large scale search. -As your dataset and traffic grow, Qdrant Cloud offers a suite of features to ensure your system can scale effectively. Horizontal scaling is achieved through [sharding](https://qdrant.tech/articles/multitenancy/), which splits your collection across multiple nodes to distribute the load and improve performance. For high availability and fault tolerance, Qdrant supports [replication](https://qdrant.tech/documentation/operations/distributed_deployment/), creating copies of your shards across the cluster. +As your dataset and traffic grow, Qdrant Cloud offers a suite of features to ensure your system can scale effectively. Horizontal scaling is achieved through [sharding](https://qdrant.tech/articles/multitenancy/), which splits your collection across multiple nodes to distribute the load and improve performance. For high availability and fault tolerance, Qdrant supports [replication](https://qdrant.tech/documentation/distributed_deployment/), creating copies of your shards across the cluster. Qdrant provides robust tools for resource and cost optimization. Vector [quantization](https://qdrant.tech/documentation/manage-data/quantization/) compresses your data, significantly reducing its memory footprint and speeding up search. @@ -143,7 +143,7 @@ Workflows that are effective for a single user or a handful of users in a develo Qdrant provides production-grade [authorization and authentication](https://qdrant.tech/documentation/cloud/authentication/) via API keys, multitenancy, and Role-Based Access Control (RBAC) to make sure your agent doesn’t go rogue. -Authentication for agents is handled by [API keys](https://qdrant.tech/documentation/operations/security/#api-keys). With Qdrant, API keys are more than just a password. They act as smart credentials that also carry the details of the authorization rules that are enforced once the agent’s identity is confirmed. These keys can be dynamically created as temporary credentials for each user session, making access limited to the session and secure. +Authentication for agents is handled by [API keys](https://qdrant.tech/documentation/security/#api-keys). With Qdrant, API keys are more than just a password. They act as smart credentials that also carry the details of the authorization rules that are enforced once the agent’s identity is confirmed. These keys can be dynamically created as temporary credentials for each user session, making access limited to the session and secure. Note: Qdrant also supports concurrent queries, so your search won’t slow down as more users are writing queries simultaneously. @@ -165,7 +165,7 @@ Your AI agent needs to be able to run without issues wherever your users are run Qdrant lets you deploy in a variety of ways so you can build the system that best fits your use case. You can deploy via the cloud or self host on Docker or your own machine. Read more below: -* [Qdrant Cloud](https://qdrant.tech/documentation/cloud-intro/) +* [Qdrant Cloud](https://qdrant.tech/documentation/deploy-intro/) * [Hybrid Cloud](https://qdrant.tech/documentation/hybrid-cloud/) * [Self-Hosted](https://qdrant.tech/documentation/quickstart/) diff --git a/qdrant-landing/content/articles/data-privacy.md b/qdrant-landing/content/articles/data-privacy.md index 5447e0165..640feb812 100644 --- a/qdrant-landing/content/articles/data-privacy.md +++ b/qdrant-landing/content/articles/data-privacy.md @@ -55,7 +55,7 @@ On Qdrant Cloud, you can create API keys using the [Cloud Dashboard](https://qdr For on-premise or local deployments, you'll need to configure API key authentication. This involves specifying a key in either the Qdrant configuration file or as an environment variable. This ensures that all requests to the server must include a valid API key sent in the header. -When using the simple API key-based authentication, you should also turn on TLS encryption. Otherwise, you are exposing the connection to sniffing and MitM attacks. To secure your connection using TLS, you would need to create a certificate and private key, and then [enable TLS](/documentation/operations/security/#tls) in the configuration. +When using the simple API key-based authentication, you should also turn on TLS encryption. Otherwise, you are exposing the connection to sniffing and MitM attacks. To secure your connection using TLS, you would need to create a certificate and private key, and then [enable TLS](/documentation/security/#tls) in the configuration. API authentication, coupled with TLS encryption, offers a first layer of security for your Qdrant instance. However, to enable more granular access control, the recommended approach is to leverage JSON Web Tokens (JWTs). diff --git a/qdrant-landing/content/articles/dedicated-vector-search.md b/qdrant-landing/content/articles/dedicated-vector-search.md index aa2fe22ad..0783e2c49 100644 --- a/qdrant-landing/content/articles/dedicated-vector-search.md +++ b/qdrant-landing/content/articles/dedicated-vector-search.md @@ -128,7 +128,7 @@ With index maintenance divided between segments, Qdrant can ensure high performa | | | |---------------------|-------------| | **Mutable Segments** | These are used for quickly ingesting new data and handling changes (updates) to existing data. | -| **Immutable Segments** | Once a mutable segment reaches a certain size, an optimization process converts it into an immutable segment, constructing an HNSW index – you could [**read about these optimizers here**](/documentation/operations/optimizer/#optimizer) in detail. This immutability trick allowed us, for example, to ensure effective [**tenant isolation**](/documentation/manage-data/indexing/#tenant-index). | +| **Immutable Segments** | Once a mutable segment reaches a certain size, an optimization process converts it into an immutable segment, constructing an HNSW index – you could [**read about these optimizers here**](/documentation/ops-optimization/optimizer/#optimizer) in detail. This immutability trick allowed us, for example, to ensure effective [**tenant isolation**](/documentation/manage-data/indexing/#tenant-index). | Immutable segments are an implementation detail transparent for users — they can delete vectors at any time, while additions and updates are applied to a mutable segment instead. This combination of mutability and immutability allows search and indexing to smoothly run simultaneously, even under heavy loads. This approach minimizes the performance impact of indexing time and allows on-the-fly configuration changes on a collection level (such as enabling or disabling data quantization) without downtimes. diff --git a/qdrant-landing/content/articles/food-discovery-demo.md b/qdrant-landing/content/articles/food-discovery-demo.md index 5f35f52fe..d82039343 100644 --- a/qdrant-landing/content/articles/food-discovery-demo.md +++ b/qdrant-landing/content/articles/food-discovery-demo.md @@ -224,7 +224,7 @@ docker-compose up -d ``` The demo will be available at `http://localhost:8001`, but you won't be able to search anything until you [import the snapshot into your Qdrant -instance](/documentation/operations/snapshots/#recover-via-api). If you don't want to bother with hosting a local one, you can use the [Qdrant +instance](/documentation/snapshots/#recover-via-api). If you don't want to bother with hosting a local one, you can use the [Qdrant Cloud](https://cloud.qdrant.io/) cluster. 4 GB RAM is enough to load all the 2 million entries. ## Fork and reuse diff --git a/qdrant-landing/content/articles/multitenancy.md b/qdrant-landing/content/articles/multitenancy.md index ce509f721..481914a19 100644 --- a/qdrant-landing/content/articles/multitenancy.md +++ b/qdrant-landing/content/articles/multitenancy.md @@ -19,14 +19,14 @@ category: vector-search-manuals # Scaling Your Machine Learning Setup: The Power of Multitenancy and Custom Sharding in Qdrant -We are seeing the topics of [multitenancy](/documentation/manage-data/multitenancy/) and [distributed deployment](/documentation/operations/distributed_deployment/#sharding) pop-up daily on our [Discord support channel](https://qdrant.to/discord). This tells us that many of you are looking to scale Qdrant along with the rest of your machine learning setup. +We are seeing the topics of [multitenancy](/documentation/manage-data/multitenancy/) and [distributed deployment](/documentation/distributed_deployment/#sharding) pop-up daily on our [Discord support channel](https://qdrant.to/discord). This tells us that many of you are looking to scale Qdrant along with the rest of your machine learning setup. Whether you are building a bank fraud-detection system, [RAG](https://qdrant.tech/articles/what-is-rag-in-ai/) for e-commerce, or services for the federal government - you will need to leverage a multitenant architecture to scale your product. In the world of SaaS and enterprise apps, this setup is the norm. It will considerably increase your application's performance and lower your hosting costs. ## Multitenancy & custom sharding with Qdrant -We have developed two major features just for this. __You can now scale a single Qdrant cluster and support all of your customers worldwide.__ Under [multitenancy](/documentation/manage-data/multitenancy/), each customer's data is completely isolated and only accessible by them. At times, if this data is location-sensitive, Qdrant also gives you the option to divide your cluster by region or other criteria that further secure your customer's access. This is called [custom sharding](/documentation/operations/distributed_deployment/#user-defined-sharding). +We have developed two major features just for this. __You can now scale a single Qdrant cluster and support all of your customers worldwide.__ Under [multitenancy](/documentation/manage-data/multitenancy/), each customer's data is completely isolated and only accessible by them. At times, if this data is location-sensitive, Qdrant also gives you the option to divide your cluster by region or other criteria that further secure your customer's access. This is called [custom sharding](/documentation/distributed_deployment/#user-defined-sharding). Combining these two will result in an efficiently-partitioned architecture that further leverages the convenience of a single Qdrant cluster. This article will briefly explain the benefits and show how you can get started using both features. @@ -41,7 +41,7 @@ Qdrant is built to excel in a single collection with a vast number of tenants. Y ## Sharding your database -With Qdrant, you can also specify a shard for each vector individually. This feature is useful if you want to [control where your data is kept in the cluster](/documentation/operations/distributed_deployment/#sharding). For example, one set of vectors can be assigned to one shard on its own node, while another set can be on a completely different node. +With Qdrant, you can also specify a shard for each vector individually. This feature is useful if you want to [control where your data is kept in the cluster](/documentation/distributed_deployment/#sharding). For example, one set of vectors can be assigned to one shard on its own node, while another set can be on a completely different node. During vector search, your operations will be able to hit only the subset of shards they actually need. In massive-scale deployments, __this can significantly improve the performance of operations that do not require the whole collection to be scanned__. @@ -49,7 +49,7 @@ This works in the other direction as well. Whenever you search for something, yo ### Common use cases -A clear use-case for this feature is managing a multitenant collection, where each tenant (let it be a user or organization) is assumed to be segregated, so they can have their data stored in separate shards. Sharding solves the problem of region-based data placement, whereby certain data needs to be kept within specific locations. To do this, however, you will need to [move your shards between nodes](/documentation/operations/distributed_deployment/#moving-shards). +A clear use-case for this feature is managing a multitenant collection, where each tenant (let it be a user or organization) is assumed to be segregated, so they can have their data stored in separate shards. Sharding solves the problem of region-based data placement, whereby certain data needs to be kept within specific locations. To do this, however, you will need to [move your shards between nodes](/documentation/distributed_deployment/#moving-shards). **Figure 2:** Users can both upsert and query shards that are relevant to them, all within the same collection. Regional sharding can help avoid cross-continental traffic. ![Qdrant Multitenancy](/articles_data/multitenancy/shards.png) @@ -79,7 +79,7 @@ client.create_shard_key("{tenant_data}", "germany") ``` In this example, your cluster is divided between Germany and Canada. Canadian and German law differ when it comes to international data transfer. Let's say you are creating a RAG application that supports the healthcare industry. Your Canadian customer data will have to be clearly separated for compliance purposes from your German customer. -Even though it is part of the same collection, data from each shard is isolated from other shards and can be retrieved as such. For additional examples on shards and retrieval, consult [Distributed Deployments](/documentation/operations/distributed_deployment/) documentation and [Qdrant Client specification](https://python-client.qdrant.tech). +Even though it is part of the same collection, data from each shard is isolated from other shards and can be retrieved as such. For additional examples on shards and retrieval, consult [Distributed Deployments](/documentation/distributed_deployment/) documentation and [Qdrant Client specification](https://python-client.qdrant.tech). ## Configure a multitenant setup for users diff --git a/qdrant-landing/content/articles/qdrant-1.2.x.md b/qdrant-landing/content/articles/qdrant-1.2.x.md index ee14c353b..2367b6ef0 100644 --- a/qdrant-landing/content/articles/qdrant-1.2.x.md +++ b/qdrant-landing/content/articles/qdrant-1.2.x.md @@ -195,7 +195,7 @@ Out-of-Memory errors. Qdrant 1.2 enters recovery mode, if enabled, when it detects a failure on startup. That makes the service halt the loading of collection data and commence operations in a partial state. This state allows for removing collections but doesn't support search or update functions. -**Recovery mode [has to be enabled by user](/documentation/operations/administration/#recovery-mode).** +**Recovery mode [has to be enabled by user](/documentation/ops-configuration/administration/#recovery-mode).** ### Appendable mmap @@ -206,7 +206,7 @@ to read more about segments, check out our docs on [vector storage](/documentati ## Security -There are two major changes in terms of [security](/documentation/operations/security/): +There are two major changes in terms of [security](/documentation/security/): 1. **API-key support** - basic authentication with a static API key to prevent unwanted access. Previously API keys were only supported in [Qdrant Cloud](https://cloud.qdrant.io/). diff --git a/qdrant-landing/content/articles/qdrant-1.7.x.md b/qdrant-landing/content/articles/qdrant-1.7.x.md index fe9d611d9..30687be2e 100644 --- a/qdrant-landing/content/articles/qdrant-1.7.x.md +++ b/qdrant-landing/content/articles/qdrant-1.7.x.md @@ -92,7 +92,7 @@ POST /collections/my_collection/points/search } ``` -If you want to know more about the user-defined sharding, please refer to the [sharding documentation](/documentation/operations/distributed_deployment/#sharding). +If you want to know more about the user-defined sharding, please refer to the [sharding documentation](/documentation/distributed_deployment/#sharding). ### Snapshot-based shard transfer @@ -101,7 +101,7 @@ That's a really more in depth technical improvement for the distributed mode use Moving shards is required for dynamical scaling of the cluster. Your data can migrate between nodes, and the way you move it is crucial for the performance of the whole system. The good old `stream_records` method (still the default one) transmits all the records between the machines and indexes them on the target node. In the case of moving the shard, it's necessary to recreate the HNSW index each time. However, with the introduction of the new `snapshot` approach, the snapshot itself, inclusive of all data and potentially quantized content, is transferred to the target node. This comprehensive snapshot includes the entire index, enabling the target node to seamlessly load it and promptly begin handling requests without the need for index recreation. -There are multiple scenarios in which you may prefer one over the other. Please check out the docs of the [shard transfer method](/documentation/operations/distributed_deployment/#shard-transfer-method) for more details and head-to-head comparison. As for now, the old `stream_records` method is still the default one, but we may decide to change it in the future. +There are multiple scenarios in which you may prefer one over the other. Please check out the docs of the [shard transfer method](/documentation/distributed_deployment/#shard-transfer-method) for more details and head-to-head comparison. As for now, the old `stream_records` method is still the default one, but we may decide to change it in the future. ## Minor improvements diff --git a/qdrant-landing/content/articles/qdrant-1.8.x.md b/qdrant-landing/content/articles/qdrant-1.8.x.md index baa56b644..5447e7074 100644 --- a/qdrant-landing/content/articles/qdrant-1.8.x.md +++ b/qdrant-landing/content/articles/qdrant-1.8.x.md @@ -65,7 +65,7 @@ This isn't mandatory, as Qdrant is by default tuned to strike the right balance This version introduces a `optimizer_cpu_budget` parameter to control the maximum number of CPUs used for indexing. -> Read more about `config.yaml` in the [configuration file](/documentation/operations/configuration/). +> Read more about `config.yaml` in the [configuration file](/documentation/ops-configuration/configuration/). ```yaml # CPU budget, how many CPUs (threads) to allocate for an optimization job. diff --git a/qdrant-landing/content/articles/vector-search-production.md b/qdrant-landing/content/articles/vector-search-production.md index 3ff10e4d5..85bb61dd0 100644 --- a/qdrant-landing/content/articles/vector-search-production.md +++ b/qdrant-landing/content/articles/vector-search-production.md @@ -88,7 +88,7 @@ Sometimes users don't properly balance HNSW search parameters. Setting the HNSW ❓ **Use Case:** A customer ran advanced similarity searches across their vast dataset of nearly 800 million vectors. Initially, they found that queries took anywhere from 10 to 20 seconds, especially when combining multiple filters and metadata fields. -> ✅ How can they retain accuracy and keep things fast? [**The answer is optimization.**](https://qdrant.tech/documentation/operations/optimize/) +> ✅ How can they retain accuracy and keep things fast? [**The answer is optimization.**](https://qdrant.tech/documentation/ops-optimization/optimize/) **Figure 1:** Qdrant is highly configurable. You can configure it for speed, precision or resource use. ![qdrant resource tradeoffs](/docs/tradeoff.png) @@ -99,7 +99,7 @@ This strategy balanced memory usage with performance: only the compact vectors n || |-| -|**Read More:** [**Optimization Guide**](https://qdrant.tech/documentation/operations/optimize/)|#optimizing-qdrant-performance-three-scenarios +|**Read More:** [**Optimization Guide**](https://qdrant.tech/documentation/ops-optimization/optimize/)|#optimizing-qdrant-performance-three-scenarios |**Read More:** [**HNSW Documentation**](https://qdrant.tech/documentation/manage-data/indexing/#vector-index)| ### Compress Your Data with Quantization Strategies @@ -155,7 +155,7 @@ Once all records are inserted, you can rebuild the index in a single pass. Consi || |-| -|**Read More:** [**Configuration Documentation**](https://qdrant.tech/documentation/operations/configuration/)| +|**Read More:** [**Configuration Documentation**](https://qdrant.tech/documentation/ops-configuration/configuration/)| ### When Indexing Falls Behind Ingestion ![vector-search-production](/articles_data/vector-search-production/vector-search-production-3.jpg) @@ -230,7 +230,7 @@ Figure: For many-tenant setups, spinning up a new collection per tenant can ball |:-:| |**"How many nodes, CPUs, RAM and storage do I need for my Qdrant Cluster?"**| -It depends. If you're just starting out - we have prepared a tool on our website to help you figure this out. For more information, [**check out the Capacity Planning document as well.**](https://qdrant.tech/documentation/operations/capacity-planning/) +It depends. If you're just starting out - we have prepared a tool on our website to help you figure this out. For more information, [**check out the Capacity Planning document as well.**](https://qdrant.tech/documentation/capacity-planning/) ✅ [**Use the sizing calculator**](https://cloud.qdrant.io/calculator) or performance testing to ensure node specs (RAM/CPU) match your workload. @@ -242,7 +242,7 @@ It depends. If you're just starting out - we have prepared a tool on our website A three-node setup provides a baseline for fault tolerance: if one node goes offline, the remaining two can continue serving queries and maintain a quorum for data consistency. This guards against hardware failures, rolling updates, and network disruptions. Fewer than three nodes leaves you vulnerable to single-point failures that can knock your entire cluster offline. -> [**We follow the Raft Protocol**](https://qdrant.tech/documentation/operations/distributed_deployment/#raft), so check out the docs and learn why this is important. +> [**We follow the Raft Protocol**](https://qdrant.tech/documentation/distributed_deployment/#raft), so check out the docs and learn why this is important. ✅ **Set a replication factor of at least 2** to tolerate node failure without losing availability. @@ -274,7 +274,7 @@ Development and staging environments often run experimental builds, tests, or si > It's quite possible that the user has multiple shards on one node, which end up handling most traffic while other nodes remain underutilized. -In this case, you should [**choose the right number of shards**](https://qdrant.tech/documentation/operations/distributed_deployment/#sharding) based on your node count and expected RPS. +In this case, you should [**choose the right number of shards**](https://qdrant.tech/documentation/distributed_deployment/#sharding) based on your node count and expected RPS. You need to implement a shard strategy that aligns with real usage patterns. First, distribute your shards across all available nodes. This will help balance the load more effectively. After redistributing the shards, run performance tests to see how it affects your system. Then add replicas and test again to see how that changes performance. @@ -285,14 +285,14 @@ Proper sharding considers data distribution and query patterns. By default, shar || |-| -|**Read More:** [**Sharding Documentation**](https://qdrant.tech/documentation/operations/distributed_deployment/#sharding)| +|**Read More:** [**Sharding Documentation**](https://qdrant.tech/documentation/distributed_deployment/#sharding)| ### Manage Your Costs by Scaling Up or Down ![vector-search-production](/articles_data/vector-search-production/vector-search-production-5.jpg) Some teams scale up for daytime surges, then scale down overnight to save resources. If you do this, ensure data is sharded and replicated appropriately, so that scaling up and down won't result in service degradation. -If using Qdrant Cloud you could also do this using the [**Replication Factor**](https://qdrant.tech/documentation/operations/distributed_deployment/#replication-factor), though it may be considered a bit of a hack. +If using Qdrant Cloud you could also do this using the [**Replication Factor**](https://qdrant.tech/documentation/distributed_deployment/#replication-factor), though it may be considered a bit of a hack. > If you have 3 nodes with just 1 shard, and replication factor 6. It will create 3 replicas (one on each node) of that shard, because it can't host more. If you add 3 more nodes at peak times, it'll automatically replicate that shard 3 more times in an attempt to match the factor of 6. @@ -308,7 +308,7 @@ If new nodes remain empty after joining, you waste resources. If departing nodes || |-| -|**Read More:** [**Distributed Deployment Documentation**](https://qdrant.tech/documentation/operations/distributed_deployment/)| +|**Read More:** [**Distributed Deployment Documentation**](https://qdrant.tech/documentation/distributed_deployment/)| |**Read More:** [**Resharding**](https://qdrant.tech/documentation/cloud/cluster-scaling/#resharding)| ### How to Predict and Test Cluster Performance @@ -331,7 +331,7 @@ Remember, cold-starts and query behaviour are dataset dependent, which is why yo || |-| -|**Read More:** [Distributed Deployment Documentation](https://qdrant.tech/documentation/operations/distributed_deployment/) +|**Read More:** [Distributed Deployment Documentation](https://qdrant.tech/documentation/distributed_deployment/) ### How to Design Your Systems to Protect Against Failure @@ -375,7 +375,7 @@ By following these comprehensive load testing practices, you'll be able to ident || |-| -|**Read More:** [**Telemetry and Monitoring Documentation**](https://qdrant.tech/documentation/operations/monitoring/)| +|**Read More:** [**Telemetry and Monitoring Documentation**](https://qdrant.tech/documentation/ops-monitoring/monitoring/)| |**Read More:** [**Cloud Monitoring Documentation**](https://qdrant.tech/documentation/hybrid-cloud/networking-logging-monitoring/) ## 4. Ensuring Disaster Recovery With Database Backups and Snapshots @@ -413,7 +413,7 @@ If you host tens of billions of vectors, store backups off-node in a different d || |-| -|**Read More:** [**Snapshot Documentation**](https://qdrant.tech/documentation/operations/snapshots/)| +|**Read More:** [**Snapshot Documentation**](https://qdrant.tech/documentation/snapshots/)| |**Read More:** [**Managed Cloud Backup Documentation**](https://qdrant.tech/documentation/cloud/backups/)| |**Read More:** [**Private Cloud Backup Documentation**](https://qdrant.tech/documentation/private-cloud/backups/)| @@ -438,7 +438,7 @@ Investigations showed they hadn't adjusted the default configuration or reserved || |-| -|**Read More:** [**Qdrant Configuration Documentation**](https://qdrant.tech/documentation/operations/configuration/)| +|**Read More:** [**Qdrant Configuration Documentation**](https://qdrant.tech/documentation/ops-configuration/configuration/)| ### Security & Governance @@ -450,7 +450,7 @@ Enabling TLS/HTTPS is essential for meeting compliance requirements in regulated > You need to protect data in transit. To enable TLS/HTTPS for encrypted traffic in production, you need to configure secure communication between clients and your Qdrant database, as well as individual cluster nodes. This involves implementing Transport Layer Security (TLS) certificates to encrypt all traffic, preventing unauthorized access and data interception. -If self-hosting, you can set up encryption yourself by [**incorporating TLS directly from the configuration**](https://qdrant.tech/documentation/operations/security/#tls) +If self-hosting, you can set up encryption yourself by [**incorporating TLS directly from the configuration**](https://qdrant.tech/documentation/security/#tls) ```text service: @@ -469,7 +469,7 @@ tls: || |-| -|**Read More:** [**Security Documentation**](https://qdrant.tech/documentation/operations/security/)| +|**Read More:** [**Security Documentation**](https://qdrant.tech/documentation/security/)| ### Setting up Access Controls in Production diff --git a/qdrant-landing/content/articles/vector-search-resource-optimization.md b/qdrant-landing/content/articles/vector-search-resource-optimization.md index d6bc25a7c..c4a38cb9f 100644 --- a/qdrant-landing/content/articles/vector-search-resource-optimization.md +++ b/qdrant-landing/content/articles/vector-search-resource-optimization.md @@ -32,12 +32,12 @@ Let's take a look at some common goals and optimization strategies: | Intended Result | Optimization Strategy | |--------------------------------|------------------------------| -| [**High Search Precision + Low Memory Expenditure**](/documentation/operations/optimize/#1-high-speed-search-with-low-memory-usage) | [**On-Disk Indexing**](/documentation/operations/optimize/#1-high-speed-search-with-low-memory-usage) | +| [**High Search Precision + Low Memory Expenditure**](/documentation/ops-optimization/optimize/#1-high-speed-search-with-low-memory-usage) | [**On-Disk Indexing**](/documentation/ops-optimization/optimize/#1-high-speed-search-with-low-memory-usage) | | [**Low Memory Expenditure + Fast Search Speed**](/documentation/manage-data/quantization/) | [**Quantization**](/documentation/manage-data/quantization/) | -| [**High Search Precision + Fast Search Speed**](/documentation/operations/optimize/#3-high-precision-with-high-speed-search) | [**RAM Storage + Quantization**](/documentation/operations/optimize/#3-high-precision-with-high-speed-search) | -| [**Balance Latency vs Throughput**](/documentation/operations/optimize/#balancing-latency-and-throughput) | [**Segment Configuration**](/documentation/operations/optimize/#balancing-latency-and-throughput) | +| [**High Search Precision + Fast Search Speed**](/documentation/ops-optimization/optimize/#3-high-precision-with-high-speed-search) | [**RAM Storage + Quantization**](/documentation/ops-optimization/optimize/#3-high-precision-with-high-speed-search) | +| [**Balance Latency vs Throughput**](/documentation/ops-optimization/optimize/#balancing-latency-and-throughput) | [**Segment Configuration**](/documentation/ops-optimization/optimize/#balancing-latency-and-throughput) | -After this article, check out the code samples in our docs on [**Qdrant’s Optimization Methods**](/documentation/operations/optimize/). +After this article, check out the code samples in our docs on [**Qdrant’s Optimization Methods**](/documentation/ops-optimization/optimize/). --- @@ -57,7 +57,7 @@ Qdrant uses the [**HNSW (Hierarchical Navigable Small World Graph) algorithm**]( Working with massive datasets that contain billions of vectors demands significant resources—and those resources come with a price. While Qdrant provides reasonable defaults, tailoring them to your specific use case can unlock optimal performance. Here’s what you need to know. -The following parameters give you the flexibility to fine-tune Qdrant’s performance for your specific workload. You can modify them directly in Qdrant's [**configuration**](https://qdrant.tech/documentation/operations/configuration/) files or at the collection and named vector levels for more granular control. +The following parameters give you the flexibility to fine-tune Qdrant’s performance for your specific workload. You can modify them directly in Qdrant's [**configuration**](https://qdrant.tech/documentation/ops-configuration/configuration/) files or at the collection and named vector levels for more granular control. **Figure 3:** A description of three key HNSW parameters. @@ -325,7 +325,7 @@ Here’s how to choose the shard_number: | **Plan for Scalability** | Start with at least **2 shards per node** to allow room for future growth. | | **Future-Proofing** | Starting with around **12 shards** is a good rule of thumb. This setup allows your system to scale seamlessly from 1 to 12 nodes without requiring re-sharding. | -Learn more about [**Sharding in Distributed Deployment**](/documentation/operations/distributed_deployment/) +Learn more about [**Sharding in Distributed Deployment**](/documentation/distributed_deployment/) --- @@ -584,7 +584,7 @@ Here are some important metrics to monitor: | grpc_responses_avg_duration_seconds | | Average response duration in gRPC API | | rest_responses_fail_total | | Total number of failed responses (REST) | -Read more about [**Qdrant Open Source Monitoring**](/documentation/operations/monitoring/) and [**Qdrant Cloud Monitoring**](/documentation/cloud/cluster-monitoring/) for managed clusters. +Read more about [**Qdrant Open Source Monitoring**](/documentation/ops-monitoring/monitoring/) and [**Qdrant Cloud Monitoring**](/documentation/cloud/cluster-monitoring/) for managed clusters. _________________________________________________________________________ ## Recap: When Should You Optimize? diff --git a/qdrant-landing/content/articles/what-is-a-vector-database.md b/qdrant-landing/content/articles/what-is-a-vector-database.md index 10886ade0..de2507ea5 100644 --- a/qdrant-landing/content/articles/what-is-a-vector-database.md +++ b/qdrant-landing/content/articles/what-is-a-vector-database.md @@ -414,7 +414,7 @@ client.create_collection( We recommend using sharding and replication together so that your data is both split across nodes and replicated for availability. -For more details on features like **user-defined sharding, node failure recovery**, and **consistency guarantees**, see our guide on [Distributed Deployment.](https://qdrant.tech/documentation/operations/distributed_deployment/) +For more details on features like **user-defined sharding, node failure recovery**, and **consistency guarantees**, see our guide on [Distributed Deployment.](https://qdrant.tech/documentation/distributed_deployment/) ## Multitenancy: Data Isolation for Multi-Tenant Architectures @@ -477,7 +477,7 @@ You can easily setup your access tokens and secure access to sensitive data thro Qdrant Web UI for generating a new access token. -By default, Qdrant instances are **unsecured**, so it's important to configure security measures before moving to production. To learn more about how to configure security for your Qdrant instance and other advanced options, please check out the [official Qdrant documentation on security.](https://qdrant.tech/documentation/operations/security/) +By default, Qdrant instances are **unsecured**, so it's important to configure security measures before moving to production. To learn more about how to configure security for your Qdrant instance and other advanced options, please check out the [official Qdrant documentation on security.](https://qdrant.tech/documentation/security/) ## Time to Experiment diff --git a/qdrant-landing/content/blog/2025-recap.md b/qdrant-landing/content/blog/2025-recap.md index c21c0660a..a2ff9f4c0 100644 --- a/qdrant-landing/content/blog/2025-recap.md +++ b/qdrant-landing/content/blog/2025-recap.md @@ -57,8 +57,8 @@ In 2025, we focused on giving teams explicit control over retrieval quality as a To support large, cost-sensitive workloads, we targeted the biggest performance bottlenecks in production systems. New improvements help teams scale indexing and querying without over-provisioning memory or compute. **Related enhancements:** -• [GPU-Accelerated HNSW Indexing](https://qdrant.tech/documentation/operations/running-with-gpu/) unlocks up to an order-of-magnitude faster ingestion -• [Inline Storage](https://qdrant.tech/documentation/operations/optimize/#inline-storage-in-hnsw-index) embedded quantized vectors directly into the graph to dramatically improve disk-based search performance +• [GPU-Accelerated HNSW Indexing](https://qdrant.tech/documentation/ops-configuration/running-with-gpu/) unlocks up to an order-of-magnitude faster ingestion +• [Inline Storage](https://qdrant.tech/documentation/ops-optimization/optimize/#inline-storage-in-hnsw-index) embedded quantized vectors directly into the graph to dramatically improve disk-based search performance • [Custom storage engine](https://qdrant.tech/articles/gridstore-key-value-storage/) optimized for predictable low-latency access • [Incremental HNSW indexing](https://qdrant.tech/documentation/database-tutorials/bulk-upload/?q=incremental+hnsw#choose-an-indexing-strategy) for upsert-heavy workloads • HNSW graph compression to reduce memory footprint diff --git a/qdrant-landing/content/blog/beta-database-migration-tool.md b/qdrant-landing/content/blog/beta-database-migration-tool.md index 191f97a83..3eccaa22b 100644 --- a/qdrant-landing/content/blog/beta-database-migration-tool.md +++ b/qdrant-landing/content/blog/beta-database-migration-tool.md @@ -19,7 +19,7 @@ We’ve launched the **beta** of our Qdrant **Vector Data Migration Tool**, desi This powerful tool streams all vectors from a source collection to a target Qdrant instance in live batches. It supports migrations from one Qdrant deployment to another, including from open source to Qdrant Cloud or between cloud regions. But that's not all. You can also migrate your data from other vector databases directly into Qdrant. All with a single command. -Unlike Qdrant’s included [snapshot migration method](https://qdrant.tech/documentation/operations/snapshots/), which requires consistent node-specific snapshots, our migration tool enables you to easily migrate data between different Qdrant database clusters in streaming batches. The only requirement is that the vector size and distance function must match. +Unlike Qdrant’s included [snapshot migration method](https://qdrant.tech/documentation/snapshots/), which requires consistent node-specific snapshots, our migration tool enables you to easily migrate data between different Qdrant database clusters in streaming batches. The only requirement is that the vector size and distance function must match. This is especially useful if you want to change the collection configuration on the target, for example by choosing a different replication factor or quantization method. diff --git a/qdrant-landing/content/blog/case-study-anima-health.md b/qdrant-landing/content/blog/case-study-anima-health.md index 0b2de55be..83086d242 100644 --- a/qdrant-landing/content/blog/case-study-anima-health.md +++ b/qdrant-landing/content/blog/case-study-anima-health.md @@ -57,7 +57,7 @@ Beyond coding, Anima uses Qdrant to understand documents at scale. By working wi Several factors made Qdrant a strong fit for healthcare workloads. -[Deployment flexibility](https://qdrant.tech/documentation/operations/installation/) was non-negotiable. Anima requires data to remain at rest in the UK, allowing them to make strong guarantees to customers about compliance and residency. Qdrant’s self-hosted and region-controlled deployment options enabled this without compromising performance. +[Deployment flexibility](https://qdrant.tech/documentation/installation/) was non-negotiable. Anima requires data to remain at rest in the UK, allowing them to make strong guarantees to customers about compliance and residency. Qdrant’s self-hosted and region-controlled deployment options enabled this without compromising performance. Cost predictability also played a critical role. With a fixed infrastructure cost for vector search, Anima could use retrieval across multiple passes in their pipelines. This unlocked higher-quality results without eroding margins. diff --git a/qdrant-landing/content/blog/case-study-fieldy.md b/qdrant-landing/content/blog/case-study-fieldy.md index 06a744cdc..1e85d6aa5 100644 --- a/qdrant-landing/content/blog/case-study-fieldy.md +++ b/qdrant-landing/content/blog/case-study-fieldy.md @@ -48,7 +48,7 @@ For the engineering team, these failures had two serious implications. First, mi After evaluating alternatives, Fieldy selected [Qdrant](http://qdrant.tech) for its stability, straightforward configuration, and suitability for self-hosted deployment. They opted to run Qdrant in the same environment as their backend services, ensuring low-latency access and avoiding the cross-region connectivity issues that had contributed to failures in the previous architecture. -The migration process took less than a week. The team reused their existing vector schema to avoid redesigning their indexing logic during the transition. Embeddings, generated using Cohere’s multilingual v3 model, were batched locally before ingestion, replacing the integrated embedding calls previously handled within Weaviate. Following [Qdrant best practices](https://qdrant.tech/documentation/operations/optimize/), they disabled indexing during bulk import to maximize throughput, re-enabling it only after the migration was complete. The backend API calls were updated to use Qdrant’s gRPC interface, and [hybrid search](https://qdrant.tech/articles/hybrid-search/) with BM25 was combined with dense vector retrieval via [Reciprocal Rank Fusion (RRF)](https://qdrant.tech/documentation/search/hybrid-queries/#hybrid-search) for relevance scoring. +The migration process took less than a week. The team reused their existing vector schema to avoid redesigning their indexing logic during the transition. Embeddings, generated using Cohere’s multilingual v3 model, were batched locally before ingestion, replacing the integrated embedding calls previously handled within Weaviate. Following [Qdrant best practices](https://qdrant.tech/documentation/ops-optimization/optimize/), they disabled indexing during bulk import to maximize throughput, re-enabling it only after the migration was complete. The backend API calls were updated to use Qdrant’s gRPC interface, and [hybrid search](https://qdrant.tech/articles/hybrid-search/) with BM25 was combined with dense vector retrieval via [Reciprocal Rank Fusion (RRF)](https://qdrant.tech/documentation/search/hybrid-queries/#hybrid-search) for relevance scoring. ### Architecture after migration diff --git a/qdrant-landing/content/blog/case-study-nyris.md b/qdrant-landing/content/blog/case-study-nyris.md index 454373a87..41b4a2381 100644 --- a/qdrant-landing/content/blog/case-study-nyris.md +++ b/qdrant-landing/content/blog/case-study-nyris.md @@ -57,8 +57,8 @@ As part of their selection process, Nyris evaluated several critical factors to Nyris has found several aspects of Qdrant particularly beneficial in their production environment: -- **Enhanced Security with JWT**: [JSON Web Tokens](https://qdrant.tech/documentation/operations/security/#granular-access-control-with-jwt) provide enhanced security and performance, critical for safeguarding their data. -- **Seamless Scalability**: Qdrant's ability to [scale effortlessly across nodes](https://qdrant.tech/documentation/operations/distributed_deployment/) ensures consistent high performance, even as Nyris's data volume grows. +- **Enhanced Security with JWT**: [JSON Web Tokens](https://qdrant.tech/documentation/security/#granular-access-control-with-jwt) provide enhanced security and performance, critical for safeguarding their data. +- **Seamless Scalability**: Qdrant's ability to [scale effortlessly across nodes](https://qdrant.tech/documentation/distributed_deployment/) ensures consistent high performance, even as Nyris's data volume grows. - **Flexible Search Options**: The availability of both graph-based and brute-force search methods offers Nyris the flexibility to tailor the search approach to specific use case requirements. - **Versatile Data Handling**: Qdrant imposes almost no restrictions on data types and vector sizes, allowing Nyris to manage diverse and complex datasets effectively. - **Built with Rust**: The use of [Rust](https://qdrant.tech/articles/why-rust/) ensures superior performance and future-proofing, while its open-source nature allows Nyris to inspect and customize the code as necessary. diff --git a/qdrant-landing/content/blog/case-study-voiceflow.md b/qdrant-landing/content/blog/case-study-voiceflow.md index 882723fb1..9621be288 100644 --- a/qdrant-landing/content/blog/case-study-voiceflow.md +++ b/qdrant-landing/content/blog/case-study-voiceflow.md @@ -28,7 +28,7 @@ partition: case-studies As part of this development, the Voiceflow engineering team was looking for a [vector database](/qdrant-vector-database/) solution to power their RAG setup. They evaluated various vector databases based on several key factors: -- **Performance**: The ability to [handle the scale](/documentation/operations/distributed_deployment/) required by Voiceflow, supporting hundreds of thousands of projects efficiently. +- **Performance**: The ability to [handle the scale](/documentation/distributed_deployment/) required by Voiceflow, supporting hundreds of thousands of projects efficiently. - **Metadata**: The capability to tag data and chunks and retrieve based on those values, essential for organizing and accessing specific information swiftly. - **Managed Solution**: The availability of a [managed service](/documentation/cloud/) with automated maintenance, scaling, and security, freeing the team from infrastructure concerns. diff --git a/qdrant-landing/content/blog/comparing-qdrant-vs-pinecone-vector-databases.md b/qdrant-landing/content/blog/comparing-qdrant-vs-pinecone-vector-databases.md index e1efde5e4..e7a1d232f 100644 --- a/qdrant-landing/content/blog/comparing-qdrant-vs-pinecone-vector-databases.md +++ b/qdrant-landing/content/blog/comparing-qdrant-vs-pinecone-vector-databases.md @@ -46,12 +46,12 @@ Qdrant is highly scalable and performant: it can handle billions of vectors effi - **Advanced Similarity Search:** Qdrant supports various similarity [search](https://qdrant.tech/documentation/search/search/) metrics like dot product, cosine similarity, Euclidean distance, and Manhattan distance. You can store additional information along with vectors, known as [payload](https://qdrant.tech/documentation/manage-data/payload/) in Qdrant terminology. A payload is any JSON formatted data. - **Built Using Rust:** Qdrant is built with Rust, and leverages its performance and efficiency. Rust is famed for its [memory safety](https://arxiv.org/abs/2206.05503) without the overhead of a garbage collector, and rivals C and C++ in speed. -- **Scaling and Multitenancy**: Qdrant supports both vertical and horizontal scaling and uses the Raft consensus protocol for [distributed deployments](https://qdrant.tech/documentation/operations/distributed_deployment/). Developers can run Qdrant clusters with replicas and shards, and seamlessly scale to handle large datasets. Qdrant also supports [multitenancy](https://qdrant.tech/documentation/manage-data/multitenancy/) where developers can create single collections and partition them using payload. +- **Scaling and Multitenancy**: Qdrant supports both vertical and horizontal scaling and uses the Raft consensus protocol for [distributed deployments](https://qdrant.tech/documentation/distributed_deployment/). Developers can run Qdrant clusters with replicas and shards, and seamlessly scale to handle large datasets. Qdrant also supports [multitenancy](https://qdrant.tech/documentation/manage-data/multitenancy/) where developers can create single collections and partition them using payload. - **Payload Indexing and Filtering:** Just as Qdrant allows attaching any JSON payload to vectors, it also supports payload indexing and [filtering](https://qdrant.tech/documentation/search/filtering/) with a wide range of data types and query conditions, including keyword matching, full-text filtering, numerical ranges, nested object filters, and [geo](https://qdrant.tech/documentation/search/filtering/#geo)filtering. - **Hybrid Search with Sparse Vectors:** Qdrant supports both dense and [sparse vectors](https://qdrant.tech/articles/sparse-vectors/), thereby enabling hybrid search capabilities. Sparse vectors are numerical representations of data where most of the elements are zero. Developers can combine search results from dense and sparse vectors, where sparse vectors ensure that results containing the specific keywords are returned and dense vectors identify semantically similar results. - **Built-In Vector Quantization:** Qdrant offers three different [quantization](https://qdrant.tech/documentation/manage-data/quantization/) options to developers to optimize resource usage. Scalar quantization balances accuracy, speed, and compression by converting 32-bit floats to 8-bit integers. Binary quantization, the fastest method, significantly reduces memory usage. Product quantization offers the highest compression, and is perfect for memory-constrained scenarios. - **Flexible Deployment Options:** Qdrant offers a range of deployment options. Developers can easily set up Qdrant (or Qdrant cluster) [locally](https://qdrant.tech/documentation/quickstart/#download-and-run) using Docker for free. [Qdrant Cloud](https://qdrant.tech/cloud/), on the other hand, is a scalable, managed solution that provides easy access with flexible pricing. Additionally, Qdrant offers [Hybrid Cloud](https://qdrant.tech/hybrid-cloud/) which integrates Kubernetes clusters from cloud, on-premises, or edge, into an enterprise-grade managed service. -- **Security through API Keys, JWT and RBAC:** Qdrant offers developers various ways to [secure](https://qdrant.tech/documentation/operations/security/) their instances. For simple authentication, developers can use API keys (including Read Only API keys). For more granular access control, it offers JSON Web Tokens (JWT) and the ability to build Role-Based Access Control (RBAC). TLS can be enabled to secure connections. Qdrant is also [SOC 2 Type II](https://qdrant.tech/blog/qdrant-soc2-type2-audit/) certified. +- **Security through API Keys, JWT and RBAC:** Qdrant offers developers various ways to [secure](https://qdrant.tech/documentation/security/) their instances. For simple authentication, developers can use API keys (including Read Only API keys). For more granular access control, it offers JSON Web Tokens (JWT) and the ability to build Role-Based Access Control (RBAC). TLS can be enabled to secure connections. Qdrant is also [SOC 2 Type II](https://qdrant.tech/blog/qdrant-soc2-type2-audit/) certified. Additionally, Qdrant integrates seamlessly with popular machine learning frameworks such as [LangChain](https://qdrant.tech/blog/using-qdrant-and-langchain/), LlamaIndex, and Haystack; and Qdrant Hybrid Cloud integrates seamlessly with AWS, DigitalOcean, Google Cloud, Linode, Oracle Cloud, OpenShift, and Azure, among others. diff --git a/qdrant-landing/content/blog/cve-2024-2221-response.md b/qdrant-landing/content/blog/cve-2024-2221-response.md index 6a5c83872..70b103784 100644 --- a/qdrant-landing/content/blog/cve-2024-2221-response.md +++ b/qdrant-landing/content/blog/cve-2024-2221-response.md @@ -45,13 +45,13 @@ guide](/documentation/cloud/authentication/#test-cluster-access). If your Qdrant deployment is local, you do not need an API key. Your next step depends on how you installed Qdrant. For details, read the -[Qdrant Installation](/documentation/operations/installation/) +[Qdrant Installation](/documentation/installation/) guide. #### If you use the Qdrant container or binary Upgrade your deployment. Run the commands in the applicable section of the -[Qdrant Installation](/documentation/operations/installation/) +[Qdrant Installation](/documentation/installation/) guide. The default commands automatically pull the latest version of Qdrant. #### If you use the Qdrant helm chart diff --git a/qdrant-landing/content/blog/cve-2024-3829-response.md b/qdrant-landing/content/blog/cve-2024-3829-response.md index 0291a3975..5e37d02db 100644 --- a/qdrant-landing/content/blog/cve-2024-3829-response.md +++ b/qdrant-landing/content/blog/cve-2024-3829-response.md @@ -45,13 +45,13 @@ guide](https://qdrant.tech/documentation/cloud/quickstart-cloud/#step-2-test-clu If your Qdrant deployment is local, you do not need an API key. Your next step depends on how you installed Qdrant. For details, read the -[Qdrant Installation](https://qdrant.tech/documentation/operations/installation/) +[Qdrant Installation](https://qdrant.tech/documentation/installation/) guide. #### If you use the Qdrant container or binary Upgrade your deployment. Run the commands in the applicable section of the -[Qdrant Installation](https://qdrant.tech/documentation/operations/installation/) +[Qdrant Installation](https://qdrant.tech/documentation/installation/) guide. The default commands automatically pull the latest version of Qdrant. #### If you use the Qdrant helm chart diff --git a/qdrant-landing/content/blog/legal-tech-builders-guide.md b/qdrant-landing/content/blog/legal-tech-builders-guide.md index cd253a6ea..023d0bc0c 100644 --- a/qdrant-landing/content/blog/legal-tech-builders-guide.md +++ b/qdrant-landing/content/blog/legal-tech-builders-guide.md @@ -85,7 +85,7 @@ Leveraging Late-Interaction Models for Rich Documents Traditional OCR pipelines can add complexity and create accuracy challenges. But late-interaction models simplify the ingestion pipeline by running at the reranking stage. -Models like ([ColPali](https://qdrant.tech/blog/qdrant-colpali/) and ColQwen) bypass traditional OCR pipelines, directly processing images of complex documents. They enhance accuracy by maintaining original layouts and contextual integrity, simplifying your retrieval pipelines. The tradeoff is a heavier application, but these challenges can be addressed with further [optimization](https://qdrant.tech/documentation/operations/optimize/)*.* +Models like ([ColPali](https://qdrant.tech/blog/qdrant-colpali/) and ColQwen) bypass traditional OCR pipelines, directly processing images of complex documents. They enhance accuracy by maintaining original layouts and contextual integrity, simplifying your retrieval pipelines. The tradeoff is a heavier application, but these challenges can be addressed with further [optimization](https://qdrant.tech/documentation/ops-optimization/optimize/)*.* #### Enabling highly granular accuracy for complex legal searches diff --git a/qdrant-landing/content/blog/qdrant-1.10.x.md b/qdrant-landing/content/blog/qdrant-1.10.x.md index 0fd9e7e4c..ffdd0ca62 100644 --- a/qdrant-landing/content/blog/qdrant-1.10.x.md +++ b/qdrant-landing/content/blog/qdrant-1.10.x.md @@ -669,7 +669,7 @@ documentation, making it easier to navigate and find the information you need. ## S3 Snapshot Storage -Qdrant **Collections**, **Shards** and **Storage** can be backed up with [Snapshots](/documentation/operations/snapshots/) and saved in case of data loss or other data transfer purposes. These snapshots can be quite large and the resources required to maintain them can result in higher costs. AWS S3 and other S3-compatible implementations like [min.io](https://min.io/) is a great low-cost alternative that can hold snapshots without incurring high costs. It is globally reliable, scalable and resistant to data loss. +Qdrant **Collections**, **Shards** and **Storage** can be backed up with [Snapshots](/documentation/snapshots/) and saved in case of data loss or other data transfer purposes. These snapshots can be quite large and the resources required to maintain them can result in higher costs. AWS S3 and other S3-compatible implementations like [min.io](https://min.io/) is a great low-cost alternative that can hold snapshots without incurring high costs. It is globally reliable, scalable and resistant to data loss. You can configure S3 storage settings in the [config.yaml](https://github.com/qdrant/qdrant/blob/master/config/config.yaml), specifically with `snapshots_storage`. @@ -697,7 +697,7 @@ storage: secret_key: your_secret_key_here ``` -*Read more about [S3 snapshot storage](/documentation/operations/snapshots/#s3) and [configuration](/documentation/operations/configuration/).* +*Read more about [S3 snapshot storage](/documentation/snapshots/#s3) and [configuration](/documentation/ops-configuration/configuration/).* This integration allows for a more convenient distribution of snapshots. Users of **any S3-compatible object storage** can now benefit from other platform services, such as automated workflows and disaster recovery options. S3's encryption and access control ensure secure storage and regulatory compliance. Additionally, S3 supports performance optimization through various storage classes and efficient data transfer methods, enabling quick and effective snapshot retrieval and management. diff --git a/qdrant-landing/content/blog/qdrant-1.12.x.md b/qdrant-landing/content/blog/qdrant-1.12.x.md index ccd3e5448..d236e3375 100644 --- a/qdrant-landing/content/blog/qdrant-1.12.x.md +++ b/qdrant-landing/content/blog/qdrant-1.12.x.md @@ -255,7 +255,7 @@ PUT /collections/{collection_name}/index ![geo-index-disk](/blog/qdrant-1.12.x/geo-index-disk.png) -> To learn how to get the best performance from Qdrant, read the [**Optimization Guide**](/documentation/operations/optimize/). +> To learn how to get the best performance from Qdrant, read the [**Optimization Guide**](/documentation/ops-optimization/optimize/). ## Just the Beginning diff --git a/qdrant-landing/content/blog/qdrant-1.13.x.md b/qdrant-landing/content/blog/qdrant-1.13.x.md index 6540aadcc..aed404359 100644 --- a/qdrant-landing/content/blog/qdrant-1.13.x.md +++ b/qdrant-landing/content/blog/qdrant-1.13.x.md @@ -62,13 +62,13 @@ This experiment didn't require any changes to the codebase, and everything worke - **Full Feature Support:** GPU indexing supports **all quantization options and datatypes** implemented in Qdrant. - **Large-Scale Benefits:** Fast indexing unlocks larger size of segments, which leads to **higher RPS on the same hardware**. -### [Instructions & Documentation](/documentation/operations/running-with-gpu/) +### [Instructions & Documentation](/documentation/ops-configuration/running-with-gpu/) The setup is simple, with pre-configured Docker images [**(check Docker Registry)**](https://hub.docker.com/r/qdrant/qdrant/tags) for GPU environments like NVIDIA and AMD. We've made it so you can enable GPU indexing with minimal configuration changes. > Note: Logs will clearly indicate GPU detection and usage for transparency. -*Read more about this feature in the [**GPU Indexing Documentation**](/documentation/operations/running-with-gpu/)* +*Read more about this feature in the [**GPU Indexing Documentation**](/documentation/ops-configuration/running-with-gpu/)* #### Interview With the Creator of GPU Indexing @@ -212,7 +212,7 @@ client.CreateCollection(context.Background(), &qdrant.CreateCollection{ ``` > You may also use the `PATCH` request to enable Strict Mode on an existing collection. -*Read more about Strict Mode in the [**Database Administration Guide**](/documentation/operations/administration/#strict-mode)* +*Read more about Strict Mode in the [**Database Administration Guide**](/documentation/ops-configuration/administration/#strict-mode)* ## HNSW Graph Compression diff --git a/qdrant-landing/content/blog/qdrant-1.16.x.md b/qdrant-landing/content/blog/qdrant-1.16.x.md index 0c1f4e92f..d8d3205ac 100644 --- a/qdrant-landing/content/blog/qdrant-1.16.x.md +++ b/qdrant-landing/content/blog/qdrant-1.16.x.md @@ -32,7 +32,7 @@ Additionally, version 1.16 introduces a new conditional update API, facilitating Multitenancy is a common requirement for SaaS applications, where multiple customers (tenants) share the same database instance. In Qdrant, when an instance is shared between multiple users, you may need to partition vectors by user. This is done so that each user can only access their own vectors and can’t see the vectors of other users. To implement multitenancy in Qdrant, there are two main approaches: - [Payload-based multitenancy](/documentation/manage-data/multitenancy/), which works well when you have a large number of small tenants. This causes practically no overhead. Quite the opposite: a query with a tenant payload filter can be faster than a full search. -- [Shard-based multitenancy](/documentation/operations/distributed_deployment/#user-defined-sharding), designed for when you have a smaller number of larger tenants. This works well when each tenant requires isolation and dedicated resources. Separating tenants by shard prevents a classic noisy neighbor problem where a single high-volume tenant can force the cluster to scale for everyone, increasing costs and reducing performance for smaller tenants. However, shard-based multitenancy is not a good solution when you have a large number of small tenants, as each shard incurs some overhead. +- [Shard-based multitenancy](/documentation/distributed_deployment/#user-defined-sharding), designed for when you have a smaller number of larger tenants. This works well when each tenant requires isolation and dedicated resources. Separating tenants by shard prevents a classic noisy neighbor problem where a single high-volume tenant can force the cluster to scale for everyone, increasing costs and reducing performance for smaller tenants. However, shard-based multitenancy is not a good solution when you have a large number of small tenants, as each shard incurs some overhead. Real-world usage patterns often fall between these two use cases. It's common to have a small number of large tenants and a huge tail of smaller ones. You may even have tenants that grow over time, starting small and eventually becoming large enough to require dedicated resources. @@ -40,7 +40,7 @@ In version 1.16, Qdrant can now efficiently combine the two multitenancy approac The main principles behind Tiered Multitenancy are: -- [User-defined Sharding](/documentation/operations/distributed_deployment/#user-defined-sharding) allows you to create named shards within a collection. It enables you to isolate large tenants into their own shards. A multitenant collection can consist of a shared "fallback" shard for small tenants and multiple dedicated shards for large tenants. +- [User-defined Sharding](/documentation/distributed_deployment/#user-defined-sharding) allows you to create named shards within a collection. It enables you to isolate large tenants into their own shards. A multitenant collection can consist of a shared "fallback" shard for small tenants and multiple dedicated shards for large tenants. - **Fallback shards** - a special routing mechanism that allows Qdrant to route a request to either a dedicated shard (if it exists) or to a shared fallback shard. This keeps requests unified, without the need to know whether a tenant is dedicated or shared. - [Tenant promotion](/documentation/manage-data/multitenancy/#promote-tenant-to-dedicated-shard) - a mechanism that makes it possible to "promote" tenants from the shared Fallback Shard to their own dedicated shard when they grow large enough. This process is based on Qdrant’s internal shard transfer mechanism, which makes promotion completely transparent for the application. Both read and write requests are supported during the promotion process. @@ -126,9 +126,9 @@ For instance, querying 1 million vectors with the HNSW parameters `m` set to 16 However, disk-based storage has a property we can exploit to reduce the number of random access reads: paged reading. Disk devices typically read a full page (4KB or more) of data at once. Traditional tree-based data structures, such as B-trees, have used this property effectively. However, in graph-based structures like the HNSW index, grouping connected nodes into pages is not straightforward due to each node potentially having an arbitrary number of connections to other nodes. -With Qdrant version 1.16, you can make use of paged reading through a new feature called [inline storage](/documentation/operations/optimize/#inline-storage-in-hnsw-index). Inline storage allows for storing quantized vector data directly inside the HNSW nodes. This offers faster read access, at the cost of additional storage space. +With Qdrant version 1.16, you can make use of paged reading through a new feature called [inline storage](/documentation/ops-optimization/optimize/#inline-storage-in-hnsw-index). Inline storage allows for storing quantized vector data directly inside the HNSW nodes. This offers faster read access, at the cost of additional storage space. -Inline storage can be enabled by [setting a collection's HNSW configuration `inline_storage` option to `true`](/documentation/operations/optimize/#inline-storage-in-hnsw-index). It requires quantization to be enabled. +Inline storage can be enabled by [setting a collection's HNSW configuration `inline_storage` option to `true`](/documentation/ops-optimization/optimize/#inline-storage-in-hnsw-index). It requires quantization to be enabled.
@@ -316,8 +316,8 @@ In version 1.16, we have revamped the Web UI with a fresh new look and improved ![Section 7](/blog/qdrant-1.16.x/section-7.png) - The constant `k` that determines how Reciprocal Rank Fusion (RRF) fuses result sets [is now configurable](/documentation/search/hybrid-queries/#parametrized-rrf). -- The Metrics API now exposes [additional metrics](/documentation/operations/monitoring/#metrics) that help monitor your deployment's health. -- In strict mode, it is now possible to [configure the maximum number of payload indices](/documentation/operations/administration/#maximum-number-of-payload-index-count). +- The Metrics API now exposes [additional metrics](/documentation/ops-monitoring/monitoring/#metrics) that help monitor your deployment's health. +- In strict mode, it is now possible to [configure the maximum number of payload indices](/documentation/ops-configuration/administration/#maximum-number-of-payload-index-count). - It's now possible to [attach custom metadata to collections](/documentation/manage-data/collections/#collection-metadata). For a full list of all changes in version 1.16, please refer to the [change log](https://github.com/qdrant/qdrant/releases/tag/v1.16.0). diff --git a/qdrant-landing/content/blog/qdrant-1.17.x.md b/qdrant-landing/content/blog/qdrant-1.17.x.md index bfa6c9c44..4d14892c1 100644 --- a/qdrant-landing/content/blog/qdrant-1.17.x.md +++ b/qdrant-landing/content/blog/qdrant-1.17.x.md @@ -78,11 +78,11 @@ We are continuously working to enhance the operational observability of Qdrant c Qdrant’s API exposes a `/telemetry` endpoint which provides information about the current state of a peer in a cluster, including the number of vectors, shards, and other useful information. However, obtaining a complete view of the entire cluster using this endpoint is not straightforward, requiring querying each peer and piecing together a complete view yourself. -In version 1.17, we’re introducing a new [`/cluster/telemetry` endpoint](/documentation/operations/monitoring/#cluster-wide-telemetry). This API provides information about all peers in a cluster, offering insights into cluster-wide operations such as leader elections, resharding, and shard transfers. +In version 1.17, we’re introducing a new [`/cluster/telemetry` endpoint](/documentation/ops-monitoring/monitoring/#cluster-wide-telemetry). This API provides information about all peers in a cluster, offering insights into cluster-wide operations such as leader elections, resharding, and shard transfers. ### Segment Optimization Monitoring -Optimization is a background process where Qdrant removes data marked for deletion, merges segments, and creates indexes. To improve visibility into this process, this release introduces [segment optimization monitoring capabilities](/documentation/operations/optimizer/#optimization-monitoring). +Optimization is a background process where Qdrant removes data marked for deletion, merges segments, and creates indexes. To improve visibility into this process, this release introduces [segment optimization monitoring capabilities](/documentation/ops-optimization/optimizer/#optimization-monitoring). A new `/collections/{collection_name}/optimizations` API endpoint provides cluster-wide information about the current optimization status, as well as detailed information for current and past optimization operations. Because the output of the API can be verbose, we’ve added a new Optimizations tab to the Collections interface in the Web UI that makes it easier to analyze the data. Here, you can find an overview of the current optimization status, a timeline of current and past optimization operations, and a breakdown of the tasks in a specific cycle and their durations. @@ -115,7 +115,7 @@ Many people have been asking about point filtering in web UI. And now it's back, As an open source project, we welcome contributions from the Qdrant community. This release features two contributions from community members: - Not all payload field indexes are used in combination with dense vector queries. With this release, you can [specify whether individual payload field indexes should be reflected in the HNSW index](/documentation/manage-data/indexing/#disable-the-creation-of-extra-edges-for-payload-fields). -- A new API endpoint is available to [list all user-defined shard keys](/documentation/operations/distributed_deployment/#user-defined-sharding). +- A new API endpoint is available to [list all user-defined shard keys](/documentation/distributed_deployment/#user-defined-sharding). Additionally, this release adds the following features: @@ -123,7 +123,7 @@ Additionally, this release adds the following features: - To speed up the recovery of the replicas after they’ve been down, shards will [increase the size of their write-ahead log](https://github.com/qdrant/qdrant/pull/7834) when they detect that one of their remote replicas is unavailable. - Reciprocal Rank Fusion (RRF) combines multiple query results into one list, but its default equal weighting can let weaker rankers dilute stronger ones. [Weighted RRF](/documentation/search/hybrid-queries/#reciprocal-rank-fusion-rrf) in Qdrant 1.17 addresses this by letting you assign weights to individual queries. - A new [user interface in the Web UI enables resharding collections](https://github.com/qdrant/qdrant-web-ui/pull/341) on Qdrant Cloud. -- Qdrant now supports [audit logging](/documentation/operations/security/#audit-logging) to track all API operations that require authentication or authorization. +- Qdrant now supports [audit logging](/documentation/security/#audit-logging) to track all API operations that require authentication or authorization. - [External provider API keys for inference requests](/documentation/inference/#external-embedding-model-providers) can now be provided in the request header. For a full list of all changes in version 1.17, please refer to the [change log](https://github.com/qdrant/qdrant/releases/tag/v1.17.0). diff --git a/qdrant-landing/content/blog/qdrant-1.9.x.md b/qdrant-landing/content/blog/qdrant-1.9.x.md index b2650f284..e4e1831ec 100644 --- a/qdrant-landing/content/blog/qdrant-1.9.x.md +++ b/qdrant-landing/content/blog/qdrant-1.9.x.md @@ -28,7 +28,7 @@ tags: Historically, our API key supported basic read and write operations. However, recognizing the evolving needs of our user base, especially large organizations, we've implemented additional options for finer control over data access within internal environments. -Qdrant now supports [granular access control using JSON Web Tokens (JWT)](/documentation/operations/security/#granular-access-control-with-jwt). JWT will let you easily limit a user's access to the specific data they are permitted to view. Specifically, JWT-based authentication leverages tokens with restricted access to designated data segments, laying the foundation for implementing role-based access control (RBAC) on top of it. **You will be able to define permissions for users and restrict access to sensitive endpoints.** +Qdrant now supports [granular access control using JSON Web Tokens (JWT)](/documentation/security/#granular-access-control-with-jwt). JWT will let you easily limit a user's access to the specific data they are permitted to view. Specifically, JWT-based authentication leverages tokens with restricted access to designated data segments, laying the foundation for implementing role-based access control (RBAC) on top of it. **You will be able to define permissions for users and restrict access to sensitive endpoints.** **Dashboard users:** For your convenience, we have added a JWT generation tool the Qdrant Web UI under the 🔑 tab. If you're using the default url, you will find it at `http://localhost:6333/dashboard#/jwt`. @@ -36,11 +36,11 @@ Qdrant now supports [granular access control using JSON Web Tokens (JWT)](/docum We highly recommend this feature to enterprises using [Qdrant Hybrid Cloud](/hybrid-cloud/), as it is tailored to those who need additional control over company data and user access. RBAC empowers administrators to define roles and assign specific privileges to users based on their roles within the organization. In combination with [Hybrid Cloud's data sovereign architecture](/documentation/hybrid-cloud/), this feature reinforces internal security and efficient collaboration by granting access only to relevant resources. -> **Documentation:** [Read the access level breakdown](/documentation/operations/security/#table-of-access) to see which actions are allowed or denied. +> **Documentation:** [Read the access level breakdown](/documentation/security/#table-of-access) to see which actions are allowed or denied. ## Faster shard transfers on node recovery -We now offer a streamlined approach to [data synchronization between shards](/documentation/operations/distributed_deployment/#shard-transfer-method) during node upgrades or recovery processes. Traditional methods used to transfer the entire dataset, but our new `wal_delta` method focuses solely on transmitting the difference between two existing shards. By leveraging the Write-Ahead Log (WAL) of both shards, this method selectively transmits missed operations to the target shard, ensuring data consistency. +We now offer a streamlined approach to [data synchronization between shards](/documentation/distributed_deployment/#shard-transfer-method) during node upgrades or recovery processes. Traditional methods used to transfer the entire dataset, but our new `wal_delta` method focuses solely on transmitting the difference between two existing shards. By leveraging the Write-Ahead Log (WAL) of both shards, this method selectively transmits missed operations to the target shard, ensuring data consistency. In some cases, where transfers can take hours, this update **reduces transfers down to a few minutes.** @@ -48,7 +48,7 @@ The advantages of this approach are twofold: 1. **It is faster** since only the differential data is transmitted, avoiding the transfer of redundant information. 2. It upholds robust **ordering guarantees**, crucial for applications reliant on strict sequencing. -For more details on how this works, check out the [shard transfer documentation](/documentation/operations/distributed_deployment/#shard-transfer-method). +For more details on how this works, check out the [shard transfer documentation](/documentation/distributed_deployment/#shard-transfer-method). > **Note:** There are limitations to consider. First, this method only works with existing shards. Second, while the WALs typically retain recent operations, their capacity is finite, potentially impeding the transfer process if exceeded. Nevertheless, for scenarios like rapid node restarts or upgrades, where the WAL content remains manageable, WAL delta transfer is an efficient solution. diff --git a/qdrant-landing/content/blog/qdrant-cpu-intel-benchmark.md b/qdrant-landing/content/blog/qdrant-cpu-intel-benchmark.md index ba60a4dae..0bfb46456 100644 --- a/qdrant-landing/content/blog/qdrant-cpu-intel-benchmark.md +++ b/qdrant-landing/content/blog/qdrant-cpu-intel-benchmark.md @@ -69,4 +69,4 @@ As large companies continue to integrate sophisticated AI and machine learning t Qdrant is open source and offers a complete SaaS solution, hosted on AWS, GCP, and Azure. -Getting started is easy, either spin up a [container image](https://hub.docker.com/r/qdrant/qdrant) or start a [free Cloud instance](https://cloud.qdrant.io/login). The documentation covers [adding the data](/documentation/tutorials-develop/bulk-upload/) to your Qdrant instance as well as [creating your indices](/documentation/operations/optimize/). We would love to hear about what you are building and please connect with our engineering team on [Github](https://github.com/qdrant/qdrant), [Discord](https://discord.com/invite/tdtYvXjC4h), or [LinkedIn](https://www.linkedin.com/company/qdrant). \ No newline at end of file +Getting started is easy, either spin up a [container image](https://hub.docker.com/r/qdrant/qdrant) or start a [free Cloud instance](https://cloud.qdrant.io/login). The documentation covers [adding the data](/documentation/tutorials-develop/bulk-upload/) to your Qdrant instance as well as [creating your indices](/documentation/ops-optimization/optimize/). We would love to hear about what you are building and please connect with our engineering team on [Github](https://github.com/qdrant/qdrant), [Discord](https://discord.com/invite/tdtYvXjC4h), or [LinkedIn](https://www.linkedin.com/company/qdrant). \ No newline at end of file diff --git a/qdrant-landing/content/blog/what-is-vector-similarity.md b/qdrant-landing/content/blog/what-is-vector-similarity.md index fd5789780..4f52fa48a 100644 --- a/qdrant-landing/content/blog/what-is-vector-similarity.md +++ b/qdrant-landing/content/blog/what-is-vector-similarity.md @@ -145,7 +145,7 @@ The vector index in Qdrant employs the Hierarchical Navigable Small World (HNSW) ### Scalability -For massive datasets and demanding workloads, Qdrant supports [distributed deployment](/documentation/operations/distributed_deployment/) from v0.8.0. In this mode, you can set up a Qdrant cluster and distribute data across multiple nodes, enabling you to maintain high performance and availability even under increased workloads. Clusters support sharding and replication, and harness the Raft consensus algorithm to manage node coordination. +For massive datasets and demanding workloads, Qdrant supports [distributed deployment](/documentation/distributed_deployment/) from v0.8.0. In this mode, you can set up a Qdrant cluster and distribute data across multiple nodes, enabling you to maintain high performance and availability even under increased workloads. Clusters support sharding and replication, and harness the Raft consensus algorithm to manage node coordination. Qdrant also supports vector [quantization](/documentation/manage-data/quantization/) to reduce memory footprint and speed up vector similarity searches, making it very effective for large-scale applications where efficient resource management is critical. @@ -153,7 +153,7 @@ There are three quantization strategies you can choose from - scalar quantizatio ### Security -Qdrant offers several [security features](/documentation/operations/security/) to help protect data and access to the vector store: +Qdrant offers several [security features](/documentation/security/) to help protect data and access to the vector store: - API Key Authentication: This helps secure API access to Qdrant Cloud with static or read-only API keys. - JWT-Based Access Control: You can also enable more granular access control through JSON Web Tokens (JWT), and opt for restricted access to specific parts of the stored data while building Role-Based Access Control (RBAC). diff --git a/qdrant-landing/content/course/essentials/day-0/qdrant-cloud.md b/qdrant-landing/content/course/essentials/day-0/qdrant-cloud.md index f8cea980b..e0feeefea 100644 --- a/qdrant-landing/content/course/essentials/day-0/qdrant-cloud.md +++ b/qdrant-landing/content/course/essentials/day-0/qdrant-cloud.md @@ -85,7 +85,7 @@ you’ll get a detailed view with these tabs: * **Search Quality Tab**: Evaluate and benchmark retrieval precision against ground truth. Tune parameters and measure the impact on accuracy. -* **Snapshots Tab**: Manage backups for this collection. Create a [snapshot](/documentation/operations/snapshots/), restore it later, or migrate it to another cluster. +* **Snapshots Tab**: Manage backups for this collection. Create a [snapshot](/documentation/snapshots/), restore it later, or migrate it to another cluster. * **Visualize Tab**: Explore your vector space with an interactive 2D projection. See clusters, spot outliers, and build intuition about your embeddings. diff --git a/qdrant-landing/content/course/essentials/day-2/collection-tuning-demo.md b/qdrant-landing/content/course/essentials/day-2/collection-tuning-demo.md index 314fea953..d85a78419 100644 --- a/qdrant-landing/content/course/essentials/day-2/collection-tuning-demo.md +++ b/qdrant-landing/content/course/essentials/day-2/collection-tuning-demo.md @@ -526,6 +526,6 @@ print("=" * 60) - [Qdrant Documentation](/documentation/) - Complete technical reference - [HNSW Paper](https://arxiv.org/abs/1603.09320) - Original algorithm research - [Qdrant Cloud](https://cloud.qdrant.io/) - Managed vector search service -- [Performance Tuning Guide](/documentation/operations/optimize/) - Advanced optimization techniques +- [Performance Tuning Guide](/documentation/ops-optimization/optimize/) - Advanced optimization techniques **Ready for the pitstop project?** Now it's your turn to optimize performance with your own dataset and use case. You'll apply these same techniques to your domain-specific data and measure the real-world impact of different HNSW parameters and indexing strategies. \ No newline at end of file diff --git a/qdrant-landing/content/course/essentials/day-2/what-is-hnsw.md b/qdrant-landing/content/course/essentials/day-2/what-is-hnsw.md index 578879404..064b4dec6 100644 --- a/qdrant-landing/content/course/essentials/day-2/what-is-hnsw.md +++ b/qdrant-landing/content/course/essentials/day-2/what-is-hnsw.md @@ -119,7 +119,7 @@ accurate_search = SearchParams(hnsw_ef=256) # Higher recall, slower ### Memory & Indexing Behavior -Some vectors can remain unindexed depending on [optimizer](/documentation/operations/optimizer/) settings e.g. when the unindexed part stays below the `indexing_threshold` (kB). +Some vectors can remain unindexed depending on [optimizer](/documentation/ops-optimization/optimizer/) settings e.g. when the unindexed part stays below the `indexing_threshold` (kB). Small collections or low-dimensional vectors may not trigger HNSW indexing at all. In such cases, full-scan search (brute force) is used instead until indexing becomes beneficial diff --git a/qdrant-landing/content/course/multi-vector-search/module-0/qdrant-setup.md b/qdrant-landing/content/course/multi-vector-search/module-0/qdrant-setup.md index f21ddda67..7c6e8166e 100644 --- a/qdrant-landing/content/course/multi-vector-search/module-0/qdrant-setup.md +++ b/qdrant-landing/content/course/multi-vector-search/module-0/qdrant-setup.md @@ -80,7 +80,7 @@ Once running, you can access the Web UI at `http://localhost:6333/dashboard` to ### Alternative Installation Methods -For production deployments or other installation methods, see the [Qdrant Installation Guide](/documentation/operations/installation/). +For production deployments or other installation methods, see the [Qdrant Installation Guide](/documentation/installation/). ## Verifying Your Setup diff --git a/qdrant-landing/content/documentation/_index.md b/qdrant-landing/content/documentation/_index.md index cdf38cd15..2515ad7e9 100644 --- a/qdrant-landing/content/documentation/_index.md +++ b/qdrant-landing/content/documentation/_index.md @@ -16,56 +16,73 @@ content: url: /documentation/quickstart/ contained: true - partial: documentation/banners/banner-d - developingTitle: Ready to start developing? - developingDescription: Qdrant is open-source and can be self-hosted. However, the quickest way to get started is with our free tier on Qdrant Cloud. It scales easily and provides a UI where you can interact with data. + developingTitle: Introducing Qdrant Edge + developingDescription: Qdrant Edge is a lightweight, embedded vector search engine for in-process retrieval — no background services, minimal memory footprint, and no network required. Built for robots, kiosks, mobile devices, and any environment requiring offline-capable AI search. developingBlock: - title: Create your first Qdrant Cloud cluster today + title: Run vector search anywhere, even offline button: text: Get Started - url: https://qdrant.to/cloud + url: /documentation/edge/edge-quickstart/ image: src: /img/rocket.svg alt: Rocket - partial: documentation/sections/cards-section - title: Optimize Qdrant's performance - description: Boost search speed, reduce latency, and improve the accuracy and memory usage of your Qdrant deployment. - button: - text: Learn More - url: /documentation/operations/optimize/ + title: Qdrant User Manual + description: Learn how to manage your data, run powerful searches, and leverage inference to build AI-native applications. cardsPartial: documentation/cards/docs-cards cards: - id: 1 - tag: Documents icon: - src: /icons/outline/documentation-blue.svg - alt: Documents - title: Distributed Deployment - description: Scale Qdrant beyond a single node and optimize for high availability, fault tolerance, and billion-scale performance. + src: /icons/outline/vectors-blue.svg + alt: Vectors + title: Manage Data + description: Create collections, manage vectors, payloads, and storage. Learn about indexing, quantization, and multitenancy. link: - url: /documentation/operations/distributed_deployment/ + url: /documentation/manage-data/ text: Read More - id: 2 - tag: Documents icon: - src: /icons/outline/documentation-blue.svg - alt: Documents - title: Multitenancy - description: Build vector search apps that serve millions of users. Learn about data isolation, security, and performance tuning. + src: /icons/outline/search-blue.svg + alt: Search + title: Search + description: Learn about similarity search, filtering, hybrid queries, and advanced retrieval techniques. link: - url: /documentation/manage-data/multitenancy/ + url: /documentation/search/ text: Read More - id: 3 - tag: Blog - tagColor: violet icon: - src: /icons/outline/blog-purple.svg - alt: Blog - title: Vector Quantization - description: Learn about cutting-edge techniques for vector quantization and how they can be used to improve search performance. + src: /icons/outline/integration-blue.svg + alt: Inference + title: Inference + description: Configure dense, sparse, and multi-vector embeddings. Use cloud-hosted embedding models directly with Qdrant. link: - url: /articles/what-is-vector-quantization/ + url: /documentation/inference/ text: Read More -partition: qdrant + - partial: documentation/sections/cards-section + title: Support + description: Get help from the Qdrant community or contact our support team. + cardsPartial: documentation/cards/docs-cards + cardsPerRow: 2 + cards: + - id: 1 + icon: + src: /icons/outline/discord-purple.svg + alt: Discord icon + title: Community Support + description: Join 6,000+ active members to learn, collaborate, and participate in Qdrant's latest activities. + link: + text: Join our Discord + url: https://qdrant.to/discord + - id: 2 + icon: + src: /icons/outline/support-blue.svg + alt: Support icon + title: Qdrant Cloud Support + description: Paying customers have access to our Support team. Links to the support portal are available in the Qdrant Cloud Console. + link: + text: Join Qdrant + url: https://qdrant.to/cloud +partition: develop --- THIS CONTENT IS GOING TO BE IGNORED FOR NOW @@ -89,7 +106,7 @@ Qdrant is an AI-native vector search and a semantic search engine. You can use i |||| |:-|:-|:-| |[Filterable HNSW](/documentation/search/filtering/)
Single-stage payload filtering | [Recommendations & Context Search](/documentation/search/explore/#explore-the-data)
Exploratory advanced search| [Pure-Vector Hybrid Search](/documentation/search/hybrid-queries/)
Full text and semantic search in one| -|[Multitenancy](/documentation/manage-data/multitenancy/)
Payload-based partitioning|[Custom Sharding](/documentation/operations/distributed_deployment/#sharding)
For data isolation and distribution|[Role Based Access Control](/documentation/operations/security/?q=jwt#granular-access-control-with-jwt)
Secure JWT-based access | +|[Multitenancy](/documentation/manage-data/multitenancy/)
Payload-based partitioning|[Custom Sharding](/documentation/distributed_deployment/#sharding)
For data isolation and distribution|[Role Based Access Control](/documentation/security/?q=jwt#granular-access-control-with-jwt)
Secure JWT-based access | |[Quantization](/documentation/manage-data/quantization/)
Compress data for drastic speedups|[Multivector Support](/documentation/manage-data/vectors/?q=multivect#multivectors)
For ColBERT late interaction |[Built-in IDF](/documentation/manage-data/indexing/?q=inverse+docu#idf-modifier)
Advanced similarity calculation| ## Developer guidebooks: diff --git a/qdrant-landing/content/documentation/operations/capacity-planning.md b/qdrant-landing/content/documentation/capacity-planning.md similarity index 97% rename from qdrant-landing/content/documentation/operations/capacity-planning.md rename to qdrant-landing/content/documentation/capacity-planning.md index c4ecb3c1f..ec85c255e 100644 --- a/qdrant-landing/content/documentation/operations/capacity-planning.md +++ b/qdrant-landing/content/documentation/capacity-planning.md @@ -1,9 +1,12 @@ --- title: Capacity Planning -weight: 5 +partition: deploy +weight: 238 aliases: - capacity - /documentation/cloud/capacity-sizing + - /documentation/capacity-planning + - /documentation/operations/capacity-planning --- # Capacity Planning diff --git a/qdrant-landing/content/documentation/cloud-account-setup.md b/qdrant-landing/content/documentation/cloud-account-setup.md index 4a541d0fa..70ef2af54 100644 --- a/qdrant-landing/content/documentation/cloud-account-setup.md +++ b/qdrant-landing/content/documentation/cloud-account-setup.md @@ -1,7 +1,7 @@ --- title: Account Setup -weight: 13 -partition: cloud +weight: 210 +partition: deploy aliases: - /documentation/cloud/qdrant-cloud-setup/ --- diff --git a/qdrant-landing/content/documentation/cloud-api.md b/qdrant-landing/content/documentation/cloud-api.md index 293e42d2f..cc5cc8d88 100644 --- a/qdrant-landing/content/documentation/cloud-api.md +++ b/qdrant-landing/content/documentation/cloud-api.md @@ -1,7 +1,7 @@ --- title: Qdrant Cloud API -weight: 27 -partition: cloud +weight: 245 +partition: deploy aliases: - /documentation/qdrant-cloud-api/ --- diff --git a/qdrant-landing/content/documentation/cloud-cli.md b/qdrant-landing/content/documentation/cloud-cli.md index 991c85cc8..3f16bdb52 100644 --- a/qdrant-landing/content/documentation/cloud-cli.md +++ b/qdrant-landing/content/documentation/cloud-cli.md @@ -1,7 +1,7 @@ --- title: Qdrant Cloud CLI -weight: 28 -partition: cloud +weight: 250 +partition: deploy --- # Qdrant Cloud CLI diff --git a/qdrant-landing/content/documentation/cloud-getting-started.md b/qdrant-landing/content/documentation/cloud-getting-started.md index 47040499b..f3d963abe 100644 --- a/qdrant-landing/content/documentation/cloud-getting-started.md +++ b/qdrant-landing/content/documentation/cloud-getting-started.md @@ -1,7 +1,7 @@ --- title: Getting Started -weight: 12 -partition: cloud +weight: 205 +partition: deploy aliases: - /documentation/cloud/getting-started/ --- @@ -20,7 +20,7 @@ Premium Plan subscribers can enable single sign-on (SSO) for their organizations ## Cluster Sizing -Before deploying any cluster, consider the resources needed for your specific workload. Our [Capacity Planning guide](/documentation/operations/capacity-planning/) describes how to assess the required CPU, memory, and storage. Additionally, the [Pricing Calculator](https://cloud.qdrant.io/calculator) helps you estimate associated costs based on your projected usage. +Before deploying any cluster, consider the resources needed for your specific workload. Our [Capacity Planning guide](/documentation/capacity-planning/) describes how to assess the required CPU, memory, and storage. Additionally, the [Pricing Calculator](https://cloud.qdrant.io/calculator) helps you estimate associated costs based on your projected usage. ## Creating and Managing Clusters @@ -28,7 +28,7 @@ After setting up your account, you can create a Qdrant Cluster by following the ## Preparing for Production -For a production-ready environment, consider deploying a multi-node Qdrant cluster (at least three nodes) with replication enabled. More details are available in the [Distributed Deployment](/documentation/operations/distributed_deployment/) guide. For more information on how to create a production-ready cluster, see our [Vector Search in Production](/articles/vector-search-production/) article. +For a production-ready environment, consider deploying a multi-node Qdrant cluster (at least three nodes) with replication enabled. More details are available in the [Distributed Deployment](/documentation/distributed_deployment/) guide. For more information on how to create a production-ready cluster, see our [Vector Search in Production](/articles/vector-search-production/) article. If you are looking to optimize costs, you can reduce memory usage through [Quantization](/documentation/manage-data/quantization/) or by [offloading vectors to disk](/documentation/manage-data/storage/#configuring-memmap-storage). diff --git a/qdrant-landing/content/documentation/cloud-premium.md b/qdrant-landing/content/documentation/cloud-premium.md index b68005c48..01d63bd4d 100644 --- a/qdrant-landing/content/documentation/cloud-premium.md +++ b/qdrant-landing/content/documentation/cloud-premium.md @@ -1,7 +1,7 @@ --- title: Premium Tier -weight: 19 -partition: cloud +weight: 260 +partition: deploy aliases: - /documentation/cloud/premium/ --- diff --git a/qdrant-landing/content/documentation/cloud-pricing-payments.md b/qdrant-landing/content/documentation/cloud-pricing-payments.md index 0c71f63a4..e8bff9db0 100644 --- a/qdrant-landing/content/documentation/cloud-pricing-payments.md +++ b/qdrant-landing/content/documentation/cloud-pricing-payments.md @@ -1,7 +1,7 @@ --- title: Billing & Payments -weight: 18 -partition: cloud +weight: 255 +partition: deploy aliases: - aws-marketplace - gcp-marketplace diff --git a/qdrant-landing/content/documentation/cloud-quickstart.md b/qdrant-landing/content/documentation/cloud-quickstart.md index 231135e3d..d6205dc98 100644 --- a/qdrant-landing/content/documentation/cloud-quickstart.md +++ b/qdrant-landing/content/documentation/cloud-quickstart.md @@ -1,7 +1,7 @@ --- title: Cloud Quickstart -weight: 4 -partition: cloud +weight: 115 +partition: develop aliases: - ../cloud-quick-start - cloud-quick-start @@ -22,7 +22,7 @@ Learn how to set up Qdrant Cloud and perform your first semantic search in just 2. Under **Create a Free Cluster**, enter a cluster name and select your preferred cloud provider and region. Click **Create Free Cluster**. 3. Copy your **API key** when prompted - you'll need it to connect. Store it somewhere safe as it won't be displayed again. -For detailed cluster setup instructions, see the [Cloud documentation](/documentation/cloud-intro/). +For detailed cluster setup instructions, see the [Cloud documentation](/documentation/deploy-intro/). ## 2. Install the Qdrant Client diff --git a/qdrant-landing/content/documentation/cloud-rbac/_index.md b/qdrant-landing/content/documentation/cloud-rbac/_index.md index e6da3b3a3..347687aea 100644 --- a/qdrant-landing/content/documentation/cloud-rbac/_index.md +++ b/qdrant-landing/content/documentation/cloud-rbac/_index.md @@ -1,7 +1,7 @@ --- title: Cloud RBAC -weight: 14 -partition: cloud +weight: 215 +partition: deploy --- # Cloud RBAC diff --git a/qdrant-landing/content/documentation/cloud-rbac/permission-reference.md b/qdrant-landing/content/documentation/cloud-rbac/permission-reference.md index 24009c82c..a973aa021 100644 --- a/qdrant-landing/content/documentation/cloud-rbac/permission-reference.md +++ b/qdrant-landing/content/documentation/cloud-rbac/permission-reference.md @@ -1,6 +1,6 @@ --- title: Permission Reference -weight: 3 +weight: 15 --- # **Permission Reference** @@ -57,8 +57,8 @@ Permissions for API Keys, backups, clusters, and backup schedules. ### **Cluster Data** | Permission | Description | |------------|------------| -| `read:cluster_data` | View cluster data, used for the Cluster UI button on Cluster Details. [Maps to global `read-only` JWT access for the cluster.](/documentation/operations/security/) | -| `write:cluster_data` | View and modify cluster data, used for the Cluster UI button on Cluster Details. [Maps to global `read-write` JWT access for the cluster.](/documentation/operations/security/) | +| `read:cluster_data` | View cluster data, used for the Cluster UI button on Cluster Details. [Maps to global `read-only` JWT access for the cluster.](/documentation/security/) | +| `write:cluster_data` | View and modify cluster data, used for the Cluster UI button on Cluster Details. [Maps to global `read-write` JWT access for the cluster.](/documentation/security/) | ### **Backup Schedules** | Permission | Description | diff --git a/qdrant-landing/content/documentation/cloud-rbac/role-management.md b/qdrant-landing/content/documentation/cloud-rbac/role-management.md index ba6c8bdbe..1abcd2564 100644 --- a/qdrant-landing/content/documentation/cloud-rbac/role-management.md +++ b/qdrant-landing/content/documentation/cloud-rbac/role-management.md @@ -1,6 +1,6 @@ --- title: Role Management -weight: 1 +weight: 5 --- # Role Management diff --git a/qdrant-landing/content/documentation/cloud-rbac/user-management.md b/qdrant-landing/content/documentation/cloud-rbac/user-management.md index 0b77282fe..a84020f1f 100644 --- a/qdrant-landing/content/documentation/cloud-rbac/user-management.md +++ b/qdrant-landing/content/documentation/cloud-rbac/user-management.md @@ -1,6 +1,6 @@ --- title: User Management -weight: 2 +weight: 10 --- # User Management diff --git a/qdrant-landing/content/documentation/cloud-security.md b/qdrant-landing/content/documentation/cloud-security.md index 81002ab78..8bd52a427 100644 --- a/qdrant-landing/content/documentation/cloud-security.md +++ b/qdrant-landing/content/documentation/cloud-security.md @@ -1,7 +1,7 @@ --- -title: Security -weight: 36 -partition: cloud +title: Cloud Security +weight: 240 +partition: deploy aliases: - /documentation/cloud/security/ --- diff --git a/qdrant-landing/content/documentation/cloud-tab.md b/qdrant-landing/content/documentation/cloud-tab.md index 869a640dc..c4223f011 100644 --- a/qdrant-landing/content/documentation/cloud-tab.md +++ b/qdrant-landing/content/documentation/cloud-tab.md @@ -4,8 +4,8 @@ slug: cloud-intro breadcrumb: false content: - partial: documentation/banners/banner-b - title: Welcome to Qdrant Cloud - description: Dev-portal Cloud + title: Deploy & Operate Qdrant + description: Deploy & Operate Qdrant image: src: /img/dev-portal-cloud/dev-portal-cloud-hero.png alt: Qdrant cloud dashboard @@ -13,7 +13,39 @@ content: text: Get Started url: https://qdrant.to/cloud - partial: documentation/sections/cards-section - title: Managed Services + title: Operations + description: Install, configure, optimize, and monitor your Qdrant deployment across any environment. + cardsPartial: documentation/cards/docs-cards + cards: + - id: 1 + icon: + src: /icons/outline/server-rack-blue.svg + alt: Installation + title: Installation + description: Deploy Qdrant on any infrastructure. Get requirements, configuration options, and GPU setup guides. + link: + url: /documentation/installation/ + text: Read More + - id: 2 + icon: + src: /icons/outline/switches-blue.svg + alt: Configuration + title: Configuration + description: Tune storage, network, performance, and runtime settings for your Qdrant instance. + link: + url: /documentation/ops-configuration/configuration/ + text: Read More + - id: 3 + icon: + src: /icons/outline/chart-bar-blue.svg + alt: Monitoring + title: Monitoring & Telemetry + description: Monitor cluster health, collect metrics with Prometheus and Grafana, and configure telemetry. + link: + url: /documentation/ops-monitoring/monitoring/ + text: Read More + - partial: documentation/sections/cards-section + title: Cloud description: Deploy and manage high-performance vector search clusters across cloud environments. Easily scale with fully managed cloud solutions, integrate seamlessly across hybrid setups, or maintain complete control with private cloud deployments in Kubernetes. cardsPartial: documentation/cards/docs-cards cards: @@ -45,8 +77,8 @@ content: url: /documentation/private-cloud/ text: Read More - partial: documentation/sections/cards-section - title: Customer Support - description: Stream, index, and migrate data to Qdrant with these essential tools and strategies. + title: Support + description: Get help from the Qdrant community or contact our support team. cardsPartial: documentation/cards/docs-cards cardsPerRow: 2 cards: @@ -68,6 +100,6 @@ content: link: text: Join Qdrant url: https://qdrant.to/cloud -partition: cloud +partition: deploy hideInSidebar: true --- diff --git a/qdrant-landing/content/documentation/cloud-tools/_index.md b/qdrant-landing/content/documentation/cloud-tools/_index.md index 3921f9955..ab9205831 100644 --- a/qdrant-landing/content/documentation/cloud-tools/_index.md +++ b/qdrant-landing/content/documentation/cloud-tools/_index.md @@ -1,7 +1,7 @@ --- title: Infrastructure Tools -weight: 28 -partition: cloud +weight: 235 +partition: deploy --- ## Cloud Tools diff --git a/qdrant-landing/content/documentation/cloud-tools/pulumi.md b/qdrant-landing/content/documentation/cloud-tools/pulumi.md index 9756329a8..c71142759 100644 --- a/qdrant-landing/content/documentation/cloud-tools/pulumi.md +++ b/qdrant-landing/content/documentation/cloud-tools/pulumi.md @@ -1,5 +1,6 @@ --- title: Pulumi +weight: 5 aliases: - /documentation/infrastructure/pulumi/ --- diff --git a/qdrant-landing/content/documentation/cloud-tools/terraform.md b/qdrant-landing/content/documentation/cloud-tools/terraform.md index 7ddcd3fff..4c4b43abf 100644 --- a/qdrant-landing/content/documentation/cloud-tools/terraform.md +++ b/qdrant-landing/content/documentation/cloud-tools/terraform.md @@ -1,5 +1,6 @@ --- title: Terraform +weight: 10 aliases: - /documentation/infrastructure/terraform/ --- diff --git a/qdrant-landing/content/documentation/cloud/_index.md b/qdrant-landing/content/documentation/cloud/_index.md index 59037c961..5fba274ee 100644 --- a/qdrant-landing/content/documentation/cloud/_index.md +++ b/qdrant-landing/content/documentation/cloud/_index.md @@ -1,9 +1,9 @@ --- title: Managed Cloud -weight: 15 +weight: 220 aliases: - /documentation/overview/qdrant-alternatives/documentation/cloud/ -partition: cloud +partition: deploy --- # About Qdrant Managed Cloud diff --git a/qdrant-landing/content/documentation/cloud/authentication.md b/qdrant-landing/content/documentation/cloud/authentication.md index fe8577f22..9062ed36b 100644 --- a/qdrant-landing/content/documentation/cloud/authentication.md +++ b/qdrant-landing/content/documentation/cloud/authentication.md @@ -1,13 +1,13 @@ --- title: Authentication -weight: 30 +weight: 10 --- # Database Authentication in Qdrant Managed Cloud This page describes what Database API keys are and shows you how to use the Qdrant Cloud Console to create a Database API key for a cluster. You will learn how to connect to your cluster using the new API key. -Database API keys can be configured with granular access control. Database API keys with granular access control can be recognized by starting with `eyJhb`. Please refer to the [Table of access](/documentation/operations/security/#table-of-access) to understand what permissions you can configure. +Database API keys can be configured with granular access control. Database API keys with granular access control can be recognized by starting with `eyJhb`. Please refer to the [Table of access](/documentation/security/#table-of-access) to understand what permissions you can configure. Database API keys with granular access control are available for clusters using version **v1.11.0** and above. diff --git a/qdrant-landing/content/documentation/cloud/backups.md b/qdrant-landing/content/documentation/cloud/backups.md index 5377d94a6..794e6b186 100644 --- a/qdrant-landing/content/documentation/cloud/backups.md +++ b/qdrant-landing/content/documentation/cloud/backups.md @@ -1,6 +1,6 @@ --- title: Backup Clusters -weight: 61 +weight: 40 --- # Backing up Qdrant Cloud Clusters @@ -71,7 +71,7 @@ Or you can restore the backup into a new cluster. Qdrant also offers a snapshot API which allows you to create a snapshot of a specific collection or your entire cluster. For more information, see our -[snapshot documentation](/documentation/operations/snapshots/). +[snapshot documentation](/documentation/snapshots/). Here is how you can take a snapshot and recover a collection: @@ -79,11 +79,11 @@ Here is how you can take a snapshot and recover a collection: - For a single node cluster, call the snapshot endpoint on the exposed URL. - For a multi node cluster call a snapshot on each node of the collection. Specifically, prepend `node-{num}-` to your cluster URL. - Then call the [snapshot endpoint](/documentation/operations/snapshots/#create-snapshot) on the individual hosts. Start with node 0. + Then call the [snapshot endpoint](/documentation/snapshots/#create-snapshot) on the individual hosts. Start with node 0. - In the response, you'll see the name of the snapshot. 2. Delete and recreate the collection. 3. Recover the snapshot: - - Call the [recover endpoint](/documentation/operations/snapshots/#recover-in-cluster-deployment). Set a location which points to the snapshot file (`file:///qdrant/snapshots/{collection_name}/{snapshot_file_name}`) for each host. + - Call the [recover endpoint](/documentation/snapshots/#recover-in-cluster-deployment). Set a location which points to the snapshot file (`file:///qdrant/snapshots/{collection_name}/{snapshot_file_name}`) for each host. ## Backup Considerations diff --git a/qdrant-landing/content/documentation/cloud/cluster-access.md b/qdrant-landing/content/documentation/cloud/cluster-access.md index d17778644..543980dcc 100644 --- a/qdrant-landing/content/documentation/cloud/cluster-access.md +++ b/qdrant-landing/content/documentation/cloud/cluster-access.md @@ -1,6 +1,6 @@ --- title: Cluster Access -weight: 35 +weight: 15 --- # Accessing Qdrant Cloud Clusters diff --git a/qdrant-landing/content/documentation/cloud/cluster-monitoring.md b/qdrant-landing/content/documentation/cloud/cluster-monitoring.md index de307092a..7243fb331 100644 --- a/qdrant-landing/content/documentation/cloud/cluster-monitoring.md +++ b/qdrant-landing/content/documentation/cloud/cluster-monitoring.md @@ -1,6 +1,6 @@ --- title: Monitor Clusters -weight: 55 +weight: 30 --- # Monitoring Qdrant Cloud Clusters @@ -120,7 +120,7 @@ The account owner will receive automatic alerts via email if your cluster has an **Where can I learn more about this alert?** - You can learn more about disk capacity [here](/documentation/operations/capacity-planning/#scaling-disk-space-in-qdrant-cloud). + You can learn more about disk capacity [here](/documentation/capacity-planning/#scaling-disk-space-in-qdrant-cloud). You can learn about vertical scaling [here](/documentation/cloud/cluster-scaling/#vertical-scaling). @@ -202,7 +202,7 @@ The account owner will receive automatic alerts via email if your cluster has an Learn about the SDKs [here](/documentation/interfaces/). - Learn more about JWT Keys and permissions [here](/documentation/operations/security/?q=jwt#granular-access-control-with-jwt). + Learn more about JWT Keys and permissions [here](/documentation/security/?q=jwt#granular-access-control-with-jwt). - title: A Node is CPU Throttled content: | @@ -230,9 +230,9 @@ The account owner will receive automatic alerts via email if your cluster has an **Where can I learn more about this alert?** - Learn how to optimize Qdrant for performance and configure indexing [here](/documentation/manage-data/indexing/) and [here](/documentation/operations/optimize/). + Learn how to optimize Qdrant for performance and configure indexing [here](/documentation/manage-data/indexing/) and [here](/documentation/ops-optimization/optimize/). - Learn about optimizers [here](/documentation/operations/optimizer/). + Learn about optimizers [here](/documentation/ops-optimization/optimizer/). Learn more about hybrid search [here](/documentation/search/hybrid-queries/). @@ -280,7 +280,7 @@ The account owner will receive automatic alerts via email if your cluster has an **Where can I learn more about this alert?** - Learn more about distributed deployments and resharding [here](/documentation/operations/distributed_deployment/#resharding). + Learn more about distributed deployments and resharding [here](/documentation/distributed_deployment/#resharding). Learn more about cloud rebalancing [here](/documentation/cloud/configure-cluster/#shard-rebalancing). @@ -294,11 +294,11 @@ To scrape metrics from a Qdrant cluster running in Qdrant Cloud, an [API key](/d ### Qdrant Node Metrics -Metrics in a Prometheus-compatible format are available at the `/metrics` endpoint of each Qdrant database node. When scraping, you should use the [node specific URLs](/documentation/cloud/cluster-access/#node-specific-endpoints) to ensure that you are scraping metrics from all nodes in each cluster. For more information, see [Qdrant monitoring](/documentation/operations/monitoring/). +Metrics in a Prometheus-compatible format are available at the `/metrics` endpoint of each Qdrant database node. When scraping, you should use the [node specific URLs](/documentation/cloud/cluster-access/#node-specific-endpoints) to ensure that you are scraping metrics from all nodes in each cluster. For more information, see [Qdrant monitoring](/documentation/ops-monitoring/monitoring/). You can also access the `/telemetry` [endpoint](https://api.qdrant.tech/api-reference/service/telemetry) of your database. This endpoint is available on the cluster endpoint and provides information about the current state of the database, including the number of vectors, shards, and other useful information. -For more information, see [Qdrant monitoring](/documentation/operations/monitoring/). +For more information, see [Qdrant monitoring](/documentation/ops-monitoring/monitoring/). ### Cluster System Metrics diff --git a/qdrant-landing/content/documentation/cloud/cluster-scaling.md b/qdrant-landing/content/documentation/cloud/cluster-scaling.md index efb2dc589..411b95542 100644 --- a/qdrant-landing/content/documentation/cloud/cluster-scaling.md +++ b/qdrant-landing/content/documentation/cloud/cluster-scaling.md @@ -1,6 +1,6 @@ --- title: Scale Clusters -weight: 50 +weight: 20 --- # Scaling Qdrant Cloud Clusters @@ -27,7 +27,7 @@ Vertical scaling can be an effective way to improve the performance of a cluster In such cases, horizontal scaling may be a more effective solution. -Horizontal scaling is the process of increasing the capacity of a cluster by adding more nodes and distributing the load and data among them. The horizontal scaling at Qdrant starts on the collection level. You have to choose the number of shards you want to distribute your collection around while creating the collection. Please refer to the [sharding documentation](/documentation/operations/distributed_deployment/#sharding) section for details. +Horizontal scaling is the process of increasing the capacity of a cluster by adding more nodes and distributing the load and data among them. The horizontal scaling at Qdrant starts on the collection level. You have to choose the number of shards you want to distribute your collection around while creating the collection. Please refer to the [sharding documentation](/documentation/distributed_deployment/#sharding) section for details. When scaling up horizontally, the cloud platform will automatically rebalance all available shards across nodes to ensure that the data is evenly distributed. See [Configuring Clusters](/documentation/cloud/configure-cluster/#shard-rebalancing) for more details. @@ -43,7 +43,7 @@ We will be glad to consult you on an optimal strategy for scaling. *Available as of Qdrant v1.13.0* - + When creating a collection, it has a specific number of shards. The ideal number of shards might change as your cluster evolves. diff --git a/qdrant-landing/content/documentation/cloud/cluster-upgrades.md b/qdrant-landing/content/documentation/cloud/cluster-upgrades.md index 22e13b913..b6a210565 100644 --- a/qdrant-landing/content/documentation/cloud/cluster-upgrades.md +++ b/qdrant-landing/content/documentation/cloud/cluster-upgrades.md @@ -1,6 +1,6 @@ --- title: Update Clusters -weight: 55 +weight: 35 --- # Updating Qdrant Cloud Clusters diff --git a/qdrant-landing/content/documentation/cloud/configure-cluster.md b/qdrant-landing/content/documentation/cloud/configure-cluster.md index 2022faf03..6b6c3411d 100644 --- a/qdrant-landing/content/documentation/cloud/configure-cluster.md +++ b/qdrant-landing/content/documentation/cloud/configure-cluster.md @@ -1,18 +1,18 @@ --- title: Configure Clusters -weight: 55 +weight: 25 --- # Configure Qdrant Cloud Clusters Qdrant Cloud offers several advanced configuration options to optimize clusters for your specific needs. You can access these options from the Cluster Details page in the Qdrant Cloud console. -The cloud platform does not expose all [configuration options](/documentation/operations/configuration/) available in Qdrant. We have selected the relevant options that are explained in detail below. +The cloud platform does not expose all [configuration options](/documentation/ops-configuration/configuration/) available in Qdrant. We have selected the relevant options that are explained in detail below. In addition, the cloud platform automatically configures the following settings for your cluster to ensure optimal performance and reliability: * The maximum number of collections in a cluster is set to 1000. Larger numbers of collections lead to performance degradation. For more information see [Multitenancy](/documentation/manage-data/multitenancy/). -* Strict mode is activated by default for new collections enforcing that all filters being used in retrieve and update queries are indexed. This improves performance and reliability. You can disable this individually for each collection. For more information see [Strict Mode](/documentation/operations/administration/#strict-mode). +* Strict mode is activated by default for new collections enforcing that all filters being used in retrieve and update queries are indexed. This improves performance and reliability. You can disable this individually for each collection. For more information see [Strict Mode](/documentation/ops-configuration/administration/#strict-mode). * The cluster mode is automatically enabled to allow distributed deployments and horizontal scaling. * The maximum amount of payload indexes per collection is set to 100. Larger numbers of payload indexes lead to performance degradation (starting with Qdrant v1.16.0). @@ -24,7 +24,7 @@ You can set default values for the configuration of new collections in your clus You can configure the default *Replication Factor*, the default *Write Consistency Factor*, and if vectors should be stored on disk only, instead of being cached in RAM. -Refer to [Qdrant Configuration](/documentation/operations/configuration/#configuration-options) for more details. +Refer to [Qdrant Configuration](/documentation/ops-configuration/configuration/#configuration-options) for more details. ## Advanced Optimizations diff --git a/qdrant-landing/content/documentation/cloud/create-cluster.md b/qdrant-landing/content/documentation/cloud/create-cluster.md index 88a539610..fc52e7b71 100644 --- a/qdrant-landing/content/documentation/cloud/create-cluster.md +++ b/qdrant-landing/content/documentation/cloud/create-cluster.md @@ -1,6 +1,6 @@ --- title: Create a Cluster -weight: 20 +weight: 5 --- # Creating a Qdrant Cloud Cluster @@ -20,7 +20,7 @@ A free tier cluster only includes 1 single node with the following resources: | Disk space | 4 GB | | Nodes | 1 | -This configuration supports serving about 1 M vectors of 768 dimensions. To calculate your needs, refer to our documentation on [Capacity Planning](/documentation/operations/capacity-planning/). +This configuration supports serving about 1 M vectors of 768 dimensions. To calculate your needs, refer to our documentation on [Capacity Planning](/documentation/capacity-planning/). The choice of cloud providers and regions is limited. @@ -77,7 +77,7 @@ This page shows you how to use the Qdrant Cloud Console to create a custom Qdran 1. Choose your data center region or Hybrid Cloud environment. 1. Configure RAM for each node. - > For more information, see our [Capacity Planning](/documentation/operations/capacity-planning/) guidance. + > For more information, see our [Capacity Planning](/documentation/capacity-planning/) guidance. 1. Choose the number of vCPUs and GPUs per node. If you add more RAM, the menu provides different options for vCPUs. For higher RAM configurations, you can also choose to add a GPU to optimize indexing performance (AWS only). 1. Select the number of nodes you want the cluster to be deployed on. @@ -116,7 +116,7 @@ We recommend the **Balanced** tier for disks >= 32 GiB, and the **Performance** **GPUs (AWS only)** -If you have a write-heavy workload, you can add a GPU to each node to optimize indexing performance. See [**GPUs for Indexing**](/documentation/operations/running-with-gpu/) for more information. All GPU settings will be configured automatically by the cloud platform. +If you have a write-heavy workload, you can add a GPU to each node to optimize indexing performance. See [**GPUs for Indexing**](/documentation/ops-configuration/running-with-gpu/) for more information. All GPU settings will be configured automatically by the cloud platform. **Backup and Disaster Recovery** @@ -124,7 +124,7 @@ You should create a backup schedule for your cluster. This ensures that you can **Collection Sharding** -To allow your cluster to easily scale horizontally, you should configure at least twice as many shards per collection than the number of nodes in your cluster. You can configure the number of shards when creating a collection. See [**Sharding**](/documentation/operations/distributed_deployment/#sharding) for more information. +To allow your cluster to easily scale horizontally, you should configure at least twice as many shards per collection than the number of nodes in your cluster. You can configure the number of shards when creating a collection. See [**Sharding**](/documentation/distributed_deployment/#sharding) for more information. If you did not configure enough shards in a collection, you can use the [**Resharding**](/documentation/cloud/cluster-scaling/#resharding) feature to change the number of shards in an existing collection. diff --git a/qdrant-landing/content/documentation/cloud/inference.md b/qdrant-landing/content/documentation/cloud/inference.md index 94cd90c78..8345b545d 100644 --- a/qdrant-landing/content/documentation/cloud/inference.md +++ b/qdrant-landing/content/documentation/cloud/inference.md @@ -1,6 +1,6 @@ --- title: Inference -weight: 81 +weight: 45 --- # Inference in Qdrant Managed Cloud diff --git a/qdrant-landing/content/documentation/operations/common-errors.md b/qdrant-landing/content/documentation/common-errors.md similarity index 95% rename from qdrant-landing/content/documentation/operations/common-errors.md rename to qdrant-landing/content/documentation/common-errors.md index 73fe37035..bfe1e7a19 100644 --- a/qdrant-landing/content/documentation/operations/common-errors.md +++ b/qdrant-landing/content/documentation/common-errors.md @@ -1,10 +1,13 @@ --- title: Troubleshooting -weight: 45 +partition: deploy +weight: 150 aliases: - ../tutorials/common-errors - /documentation/troubleshooting/ - /documentation/guides/common-errors/ + - /documentation/common-errors + - /documentation/operations/common-errors --- # Solving common errors @@ -35,7 +38,7 @@ Please note, the command should be executed before you run Qdrant server. ## Incompatible file system -Qdrant have a [set of requirements](/documentation/operations/installation/#storage) for persistent file storage. +Qdrant have a [set of requirements](/documentation/installation/#storage) for persistent file storage. The most important requirement is that file system **must** be [POSIX-compatible](https://www.quobyte.com/storage-explained/posix-filesystem/). diff --git a/qdrant-landing/content/documentation/data-management/airbyte.md b/qdrant-landing/content/documentation/data-management/airbyte.md index c5cf0fa55..02ac16431 100644 --- a/qdrant-landing/content/documentation/data-management/airbyte.md +++ b/qdrant-landing/content/documentation/data-management/airbyte.md @@ -26,7 +26,7 @@ Before you start, make sure you have the following: 1. Airbyte instance, either [Open Source](https://airbyte.com/solutions/airbyte-open-source), [Self-Managed](https://airbyte.com/solutions/airbyte-enterprise), or [Cloud](https://airbyte.com/solutions/airbyte-cloud). 2. Running instance of Qdrant. It has to be accessible by URL from the machine where Airbyte is running. - You can follow the [installation guide](/documentation/operations/installation/) to set up Qdrant. + You can follow the [installation guide](/documentation/installation/) to set up Qdrant. ## Setting up Qdrant as a destination diff --git a/qdrant-landing/content/documentation/data-management/airflow.md b/qdrant-landing/content/documentation/data-management/airflow.md index 45e196ce9..0bd6f4c7f 100644 --- a/qdrant-landing/content/documentation/data-management/airflow.md +++ b/qdrant-landing/content/documentation/data-management/airflow.md @@ -13,7 +13,7 @@ Qdrant is available as a [provider](https://airflow.apache.org/docs/apache-airfl Before configuring Airflow, you need: -1. A Qdrant instance to connect to. You can set one up in our [installation guide](/documentation/operations/installation/). +1. A Qdrant instance to connect to. You can set one up in our [installation guide](/documentation/installation/). 2. A running Airflow instance. You can use their [Quick Start Guide](https://airflow.apache.org/docs/apache-airflow/stable/start.html). diff --git a/qdrant-landing/content/documentation/datasets.md b/qdrant-landing/content/documentation/datasets.md index f80c71a5d..6f0e7e05d 100644 --- a/qdrant-landing/content/documentation/datasets.md +++ b/qdrant-landing/content/documentation/datasets.md @@ -22,7 +22,7 @@ on a dataset name to see its detailed description. | [Arxiv.org abstracts](#arxivorg-abstracts) | [InstructorXL](https://huggingface.co/hkunlp/instructor-xl) | 768 | 2.3M | 8.4 GB | [Download](https://snapshots.qdrant.io/arxiv_abstracts-3083016565637815127-2023-06-02-07-26-29.snapshot) | [Open](https://huggingface.co/datasets/Qdrant/arxiv-abstracts-instructorxl-embeddings) | | [Wolt food](#wolt-food) | [clip-ViT-B-32](https://huggingface.co/sentence-transformers/clip-ViT-B-32) | 512 | 1.7M | 7.9 GB | [Download](https://snapshots.qdrant.io/wolt-clip-ViT-B-32-2446808438011867-2023-12-14-15-55-26.snapshot) | [Open](https://huggingface.co/datasets/Qdrant/wolt-food-clip-ViT-B-32-embeddings) | -Once you download a snapshot, you need to [restore it](/documentation/operations/snapshots/#restore-snapshot) +Once you download a snapshot, you need to [restore it](/documentation/snapshots/#restore-snapshot) using the Qdrant CLI upon startup or through the API. ## Qdrant on Hugging Face diff --git a/qdrant-landing/content/documentation/deploy-tab.md b/qdrant-landing/content/documentation/deploy-tab.md new file mode 100644 index 000000000..5a8ea6ac1 --- /dev/null +++ b/qdrant-landing/content/documentation/deploy-tab.md @@ -0,0 +1,108 @@ +--- +title: Deploy Qdrant +slug: deploy-intro +breadcrumb: false +aliases: + - /documentation/deploy-intro + - /documentation/cloud-intro +content: + - partial: documentation/banners/banner-b + title: Deploy Qdrant + description: Deploy Qdrant + image: + src: /img/dev-portal-cloud/dev-portal-cloud-hero.png + alt: Qdrant cloud dashboard + startedButton: + text: Get Started + url: https://qdrant.to/cloud + - partial: documentation/sections/cards-section + title: Operations + description: Install, configure, optimize, and monitor your Qdrant deployment across any environment. + cardsPartial: documentation/cards/docs-cards + cards: + - id: 1 + icon: + src: /icons/outline/server-rack-blue.svg + alt: Installation + title: Installation + description: Deploy Qdrant on any infrastructure. Get requirements, configuration options, and GPU setup guides. + link: + url: /documentation/installation/ + text: Read More + - id: 2 + icon: + src: /icons/outline/switches-blue.svg + alt: Configuration + title: Configuration + description: Tune storage, network, performance, and runtime settings for your Qdrant instance. + link: + url: /documentation/ops-configuration/configuration/ + text: Read More + - id: 3 + icon: + src: /icons/outline/chart-bar-blue.svg + alt: Monitoring + title: Monitoring & Telemetry + description: Monitor cluster health, collect metrics with Prometheus and Grafana, and configure telemetry. + link: + url: /documentation/ops-monitoring/monitoring/ + text: Read More + - partial: documentation/sections/cards-section + title: Cloud + description: Deploy and manage high-performance vector search clusters across cloud environments. Easily scale with fully managed cloud solutions, integrate seamlessly across hybrid setups, or maintain complete control with private cloud deployments in Kubernetes. + cardsPartial: documentation/cards/docs-cards + cards: + - id: 1 + image: + src: /img/dev-portal-cloud/managed-cloud.png + alt: Managed Cloud + title: Managed Cloud + description: Qdrant Managed Cloud is our SaaS solution, providing managed Qdrant database clusters on the cloud. + link: + url: /documentation/cloud/ + text: Read More + - id: 2 + image: + src: /img/dev-portal-cloud/hybrid-cloud.png + alt: Hybrid Cloud + title: Hybrid Cloud + description: Deploy and manage your vector database across diverse environments, ensuring performance, security, and cost efficiency. + link: + url: /documentation/hybrid-cloud/ + text: Read More + - id: 3 + image: + src: /img/dev-portal-cloud/private-cloud.png + alt: Private Cloud + title: Private Cloud + description: Qdrant Private Cloud allows you to manage Qdrant database clusters in any Kubernetes cluster on any infrastructure. + link: + url: /documentation/private-cloud/ + text: Read More + - partial: documentation/sections/cards-section + title: Support + description: Get help from the Qdrant community or contact our support team. + cardsPartial: documentation/cards/docs-cards + cardsPerRow: 2 + cards: + - id: 1 + icon: + src: /icons/outline/discord-purple.svg + alt: Discord icon + title: Community Support + description: Join 6,000+ active members to learn, collaborate, and participate in Qdrant’s latest activities. + link: + text: Join our Discord + url: https://qdrant.to/discord + - id: 2 + icon: + src: /icons/outline/support-blue.svg + alt: Support icon + title: Qdrant Cloud Support + description: Paying customers have access to our Support team. Links to the support portal are available in the Qdrant Cloud Console. + link: + text: Join Qdrant + url: https://qdrant.to/cloud +partition: deploy +hideInSidebar: true +--- diff --git a/qdrant-landing/content/documentation/operations/distributed_deployment.md b/qdrant-landing/content/documentation/distributed_deployment.md similarity index 98% rename from qdrant-landing/content/documentation/operations/distributed_deployment.md rename to qdrant-landing/content/documentation/distributed_deployment.md index b788b991e..3d8de01c1 100644 --- a/qdrant-landing/content/documentation/operations/distributed_deployment.md +++ b/qdrant-landing/content/documentation/distributed_deployment.md @@ -1,9 +1,11 @@ --- title: Distributed Deployment -weight: 60 +partition: deploy +weight: 115 aliases: - - ../distributed_deployment + - /documentation/distributed_deployment - /guides/distributed_deployment + - /documentation/operations/distributed_deployment --- # Distributed deployment @@ -32,7 +34,7 @@ In summary, single-node clusters are best for non-production workloads, replicat ## Enabling distributed mode in self-hosted Qdrant -To enable distributed deployment - enable the cluster mode in the [configuration](/documentation/operations/configuration/) or using the ENV variable: `QDRANT__CLUSTER__ENABLED=true`. +To enable distributed deployment - enable the cluster mode in the [configuration](/documentation/ops-configuration/configuration/) or using the ENV variable: `QDRANT__CLUSTER__ENABLED=true`. ```yaml cluster: @@ -313,7 +315,7 @@ When you add or remove nodes from the cluster, rebalancing of existing shards ac *Available as of v1.13.0 in Cloud* -Resharding allows you to change the number of shards in your existing collections if you're hosting with our [Cloud](/documentation/cloud-intro/) offering. +Resharding allows you to change the number of shards in your existing collections if you're hosting with our [Cloud](/documentation/deploy-intro/) offering. Resharding can change the number of shards both up and down, without having to recreate the collection from scratch. @@ -423,7 +425,7 @@ fastest depends on the size and state of a shard. Available shard transfer methods are: - `stream_records`: _(default)_ transfer by streaming just its records to the target node in batches. -- `snapshot`: transfer including its index and quantized data by utilizing a [snapshot](/documentation/operations/snapshots/) automatically. +- `snapshot`: transfer including its index and quantized data by utilizing a [snapshot](/documentation/snapshots/) automatically. - `wal_delta`: _(auto recovery default)_ transfer by resolving [WAL] difference; the operations that were missed. Each has pros, cons and specific requirements, some of which are: @@ -476,7 +478,7 @@ are acceptable in your use case. If your cluster is unstable and out of resources, it's probably best to use the `stream_records` transfer method, because it is unlikely to fail. -The `snapshot` transfer method utilizes [snapshots](/documentation/operations/snapshots/) +The `snapshot` transfer method utilizes [snapshots](/documentation/snapshots/) to transfer a shard. A snapshot is created automatically. It is then transferred and restored on the target node. After this is done, the snapshot is removed from both nodes. While the snapshot/transfer/restore operation is happening, the @@ -516,7 +518,7 @@ This ensures the availability of the data in case of node failures, except if al ### Replication factor -When you create a collection, you can control how many shard replicas you'd like to store by changing the `replication_factor`. By default, `replication_factor` is set to "1", meaning no additional copy is maintained automatically. The default can be changed in the [Qdrant configuration](/documentation/operations/configuration/#configuration-options). You can change that by setting the `replication_factor` when you create a collection. +When you create a collection, you can control how many shard replicas you'd like to store by changing the `replication_factor`. By default, `replication_factor` is set to "1", meaning no additional copy is maintained automatically. The default can be changed in the [Qdrant configuration](/documentation/ops-configuration/configuration/#configuration-options). You can change that by setting the `replication_factor` when you create a collection. The `replication_factor` can be updated for an existing collection, but the effect of this depends on how you're running Qdrant. If you're hosting the open source version of Qdrant yourself, changing the replication factor after collection creation doesn't do anything. You can manually [create](#creating-new-shard-replicas) or drop shard replicas to achieve your desired replication factor. In Qdrant Cloud (including Hybrid Cloud, Private Cloud) your shards will automatically be replicated or dropped to match your configured replication factor. @@ -739,7 +741,7 @@ Snapshot recovery, used in single-node deployment, is different from cluster one Consensus manages all metadata about all collections and does not require snapshots to recover it. But you can use snapshots to recover missing shards of the collections. -Use the [Collection Snapshot Recovery API](/documentation/operations/snapshots/#recover-in-cluster-deployment) to do it. +Use the [Collection Snapshot Recovery API](/documentation/snapshots/#recover-in-cluster-deployment) to do it. The service will download the specified snapshot of the collection and recover shards with data from it. Once all shards of the collection are recovered, the collection will become operational again. diff --git a/qdrant-landing/content/documentation/dl-cloud-getting-started.md b/qdrant-landing/content/documentation/dl-cloud-getting-started.md index 981ea9203..dcd3705ba 100644 --- a/qdrant-landing/content/documentation/dl-cloud-getting-started.md +++ b/qdrant-landing/content/documentation/dl-cloud-getting-started.md @@ -3,9 +3,10 @@ title: "Getting Started" type: delimiter weight: 1 # Change this weight to change order of sections +hideInSidebar: true sitemapExclude: True _build: publishResources: false render: never -partition: cloud +partition: deploy --- diff --git a/qdrant-landing/content/documentation/dl-cloud-interfaces.md b/qdrant-landing/content/documentation/dl-cloud-interfaces.md index 1a72582fb..290de4353 100644 --- a/qdrant-landing/content/documentation/dl-cloud-interfaces.md +++ b/qdrant-landing/content/documentation/dl-cloud-interfaces.md @@ -3,9 +3,10 @@ title: "Interfaces & Tools" type: delimiter weight: 25 # Change this weight to change order of sections +hideInSidebar: true sitemapExclude: True _build: publishResources: false render: never -partition: cloud +partition: deploy --- \ No newline at end of file diff --git a/qdrant-landing/content/documentation/dl-cloud-support.md b/qdrant-landing/content/documentation/dl-cloud-support.md index df5b960c4..5310e1f8f 100644 --- a/qdrant-landing/content/documentation/dl-cloud-support.md +++ b/qdrant-landing/content/documentation/dl-cloud-support.md @@ -2,10 +2,10 @@ #Delimiter files are used to separate the list of documentation pages into sections. title: "Support" type: delimiter -weight: 30 # Change this weight to change order of sections +weight: 300 sitemapExclude: True _build: publishResources: false render: never -partition: cloud +partition: deploy --- \ No newline at end of file diff --git a/qdrant-landing/content/documentation/dl-getting-started.md b/qdrant-landing/content/documentation/dl-getting-started.md index 4ee826706..f299558c3 100644 --- a/qdrant-landing/content/documentation/dl-getting-started.md +++ b/qdrant-landing/content/documentation/dl-getting-started.md @@ -7,5 +7,5 @@ sitemapExclude: True _build: publishResources: false render: never -partition: qdrant +partition: develop --- diff --git a/qdrant-landing/content/documentation/dl-managed-services.md b/qdrant-landing/content/documentation/dl-managed-services.md index 61d13688e..1c5f92c46 100644 --- a/qdrant-landing/content/documentation/dl-managed-services.md +++ b/qdrant-landing/content/documentation/dl-managed-services.md @@ -1,11 +1,11 @@ --- #Delimiter files are used to separate the list of documentation pages into sections. -title: "Managed Services" +title: "Cloud" type: delimiter -weight: 11 # Change this weight to change order of sections +weight: 200 # Change this weight to change order of sections sitemapExclude: True _build: publishResources: false render: never -partition: cloud +partition: deploy --- \ No newline at end of file diff --git a/qdrant-landing/content/documentation/dl-support.md b/qdrant-landing/content/documentation/dl-support.md index 0be22d757..608a64f06 100644 --- a/qdrant-landing/content/documentation/dl-support.md +++ b/qdrant-landing/content/documentation/dl-support.md @@ -7,5 +7,5 @@ sitemapExclude: True _build: publishResources: false render: never -partition: qdrant +partition: develop --- \ No newline at end of file diff --git a/qdrant-landing/content/documentation/dl-tools.md b/qdrant-landing/content/documentation/dl-tools.md index a9bf11237..a79758d1c 100644 --- a/qdrant-landing/content/documentation/dl-tools.md +++ b/qdrant-landing/content/documentation/dl-tools.md @@ -7,5 +7,5 @@ sitemapExclude: True _build: publishResources: false render: never -partition: qdrant +partition: develop --- \ No newline at end of file diff --git a/qdrant-landing/content/documentation/dl-tutorials.md b/qdrant-landing/content/documentation/dl-tutorials.md index 97eb4d3a1..2191758d0 100644 --- a/qdrant-landing/content/documentation/dl-tutorials.md +++ b/qdrant-landing/content/documentation/dl-tutorials.md @@ -7,5 +7,5 @@ sitemapExclude: True _build: publishResources: false render: never -partition: qdrant +partition: develop --- \ No newline at end of file diff --git a/qdrant-landing/content/documentation/dl-user-manual.md b/qdrant-landing/content/documentation/dl-user-manual.md index e4286295f..4373b7902 100644 --- a/qdrant-landing/content/documentation/dl-user-manual.md +++ b/qdrant-landing/content/documentation/dl-user-manual.md @@ -7,5 +7,5 @@ sitemapExclude: True _build: publishResources: false render: never -partition: qdrant +partition: develop --- \ No newline at end of file diff --git a/qdrant-landing/content/documentation/edge/_index.md b/qdrant-landing/content/documentation/edge/_index.md index 89fb5a891..a329c1cd3 100644 --- a/qdrant-landing/content/documentation/edge/_index.md +++ b/qdrant-landing/content/documentation/edge/_index.md @@ -1,7 +1,7 @@ --- title: "Qdrant Edge" -weight: 225 -partition: qdrant +weight: 220 +partition: develop --- diff --git a/qdrant-landing/content/documentation/edge/edge-data-synchronization-patterns.md b/qdrant-landing/content/documentation/edge/edge-data-synchronization-patterns.md index 0bead20a8..b15542a0b 100644 --- a/qdrant-landing/content/documentation/edge/edge-data-synchronization-patterns.md +++ b/qdrant-landing/content/documentation/edge/edge-data-synchronization-patterns.md @@ -1,7 +1,7 @@ --- title: "Data Synchronization Patterns" weight: 20 -partition: qdrant +partition: develop --- # Data Synchronization Patterns diff --git a/qdrant-landing/content/documentation/edge/edge-fastembed-embeddings.md b/qdrant-landing/content/documentation/edge/edge-fastembed-embeddings.md index 159f92343..53ed2b1d8 100644 --- a/qdrant-landing/content/documentation/edge/edge-fastembed-embeddings.md +++ b/qdrant-landing/content/documentation/edge/edge-fastembed-embeddings.md @@ -1,7 +1,7 @@ --- title: "On-Device Embeddings" weight: 15 -partition: qdrant +partition: develop --- # On-Device Embeddings with Qdrant Edge and FastEmbed diff --git a/qdrant-landing/content/documentation/edge/edge-quickstart.md b/qdrant-landing/content/documentation/edge/edge-quickstart.md index 8cd6f5404..499e421a1 100644 --- a/qdrant-landing/content/documentation/edge/edge-quickstart.md +++ b/qdrant-landing/content/documentation/edge/edge-quickstart.md @@ -1,7 +1,7 @@ --- title: "Quickstart" weight: 10 -partition: qdrant +partition: develop --- # Qdrant Edge Quickstart diff --git a/qdrant-landing/content/documentation/edge/edge-synchronization-guide.md b/qdrant-landing/content/documentation/edge/edge-synchronization-guide.md index 0c3c54db7..0b734c35c 100644 --- a/qdrant-landing/content/documentation/edge/edge-synchronization-guide.md +++ b/qdrant-landing/content/documentation/edge/edge-synchronization-guide.md @@ -1,7 +1,7 @@ --- title: "Synchronize with a Server" weight: 30 -partition: qdrant +partition: develop --- # Synchronize Qdrant Edge with a Server diff --git a/qdrant-landing/content/documentation/faq/_index.md b/qdrant-landing/content/documentation/faq/_index.md index 6dbe23cea..47ad6ed45 100644 --- a/qdrant-landing/content/documentation/faq/_index.md +++ b/qdrant-landing/content/documentation/faq/_index.md @@ -1,7 +1,7 @@ --- title: FAQ -weight: 505 -partition: qdrant +weight: 510 +partition: develop # If the index.md file `is_empty`, the sidebar will display the first child link as the main entry is_empty: true build: diff --git a/qdrant-landing/content/documentation/faq/database-optimization.md b/qdrant-landing/content/documentation/faq/database-optimization.md index 7d20b49bd..a1396c90a 100644 --- a/qdrant-landing/content/documentation/faq/database-optimization.md +++ b/qdrant-landing/content/documentation/faq/database-optimization.md @@ -13,7 +13,7 @@ The primary source of memory usage is vector data. There are several ways to add - Configure on-disk vector storage The choice of the approach depends on your requirements. -Read more about [configuring the optimal](/documentation/operations/optimize/) use of Qdrant. +Read more about [configuring the optimal](/documentation/ops-optimization/optimize/) use of Qdrant. ### How do you choose the machine configuration? diff --git a/qdrant-landing/content/documentation/faq/qdrant-fundamentals.md b/qdrant-landing/content/documentation/faq/qdrant-fundamentals.md index 5d853b31f..39c5eaa87 100644 --- a/qdrant-landing/content/documentation/faq/qdrant-fundamentals.md +++ b/qdrant-landing/content/documentation/faq/qdrant-fundamentals.md @@ -18,7 +18,7 @@ In dense vectors, Qdrant supports up to 65,535 dimensions. ### What is the maximum size of vector metadata that can be stored? -There is no inherent limitation on metadata size, but it should be [optimized for performance and resource usage](/documentation/operations/optimize/). Users can set upper limits in the configuration. +There is no inherent limitation on metadata size, but it should be [optimized for performance and resource usage](/documentation/ops-optimization/optimize/). Users can set upper limits in the configuration. ### Can the same similarity search query yield different results on different machines? diff --git a/qdrant-landing/content/documentation/fastembed/_index.md b/qdrant-landing/content/documentation/fastembed/_index.md index a9f654004..7c22a9ab7 100644 --- a/qdrant-landing/content/documentation/fastembed/_index.md +++ b/qdrant-landing/content/documentation/fastembed/_index.md @@ -1,7 +1,7 @@ --- title: "FastEmbed" weight: 305 -partition: qdrant +partition: develop --- # What is FastEmbed? diff --git a/qdrant-landing/content/documentation/frameworks/cheshire-cat.md b/qdrant-landing/content/documentation/frameworks/cheshire-cat.md index 47b13f4c4..66e82d71d 100644 --- a/qdrant-landing/content/documentation/frameworks/cheshire-cat.md +++ b/qdrant-landing/content/documentation/frameworks/cheshire-cat.md @@ -27,7 +27,7 @@ Cheshire Cat takes great advantage of the following features of Qdrant: * [Collection Aliases](/documentation/manage-data/collections/#collection-aliases) to manage the change from one embedder to another. * [Quantization](/documentation/manage-data/quantization/) to obtain a good balance between speed, memory usage and quality of the results. -* [Snapshots](/documentation/operations/snapshots/) to not miss any information. +* [Snapshots](/documentation/snapshots/) to not miss any information. * [Community](https://discord.com/invite/tdtYvXjC4h) ![RAG Pipeline](/documentation/frameworks/cheshire-cat/stregatto.jpg) diff --git a/qdrant-landing/content/documentation/frameworks/langchain.md b/qdrant-landing/content/documentation/frameworks/langchain.md index af441b2dc..1daa27c41 100644 --- a/qdrant-landing/content/documentation/frameworks/langchain.md +++ b/qdrant-landing/content/documentation/frameworks/langchain.md @@ -81,7 +81,7 @@ qdrant = Qdrant.from_documents( ### On-premise server deployment -No matter if you choose to launch QdrantVectorStore locally with [a Docker container](/documentation/operations/installation/), or +No matter if you choose to launch QdrantVectorStore locally with [a Docker container](/documentation/installation/), or select a Kubernetes deployment with [the official Helm chart](https://github.com/qdrant/qdrant-helm), the way you're going to connect to such an instance will be identical. You'll need to provide a URL pointing to the service. diff --git a/qdrant-landing/content/documentation/headless/content/tutorials/operations.md b/qdrant-landing/content/documentation/headless/content/tutorials/operations.md index 43fefe0fb..849d21640 100644 --- a/qdrant-landing/content/documentation/headless/content/tutorials/operations.md +++ b/qdrant-landing/content/documentation/headless/content/tutorials/operations.md @@ -5,5 +5,5 @@ | [Embedding Model Migration](/documentation/tutorials-operations/embedding-model-migration/) | Use your new model with zero downtime. | None | 40m | Intermediate | | [Time-Based Sharding](/documentation/tutorials-operations/time-based-sharding/) | Efficiently manage time-series data with user-defined sharding. | None | 1h | Intermediate | | [Large-Scale Search](/documentation/tutorials-operations/large-scale-search/) | Cost-efficient search for LAION-400M datasets. | None | 48h | Advanced | -| [Qdrant Cloud Prometheus Monitoring](/documentation/tutorials-and-examples/managed-cloud-prometheus/) | Observability with Prometheus and Grafana. | Prometheus | 30m | Intermediate | -| [Self-Hosted Prometheus Monitoring](/documentation/tutorials-and-examples/hybrid-cloud-prometheus/) | Observability for hybrid/private cloud setups. | Prometheus | 30m | Intermediate | \ No newline at end of file +| [Qdrant Cloud Prometheus Monitoring](/documentation/ops-monitoring/managed-cloud-prometheus/) | Observability with Prometheus and Grafana. | Prometheus | 30m | Intermediate | +| [Self-Hosted Prometheus Monitoring](/documentation/ops-monitoring/hybrid-cloud-prometheus/) | Observability for hybrid/private cloud setups. | Prometheus | 30m | Intermediate | \ No newline at end of file diff --git a/qdrant-landing/content/documentation/hybrid-cloud/_index.md b/qdrant-landing/content/documentation/hybrid-cloud/_index.md index ba1922490..70ab3d5be 100644 --- a/qdrant-landing/content/documentation/hybrid-cloud/_index.md +++ b/qdrant-landing/content/documentation/hybrid-cloud/_index.md @@ -1,7 +1,7 @@ --- title: Hybrid Cloud -weight: 16 -partition: cloud +weight: 225 +partition: deploy --- # Qdrant Hybrid Cloud diff --git a/qdrant-landing/content/documentation/hybrid-cloud/configure-scale-upgrade.md b/qdrant-landing/content/documentation/hybrid-cloud/configure-scale-upgrade.md index 71ddf2c84..8257b5891 100644 --- a/qdrant-landing/content/documentation/hybrid-cloud/configure-scale-upgrade.md +++ b/qdrant-landing/content/documentation/hybrid-cloud/configure-scale-upgrade.md @@ -1,6 +1,6 @@ --- title: Configure, Scale & Update Clusters -weight: 3 +weight: 15 --- # Configure, Scale & Update Qdrant Hybrid Cloud Clusters diff --git a/qdrant-landing/content/documentation/hybrid-cloud/hybrid-cloud-cluster-creation.md b/qdrant-landing/content/documentation/hybrid-cloud/hybrid-cloud-cluster-creation.md index 4da7a3d5a..7c383660e 100644 --- a/qdrant-landing/content/documentation/hybrid-cloud/hybrid-cloud-cluster-creation.md +++ b/qdrant-landing/content/documentation/hybrid-cloud/hybrid-cloud-cluster-creation.md @@ -1,6 +1,6 @@ --- title: Create a Cluster -weight: 2 +weight: 10 --- # Creating a Qdrant Cluster in Hybrid Cloud @@ -64,7 +64,7 @@ If you want to retrieve the secret again, you can also use `kubectl`: kubectl get secret qdrant-api-key -o jsonpath="{.data.api-key}" --namespace the-qdrant-namespace | base64 --decode ``` -After configuring the API key secret, you can create JWTs with granular access control in the Qdrant Cluster UI. Please refer to the [Granular access control with JWT](/documentation/operations/security/#granular-access-control-with-jwt) documentation for more details. +After configuring the API key secret, you can create JWTs with granular access control in the Qdrant Cluster UI. Please refer to the [Granular access control with JWT](/documentation/security/#granular-access-control-with-jwt) documentation for more details. #### Watch the Video diff --git a/qdrant-landing/content/documentation/hybrid-cloud/hybrid-cloud-setup.md b/qdrant-landing/content/documentation/hybrid-cloud/hybrid-cloud-setup.md index 8a3e0cbd9..65cf7e90e 100644 --- a/qdrant-landing/content/documentation/hybrid-cloud/hybrid-cloud-setup.md +++ b/qdrant-landing/content/documentation/hybrid-cloud/hybrid-cloud-setup.md @@ -1,6 +1,6 @@ --- title: Setup Hybrid Cloud -weight: 1 +weight: 5 --- # Creating a Hybrid Cloud Environment @@ -52,7 +52,7 @@ You will need to have access to the Kubernetes cluster with `kubectl` and `helm` You can also configure the StorageClass and VolumeSnapshotClass to use for the Qdrant databases, if you want to deviate from the default settings of your cluster. -By default, Qdrant Cloud will provision two volumes per Qdrant Pod: One for the data stored within Qdrant, and one for [collection snapshots](/documentation/operations/snapshots/). By default, the same StorageClass will be used for both volumes. You can also configure a different StorageClass in the advanced configuration options of your Hybrid Cloud environment. If you want to disable the snapshot volume, you can configure `emptyDir` as a Snapshot StorageClass. +By default, Qdrant Cloud will provision two volumes per Qdrant Pod: One for the data stored within Qdrant, and one for [collection snapshots](/documentation/snapshots/). By default, the same StorageClass will be used for both volumes. You can also configure a different StorageClass in the advanced configuration options of your Hybrid Cloud environment. If you want to disable the snapshot volume, you can configure `emptyDir` as a Snapshot StorageClass. ![Create Hybrid Cloud Environment](/documentation/cloud/hybrid_cloud_env_create.png) diff --git a/qdrant-landing/content/documentation/hybrid-cloud/networking-logging-monitoring.md b/qdrant-landing/content/documentation/hybrid-cloud/networking-logging-monitoring.md index 57881776a..6db4c2ca4 100644 --- a/qdrant-landing/content/documentation/hybrid-cloud/networking-logging-monitoring.md +++ b/qdrant-landing/content/documentation/hybrid-cloud/networking-logging-monitoring.md @@ -1,6 +1,6 @@ --- title: Networking, Logging & Monitoring -weight: 4 +weight: 25 --- # Configuring Networking, Logging & Monitoring in Qdrant Hybrid Cloud diff --git a/qdrant-landing/content/documentation/hybrid-cloud/operator-configuration.md b/qdrant-landing/content/documentation/hybrid-cloud/operator-configuration.md index b23316fa5..31e601149 100644 --- a/qdrant-landing/content/documentation/hybrid-cloud/operator-configuration.md +++ b/qdrant-landing/content/documentation/hybrid-cloud/operator-configuration.md @@ -1,6 +1,6 @@ --- title: Configure the Qdrant Operator -weight: 4 +weight: 20 --- # Configuring Qdrant Operator: Advanced Options diff --git a/qdrant-landing/content/documentation/hybrid-cloud/platform-deployment-options.md b/qdrant-landing/content/documentation/hybrid-cloud/platform-deployment-options.md index 56dfa0382..80f113b38 100644 --- a/qdrant-landing/content/documentation/hybrid-cloud/platform-deployment-options.md +++ b/qdrant-landing/content/documentation/hybrid-cloud/platform-deployment-options.md @@ -1,6 +1,6 @@ --- title: Deployment Platforms -weight: 5 +weight: 30 --- # Qdrant Hybrid Cloud: Hosting Platforms & Deployment Options diff --git a/qdrant-landing/content/documentation/inference.md b/qdrant-landing/content/documentation/inference.md index 98e1aae16..ff6ff3e06 100644 --- a/qdrant-landing/content/documentation/inference.md +++ b/qdrant-landing/content/documentation/inference.md @@ -1,7 +1,7 @@ --- title: Inference -weight: 220 -partition: qdrant +weight: 215 +partition: develop aliases: - ../inference --- diff --git a/qdrant-landing/content/documentation/operations/installation.md b/qdrant-landing/content/documentation/installation.md similarity index 91% rename from qdrant-landing/content/documentation/operations/installation.md rename to qdrant-landing/content/documentation/installation.md index 174422020..6e459214f 100644 --- a/qdrant-landing/content/documentation/operations/installation.md +++ b/qdrant-landing/content/documentation/installation.md @@ -1,9 +1,11 @@ --- title: Installation -weight: 10 +partition: deploy +weight: 110 aliases: - - ../install - - ../installation + - /documentation/install + - /documentation/installation + - /documentation/operations/installation --- # Installation requirements @@ -39,15 +41,15 @@ Qdrant won't work with [Network file systems](https://en.wikipedia.org/wiki/File If you offload vectors to a local disk, we recommend you use a solid-state (SSD or NVMe) drive. - + ### Networking Each Qdrant instance requires three open ports: -* `6333` - For the HTTP API, for the [Monitoring](/documentation/operations/monitoring/) health and metrics endpoints +* `6333` - For the HTTP API, for the [Monitoring](/documentation/ops-monitoring/monitoring/) health and metrics endpoints * `6334` - For the [gRPC](/documentation/interfaces/#grpc-interface) API -* `6335` - For [Distributed deployment](/documentation/operations/distributed_deployment/) +* `6335` - For [Distributed deployment](/documentation/distributed_deployment/) All Qdrant instances in a cluster must be able to: @@ -56,7 +58,7 @@ All Qdrant instances in a cluster must be able to: ### Security -The default configuration of Qdrant might not be secure enough for every situation. Please see [our security documentation](/documentation/operations/security/) for more information. +The default configuration of Qdrant might not be secure enough for every situation. Please see [our security documentation](/documentation/security/) for more information. ## Installation options @@ -81,7 +83,7 @@ We provide a Qdrant Enterprise Operator for Kubernetes installations as part of ### Kubernetes -You can use a ready-made [Helm Chart](https://helm.sh/docs/) to run Qdrant in your Kubernetes cluster. While it is possible to deploy Qdrant in a distributed setup with the Helm chart, it does not come with the same level of features for zero-downtime upgrades, up and down-scaling, monitoring, logging, and backup and disaster recovery as the Qdrant Cloud offering or the Qdrant Private Cloud Enterprise Operator. Instead you must manage and set this up [yourself](/documentation/operations/distributed_deployment/). Support for the Helm chart is limited to community support. +You can use a ready-made [Helm Chart](https://helm.sh/docs/) to run Qdrant in your Kubernetes cluster. While it is possible to deploy Qdrant in a distributed setup with the Helm chart, it does not come with the same level of features for zero-downtime upgrades, up and down-scaling, monitoring, logging, and backup and disaster recovery as the Qdrant Cloud offering or the Qdrant Private Cloud Enterprise Operator. Instead you must manage and set this up [yourself](/documentation/distributed_deployment/). Support for the Helm chart is limited to community support. The following table gives you an overview about the feature differences between the Qdrant Cloud and the Helm chart: @@ -123,11 +125,11 @@ However, you can also use Docker and Docker Compose to run Qdrant in production, In addition, you have to make sure: * To use a performant [persistent storage](#storage) for your data -* To configure the [security settings](/documentation/operations/security/) for your deployment -* To set up and configure Qdrant on multiple nodes for a highly available [distributed deployment](/documentation/operations/distributed_deployment/) +* To configure the [security settings](/documentation/security/) for your deployment +* To set up and configure Qdrant on multiple nodes for a highly available [distributed deployment](/documentation/distributed_deployment/) * To set up a load balancer for your Qdrant cluster -* To create a [backup and disaster recovery strategy](/documentation/operations/snapshots/) for your data -* To integrate Qdrant with your [monitoring](/documentation/operations/monitoring/) and logging solutions +* To create a [backup and disaster recovery strategy](/documentation/snapshots/) for your data +* To integrate Qdrant with your [monitoring](/documentation/ops-monitoring/monitoring/) and logging solutions ## Development @@ -178,7 +180,7 @@ docker run -p 6333:6333 \ ./qdrant --config-path config/custom_config.yaml ``` -For more information, see the [Configuration](/documentation/operations/configuration/) documentation. +For more information, see the [Configuration](/documentation/ops-configuration/configuration/) documentation. ### Docker Compose diff --git a/qdrant-landing/content/documentation/interfaces.md b/qdrant-landing/content/documentation/interfaces.md index 518f9e29b..f03c736dc 100644 --- a/qdrant-landing/content/documentation/interfaces.md +++ b/qdrant-landing/content/documentation/interfaces.md @@ -1,7 +1,7 @@ --- title: API & SDKs -weight: 235 -partition: qdrant +weight: 230 +partition: develop --- # Interfaces diff --git a/qdrant-landing/content/documentation/manage-data/_index.md b/qdrant-landing/content/documentation/manage-data/_index.md index 3d41054ec..6bd6fa103 100644 --- a/qdrant-landing/content/documentation/manage-data/_index.md +++ b/qdrant-landing/content/documentation/manage-data/_index.md @@ -1,7 +1,7 @@ --- title: Manage Data weight: 205 -partition: qdrant +partition: develop --- # Manage Data diff --git a/qdrant-landing/content/documentation/manage-data/collections.md b/qdrant-landing/content/documentation/manage-data/collections.md index 9bc3f38b6..aa736988c 100644 --- a/qdrant-landing/content/documentation/manage-data/collections.md +++ b/qdrant-landing/content/documentation/manage-data/collections.md @@ -41,11 +41,11 @@ In addition to the required options, you can also specify custom values for the * `hnsw_config` - see [indexing](/documentation/manage-data/indexing/#vector-index) for details. * `wal_config` - Write-Ahead-Log related configuration. See more details about [WAL](/documentation/manage-data/storage/#versioning) -* `optimizers_config` - see [optimizer](/documentation/operations/optimizer/) for details. -* `shard_number` - which defines how many shards the collection should have. See [distributed deployment](/documentation/operations/distributed_deployment/#sharding) section for details. +* `optimizers_config` - see [optimizer](/documentation/ops-optimization/optimizer/) for details. +* `shard_number` - which defines how many shards the collection should have. See [distributed deployment](/documentation/distributed_deployment/#sharding) section for details. * `on_disk_payload` - defines where to store payload data. If `true` - payload will be stored on disk only. Might be useful for limiting the RAM usage in case of large payload. * `quantization_config` - see [quantization](/documentation/manage-data/quantization/#setting-up-quantization-in-qdrant) for details. -* `strict_mode_config` - see [strict mode](/documentation/operations/administration/#strict-mode) for details. +* `strict_mode_config` - see [strict mode](/documentation/ops-configuration/administration/#strict-mode) for details. Default parameters for the optional collection parameters are defined in [configuration file](https://github.com/qdrant/qdrant/blob/master/config/config.yaml). @@ -166,12 +166,12 @@ The following command enables indexing for segments that have more than 10000 kB The following parameters can be updated: -* `optimizers_config` - see [optimizer](/documentation/operations/optimizer/) for details. +* `optimizers_config` - see [optimizer](/documentation/ops-optimization/optimizer/) for details. * `hnsw_config` - see [indexing](/documentation/manage-data/indexing/#vector-index) for details. * `quantization_config` - see [quantization](/documentation/manage-data/quantization/#setting-up-quantization-in-qdrant) for details. * `vectors_config` - vector-specific configuration, including individual `hnsw_config`, `quantization_config` and `on_disk` settings. * `params` - other collection parameters, including `read_fan_out_delay_ms`, `write_consistency_factor` and `on_disk_payload`. -* `strict_mode_config` - see [strict mode](/documentation/operations/administration/#strict-mode) for details. +* `strict_mode_config` - see [strict mode](/documentation/ops-configuration/administration/#strict-mode) for details. Full API specification is available in [schema definitions](https://api.qdrant.tech/api-reference/collections/update-collection). @@ -329,7 +329,7 @@ _Note: these numbers may be removed in a future version of Qdrant._ ### Indexing vectors in HNSW In some cases, you might be surprised the value of `indexed_vectors_count` is lower than you expected. This is an intended behaviour and -depends on the [optimizer configuration](/documentation/operations/optimizer/). A new index segment is built if the size of non-indexed vectors is higher than the +depends on the [optimizer configuration](/documentation/ops-optimization/optimizer/). A new index segment is built if the size of non-indexed vectors is higher than the value of `indexing_threshold`(in kB). If your collection is very small or the dimensionality of the vectors is low, there might be no HNSW segment created and `indexed_vectors_count` might be equal to `0`. diff --git a/qdrant-landing/content/documentation/manage-data/indexing.md b/qdrant-landing/content/documentation/manage-data/indexing.md index bdc969ebf..f7f34011d 100644 --- a/qdrant-landing/content/documentation/manage-data/indexing.md +++ b/qdrant-landing/content/documentation/manage-data/indexing.md @@ -12,7 +12,7 @@ A key feature of Qdrant is the effective combination of vector and traditional i The indexes in the segments exist independently, but the parameters of the indexes themselves are configured for the whole collection. Not all segments automatically have indexes. -Their necessity is determined by the [optimizer](/documentation/operations/optimizer/) settings and depends, as a rule, on the number of stored points. +Their necessity is determined by the [optimizer](/documentation/ops-optimization/optimizer/) settings and depends, as a rule, on the number of stored points. ## Payload Index diff --git a/qdrant-landing/content/documentation/manage-data/multitenancy.md b/qdrant-landing/content/documentation/manage-data/multitenancy.md index 97fc6d509..58feadac8 100644 --- a/qdrant-landing/content/documentation/manage-data/multitenancy.md +++ b/qdrant-landing/content/documentation/manage-data/multitenancy.md @@ -79,7 +79,7 @@ To address this problem, in v1.16.0 Qdrant provides a built-in mechanism for tie With tiered multitenancy, you can implement two levels of tenant isolation within a single collection, keeping small tenants together inside a shared Shard, while isolating large tenants into their own dedicated Shards. There are 3 components in Qdrant, that allows you to implement tiered multitenancy: -- [**User-defined Sharding**](/documentation/operations/distributed_deployment/#user-defined-sharding) allows you to create named Shards within a collection. It allows to isolate large tenants into their own Shards. +- [**User-defined Sharding**](/documentation/distributed_deployment/#user-defined-sharding) allows you to create named Shards within a collection. It allows to isolate large tenants into their own Shards. - **Fallback shards** - a special routing mechanism that allows to route request to either a dedicated Shard (if it exists) or to a shared Fallback Shard. It allows to keep requests unified, without the need to know whether a tenant is dedicated or shared. - **Tenant promotion** - a mechanism that allows to move tenants from the shared Fallback Shard to their own dedicated Shard when they grow large enough. This process is based on Qdrant's internal shard transfer mechanism, which makes promotion completely transparent for the application. Both read and write requests are supported during the promotion process. diff --git a/qdrant-landing/content/documentation/manage-data/storage.md b/qdrant-landing/content/documentation/manage-data/storage.md index a893b057c..449db24e5 100644 --- a/qdrant-landing/content/documentation/manage-data/storage.md +++ b/qdrant-landing/content/documentation/manage-data/storage.md @@ -51,7 +51,7 @@ This is the recommended way, in case your Qdrant instance operates with fast dis There are two ways to do this: - 1. You can set the threshold globally in the [configuration file](/documentation/operations/configuration/). The parameter is called `memmap_threshold` (previously `memmap_threshold_kb`). + 1. You can set the threshold globally in the [configuration file](/documentation/ops-configuration/configuration/). The parameter is called `memmap_threshold` (previously `memmap_threshold_kb`). 2. You can set the threshold for each collection separately during [creation](/documentation/manage-data/collections/#create-collection) or [update](/documentation/manage-data/collections/#update-collection-parameters). {{< code-snippet path="/documentation/headless/snippets/create-collection/with-optimizer-config/" >}} @@ -81,7 +81,7 @@ If you need to query vectors with some payload-based conditions - checking value In this scenario, we recommend creating a payload index for each field used in filtering conditions to avoid disk access. Once you create the field index, Qdrant will preserve all values of the indexed field in RAM regardless of the payload storage type. -You can specify the desired type of payload storage with [configuration file](/documentation/operations/configuration/) or with collection parameter `on_disk_payload` during [creation](/documentation/manage-data/collections/#create-collection) of the collection. +You can specify the desired type of payload storage with [configuration file](/documentation/ops-configuration/configuration/) or with collection parameter `on_disk_payload` during [creation](/documentation/manage-data/collections/#create-collection) of the collection. ## Versioning diff --git a/qdrant-landing/content/documentation/observability/datadog.md b/qdrant-landing/content/documentation/observability/datadog.md index 43e5a72fc..4040df38e 100644 --- a/qdrant-landing/content/documentation/observability/datadog.md +++ b/qdrant-landing/content/documentation/observability/datadog.md @@ -20,7 +20,7 @@ You can install the [Qdrant integration](https://docs.datadoghq.com/integrations datadog-agent integration install -t qdrant==1.0.0 ``` -- Edit the `conf.d/qdrant.d/conf.yaml` file in your [Agent's configuration directory](https://docs.datadoghq.com/agent/guide/agent-configuration-files/#agent-configuration-directory) to start collecting your [Qdrant metrics](/documentation/operations/monitoring/). +- Edit the `conf.d/qdrant.d/conf.yaml` file in your [Agent's configuration directory](https://docs.datadoghq.com/agent/guide/agent-configuration-files/#agent-configuration-directory) to start collecting your [Qdrant metrics](/documentation/ops-monitoring/monitoring/). Most importantly, set the `openmetrics_endpoint` value to the `/metrics` endpoint of your Qdrant instance. diff --git a/qdrant-landing/content/documentation/operations/_index.md b/qdrant-landing/content/documentation/operations/_index.md index 421f29cf5..906bdfde9 100644 --- a/qdrant-landing/content/documentation/operations/_index.md +++ b/qdrant-landing/content/documentation/operations/_index.md @@ -1,65 +1,10 @@ --- title: Operations -weight: 215 -partition: qdrant +type: delimiter +weight: 100 +partition: deploy +sitemapExclude: True +_build: + publishResources: false + render: never --- - -# Operations - -Everything you need to deploy, configure, and run Qdrant in production. These pages cover installation, capacity planning, distributed setups, security, monitoring, performance optimization, and troubleshooting. - -## Capacity Planning - -[Capacity Planning](/documentation/operations/capacity-planning/) helps you estimate memory and storage requirements based on your vector dimensions, quantization settings, and dataset size. - -## Installation - -[Installation](/documentation/operations/installation/) covers how to run Qdrant using Docker, from packages, or from source, including basic configuration options. - -## Upgrading - -[Upgrading](/documentation/operations/upgrades/) explains how to safely upgrade your Qdrant cluster to a new version with zero downtime, including version compatibility and client SDK updates. - -## Snapshots - -[Snapshots](/documentation/operations/snapshots/) describe how to back up and restore collections at a point in time, for individual nodes or the full cluster. - -## Usage Statistics - -[Usage Statistics](/documentation/operations/usage-statistics/) explains the anonymized telemetry Qdrant collects and how to opt out. - -## Monitoring & Telemetry - -[Monitoring](/documentation/operations/monitoring/) covers Qdrant's metrics endpoint, Prometheus integration, and health-check APIs for observability. - -## Security - -[Security](/documentation/operations/security/) explains how to enable API key authentication and TLS to secure your Qdrant instance. - -## Troubleshooting - -[Troubleshooting](/documentation/operations/common-errors/) lists common errors and their solutions to help diagnose issues quickly. - -## Configuration - -[Configuration](/documentation/operations/configuration/) documents all available Qdrant configuration file settings and environment variable overrides. - -## Administration - -[Administration](/documentation/operations/administration/) covers runtime administration tools, including recovery mode and collection locking. - -## Distributed Deployment - -[Distributed Deployment](/documentation/operations/distributed_deployment/) explains how to run Qdrant as a multi-node cluster, including sharding, replication, and consensus. - -## Running with GPU - -[Running with GPU](/documentation/operations/running-with-gpu/) describes how to enable GPU-accelerated indexing using dedicated Qdrant Docker images for NVIDIA and AMD GPUs. - -## Optimize Performance - -[Optimize Performance](/documentation/operations/optimize/) walks through three main strategies for tuning Qdrant for high speed, low memory, or high precision workloads. - -## Optimizer - -[Optimizer](/documentation/operations/optimizer/) describes the background optimizer process that rebuilds segments to improve search performance over time. diff --git a/qdrant-landing/content/documentation/ops-configuration/_index.md b/qdrant-landing/content/documentation/ops-configuration/_index.md new file mode 100644 index 000000000..351e0c225 --- /dev/null +++ b/qdrant-landing/content/documentation/ops-configuration/_index.md @@ -0,0 +1,25 @@ +--- +title: Configuration +weight: 120 +partition: deploy +--- + +# Configuration + +These pages cover the settings and runtime options available for customizing and administering a Qdrant deployment. + +## Configuration + +[Configuration](/documentation/ops-configuration/configuration/) describes how to customize Qdrant's behavior using config files and environment variables, covering storage paths, network interfaces, performance parameters, and feature flags. + +## Administration + +[Administration](/documentation/ops-configuration/administration/) covers runtime administration tools that let you modify instance behavior without restarting — including recovery mode for resolving out-of-memory situations. + +## Usage Statistics + +[Usage Statistics](/documentation/ops-configuration/usage-statistics/) explains what anonymized telemetry the open-source Qdrant image collects, why it's collected, and how to opt out. + +## Running with GPU + +[Running with GPU](/documentation/ops-configuration/running-with-gpu/) explains how to enable GPU-accelerated vector indexing using dedicated Docker images for NVIDIA and AMD hardware, available from Qdrant v1.13.0. diff --git a/qdrant-landing/content/documentation/operations/administration.md b/qdrant-landing/content/documentation/ops-configuration/administration.md similarity index 97% rename from qdrant-landing/content/documentation/operations/administration.md rename to qdrant-landing/content/documentation/ops-configuration/administration.md index 54b7282f5..c8b86769f 100644 --- a/qdrant-landing/content/documentation/operations/administration.md +++ b/qdrant-landing/content/documentation/ops-configuration/administration.md @@ -1,8 +1,10 @@ --- title: Administration -weight: 55 +weight: 10 aliases: - - ../administration + - /documentation/administration + - /documentation/ops-configuration/administration + - /documentation/operations/administration --- # Administration diff --git a/qdrant-landing/content/documentation/operations/configuration.md b/qdrant-landing/content/documentation/ops-configuration/configuration.md similarity index 98% rename from qdrant-landing/content/documentation/operations/configuration.md rename to qdrant-landing/content/documentation/ops-configuration/configuration.md index 15ad2902d..00c5462e8 100644 --- a/qdrant-landing/content/documentation/operations/configuration.md +++ b/qdrant-landing/content/documentation/ops-configuration/configuration.md @@ -1,9 +1,10 @@ --- title: Configuration -weight: 50 +weight: 5 aliases: - - ../configuration - /guides/configuration/ + - /documentation/ops-configuration/configuration + - /documentation/operations/configuration --- # Configuration @@ -312,7 +313,7 @@ storage: # Default shard transfer method to use if none is defined. # If null - don't have a shard transfer preference, choose automatically. # If stream_records, snapshot or wal_delta - prefer this specific method. - # More info: https://qdrant.tech/documentation/operations/distributed_deployment/#shard-transfer-method + # More info: https://qdrant.tech/documentation/distributed_deployment/#shard-transfer-method shard_transfer_method: null # Default parameters for collections @@ -463,7 +464,7 @@ cluster: compact_wal_entries: 128 # Set to true to prevent service from sending usage statistics to the developers. -# Read more: https://qdrant.tech/documentation/operations/usage-statistics +# Read more: https://qdrant.tech/documentation/ops-configuration/usage-statistics telemetry_disabled: false # TLS configuration. diff --git a/qdrant-landing/content/documentation/operations/running-with-GPU.md b/qdrant-landing/content/documentation/ops-configuration/running-with-GPU.md similarity index 98% rename from qdrant-landing/content/documentation/operations/running-with-GPU.md rename to qdrant-landing/content/documentation/ops-configuration/running-with-GPU.md index 067470de0..cc5a835a5 100644 --- a/qdrant-landing/content/documentation/operations/running-with-GPU.md +++ b/qdrant-landing/content/documentation/ops-configuration/running-with-GPU.md @@ -1,8 +1,11 @@ --- title: Running with GPU -weight: 65 +weight: 20 aliases: - /documentation/guides/running-with-GPU/ + - /documentation/ops-configuration/running-with-gpu + - /documentation/operations/running-with-GPU + - /documentation/operations/running-with-gpu --- # Running Qdrant with GPU Support diff --git a/qdrant-landing/content/documentation/operations/usage-statistics.md b/qdrant-landing/content/documentation/ops-configuration/usage-statistics.md similarity index 96% rename from qdrant-landing/content/documentation/operations/usage-statistics.md rename to qdrant-landing/content/documentation/ops-configuration/usage-statistics.md index 0c15b5381..de57f8ee5 100644 --- a/qdrant-landing/content/documentation/operations/usage-statistics.md +++ b/qdrant-landing/content/documentation/ops-configuration/usage-statistics.md @@ -1,10 +1,12 @@ --- title: Usage Statistics -weight: 30 +weight: 15 aliases: - - ../telemetry + - /documentation/telemetry - /documentation/guides/telemetry - /documentation/guides/usage-statistics/ + - /documentation/ops-configuration/usage-statistics + - /documentation/operations/usage-statistics --- # Usage statistics diff --git a/qdrant-landing/content/documentation/ops-monitoring/_index.md b/qdrant-landing/content/documentation/ops-monitoring/_index.md new file mode 100644 index 000000000..95172f652 --- /dev/null +++ b/qdrant-landing/content/documentation/ops-monitoring/_index.md @@ -0,0 +1,21 @@ +--- +title: Monitoring & Telemetry +weight: 130 +partition: deploy +--- + +# Monitoring & Telemetry + +These pages cover how to observe and measure a running Qdrant deployment using its built-in metrics endpoints and external monitoring tools. + +## Monitoring & Telemetry + +[Monitoring & Telemetry](/documentation/ops-monitoring/monitoring/) describes the Prometheus/OpenMetrics-compatible `/metrics` endpoint, the available metrics, and how to connect Qdrant to a Prometheus and Grafana monitoring stack. + +## Managed Cloud Prometheus Monitoring + +[Managed Cloud Prometheus Monitoring](/documentation/ops-monitoring/managed-cloud-prometheus/) is a step-by-step tutorial for deploying Prometheus and Grafana in a Kubernetes cluster and configuring them to scrape metrics from a Qdrant Managed Cloud database. + +## Self-Hosted Prometheus Monitoring + +[Self-Hosted Prometheus Monitoring](/documentation/ops-monitoring/hybrid-cloud-prometheus/) is a step-by-step tutorial for setting up Prometheus and Grafana monitoring for Qdrant running in a Hybrid Cloud or Private Cloud environment. diff --git a/qdrant-landing/content/documentation/tutorials-and-examples/hybrid-cloud-prometheus.md b/qdrant-landing/content/documentation/ops-monitoring/hybrid-cloud-prometheus.md similarity index 96% rename from qdrant-landing/content/documentation/tutorials-and-examples/hybrid-cloud-prometheus.md rename to qdrant-landing/content/documentation/ops-monitoring/hybrid-cloud-prometheus.md index d1530382d..399ab9b27 100644 --- a/qdrant-landing/content/documentation/tutorials-and-examples/hybrid-cloud-prometheus.md +++ b/qdrant-landing/content/documentation/ops-monitoring/hybrid-cloud-prometheus.md @@ -1,6 +1,9 @@ --- title: Self-Hosted Prometheus Monitoring -weight: 37 +weight: 15 +aliases: + - /documentation/ops-monitoring/hybrid-cloud-prometheus + - /documentation/tutorials-and-examples/hybrid-cloud-prometheus --- # Monitoring Hybrid/Private Cloud with Prometheus and Grafana diff --git a/qdrant-landing/content/documentation/tutorials-and-examples/managed-cloud-prometheus.md b/qdrant-landing/content/documentation/ops-monitoring/managed-cloud-prometheus.md similarity index 95% rename from qdrant-landing/content/documentation/tutorials-and-examples/managed-cloud-prometheus.md rename to qdrant-landing/content/documentation/ops-monitoring/managed-cloud-prometheus.md index ae58d2c08..d22bfe109 100644 --- a/qdrant-landing/content/documentation/tutorials-and-examples/managed-cloud-prometheus.md +++ b/qdrant-landing/content/documentation/ops-monitoring/managed-cloud-prometheus.md @@ -1,6 +1,9 @@ --- title: Managed Cloud Prometheus Monitoring -weight: 36 +weight: 10 +aliases: + - /documentation/ops-monitoring/managed-cloud-prometheus + - /documentation/tutorials-and-examples/managed-cloud-prometheus --- # Monitoring Managed Cloud with Prometheus and Grafana diff --git a/qdrant-landing/content/documentation/operations/monitoring.md b/qdrant-landing/content/documentation/ops-monitoring/monitoring.md similarity index 97% rename from qdrant-landing/content/documentation/operations/monitoring.md rename to qdrant-landing/content/documentation/ops-monitoring/monitoring.md index 20078a828..1da087202 100644 --- a/qdrant-landing/content/documentation/operations/monitoring.md +++ b/qdrant-landing/content/documentation/ops-monitoring/monitoring.md @@ -1,8 +1,10 @@ --- title: Monitoring & Telemetry -weight: 35 +weight: 5 aliases: - - ../monitoring + - /documentation/monitoring + - /documentation/ops-monitoring/monitoring + - /documentation/operations/monitoring --- # Monitoring & Telemetry @@ -63,7 +65,7 @@ Counters - such as the number of created snapshots - are reset when the node is | collection_hardware_metric_vector_io_read | counter | Vector IO read operations measurement, per collection (v1.13+) [^metrics-hwreporting] | | collection_hardware_metric_vector_io_write | counter | Vector IO write operations measurement, per collection (v1.13+) [^metrics-hwreporting] | -[^metrics-hwreporting]: Only reported if hardware metrics are enabled in the configuration. See `service.hardware_reporting` in the [configuration](/documentation/operations/configuration/). +[^metrics-hwreporting]: Only reported if hardware metrics are enabled in the configuration. See `service.hardware_reporting` in the [configuration](/documentation/ops-configuration/configuration/). **Snapshot metrics** @@ -121,7 +123,7 @@ when distributed mode is enabled. | cluster_pending_operations_total | gauge | Number of pending consensus operations [^metrics-distributed] | | cluster_voter | gauge | If a consensus voter (`1`) or learner (`0`) [^metrics-distributed] | -[^metrics-distributed]: Only reported if distributed mode (cluster mode) is enabled. Enabled by default in all Qdrant Cloud environments. See `cluster.enabled` in the [configuration](/documentation/operations/configuration/). +[^metrics-distributed]: Only reported if distributed mode (cluster mode) is enabled. Enabled by default in all Qdrant Cloud environments. See `cluster.enabled` in the [configuration](/documentation/ops-configuration/configuration/). ### Metrics configuration @@ -131,7 +133,7 @@ In self-hosted environments you have further configuration options for metrics. By default, all Qdrant metrics have no application namespace prefix. You may set a prefix with `service.metrics_prefix` in the -[configuration](/documentation/operations/configuration/). +[configuration](/documentation/ops-configuration/configuration/). To achieve this you may use the following environment variable for example: @@ -163,7 +165,7 @@ Qdrant server. These currently provide the most basic status response, returning HTTP 200 if Qdrant is started and ready to be used. -Regardless of whether an [API key](/documentation/operations/security/#authentication) is configured, +Regardless of whether an [API key](/documentation/security/#authentication) is configured, the endpoints are always accessible. You can read more about Kubernetes health endpoints diff --git a/qdrant-landing/content/documentation/ops-optimization/_index.md b/qdrant-landing/content/documentation/ops-optimization/_index.md new file mode 100644 index 000000000..5962f0e8b --- /dev/null +++ b/qdrant-landing/content/documentation/ops-optimization/_index.md @@ -0,0 +1,17 @@ +--- +title: Optimization +weight: 125 +partition: deploy +--- + +# Optimization + +These pages cover strategies and internal mechanisms for improving search performance, reducing memory usage, and managing how Qdrant organizes data on disk. + +## Optimize Performance + +[Optimize Performance](/documentation/ops-optimization/optimize/) walks through three main optimization scenarios — high-speed search, high-precision search, and low memory usage — and the configuration choices that achieve each one. + +## Optimizer + +[Optimizer](/documentation/ops-optimization/optimizer/) explains how Qdrant's background optimizer rebuilds segments to keep data structures efficient, including the vacuum, merge, and indexing stages and the thresholds that trigger them. diff --git a/qdrant-landing/content/documentation/operations/optimize.md b/qdrant-landing/content/documentation/ops-optimization/optimize.md similarity index 97% rename from qdrant-landing/content/documentation/operations/optimize.md rename to qdrant-landing/content/documentation/ops-optimization/optimize.md index 44c8e990c..03014559d 100644 --- a/qdrant-landing/content/documentation/operations/optimize.md +++ b/qdrant-landing/content/documentation/ops-optimization/optimize.md @@ -1,8 +1,10 @@ --- title: Optimize Performance -weight: 70 +weight: 5 aliases: - - ../tutorials/optimize + - /documentation/tutorials/optimize + - /documentation/ops-optimization/optimize + - /documentation/operations/optimize --- # Optimizing Qdrant Performance: Three Scenarios diff --git a/qdrant-landing/content/documentation/operations/optimizer.md b/qdrant-landing/content/documentation/ops-optimization/optimizer.md similarity index 98% rename from qdrant-landing/content/documentation/operations/optimizer.md rename to qdrant-landing/content/documentation/ops-optimization/optimizer.md index 6797fcfc4..891b61b33 100644 --- a/qdrant-landing/content/documentation/operations/optimizer.md +++ b/qdrant-landing/content/documentation/ops-optimization/optimizer.md @@ -1,8 +1,10 @@ --- title: Optimizer -weight: 75 +weight: 10 aliases: - - ../optimizer + - /documentation/optimizer + - /documentation/ops-optimization/optimizer + - /documentation/operations/optimizer --- # Optimizer @@ -160,7 +162,7 @@ Because the update worker must finish indexing before continuing to consume the ### Monitoring Deferred Points -You can check the number of deferred points in a collection via the `update_queue` section in the response of the [collection info API](/documentation/manage-data/collections/#collection-info). The same information is also available in [telemetry and metrics](/documentation/operations/monitoring/), enabling dashboards and alerting. +You can check the number of deferred points in a collection via the `update_queue` section in the response of the [collection info API](/documentation/manage-data/collections/#collection-info). The same information is also available in [telemetry and metrics](/documentation/ops-monitoring/monitoring/), enabling dashboards and alerting. A non-zero deferred point count means the optimizer is processing a backlog. This is expected under heavy write load; monitor the count to confirm that it is decreasing over time. diff --git a/qdrant-landing/content/documentation/overview/_index.md b/qdrant-landing/content/documentation/overview/_index.md index d94c3e72f..5fd35ae06 100644 --- a/qdrant-landing/content/documentation/overview/_index.md +++ b/qdrant-landing/content/documentation/overview/_index.md @@ -6,7 +6,7 @@ aliases: - orientation - concepts - guides -partition: qdrant +partition: develop ---