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Merge pull request #248 from qdrant/gcp-quickstart
Update Qdrant Cloud Documentation
This commit is contained in:
David Myriel
@@ -3,15 +3,37 @@ title: Qdrant Cloud
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weight: 20
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---
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# Getting started with Qdrant Cloud
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# About Qdrant Cloud
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Qdrant Cloud is an official cloud-based managed solution by the creators of the [Qdrant](https://github.com/qdrant/qdrant) Vector Search Engine.
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It provides the same fast and reliable similarity search engine, but without a need to maintain your own infrastructure.
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Qdrant Cloud is our SaaS (software-as-a-service) solution, providing managed Qdrant instances on the cloud.
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We provide you with the same fast and reliable similarity search engine, but without the need to maintain your own infrastructure.
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The transition from the on-premise to the cloud version of Qdrant does not require changing anything in the way you interact with the service, except for an API key that has to be provided to each request.
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Transitioning from on-premise to the cloud version of Qdrant does not require changing anything in the way you interact with the service. All you have to do is [create a Qdrant Cloud account](https://qdrant.to/cloud) and [provide a new API key](../cloud/authentication/) to each request.
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The transition is even easier if you use the official client libraries.
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The transition is even easier if you use the official client libraries. For example, the [Python Client](https://github.com/qdrant/qdrant-client) has the support of the API key already built-in, so you only need to provide it once, when the QdrantClient instance is created.
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For example, the Python Qdrant client has the support of the API key already built-in, so you only need to provide it once, when the QdrantClient instance is created.
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### Cluster configuration
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Each instance comes pre-configured with the following tools, features and support services:
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- Automatically created with the latest available version of Qdrant.
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- Upgradeable to later versions of Qdrant as they are released.
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- Equipped with monitoring and logging to observe the health of each cluster.
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- Accessible through the Qdrant Cloud Console.
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- Vertically scalable.
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- Offered on AWS and GCP, with Azure currently in development.
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### Getting started with Qdrant Cloud
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To use Qdrant Cloud, you will need to create at least one cluster. There are two ways to start:
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1. [**Create a Free Tier cluster**](../cloud/quickstart-cloud/) with 1 node and a default configuration (1GB RAM, 0.5 CPU and 4GB Disk). This option is perfect for prototyping and you don't need a credit card to join.
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2. [**Configure a custom cluster**](../cloud/create-cluster/) with additional nodes and more resources. For this option, you will have to provide billing information.
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We recommend that you use the Free Tier cluster for testing purposes. The capacity should be enough to serve up to 1M vectors of 768dim. To calculate your needs, refer to [capacity planning](../capacity/).
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### Support & Troubleshooting
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All Qdrant Cloud users are welcome to join our [Discord community](https://qdrant.to/discord). Our Support Engineers are available to help you anytime.
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Additionally, paid customers can also contact support via channels provided during cluster creation and/or on-boarding.
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Please see [**Quick Start**](../cloud/cloud-quick-start/) section for details.
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@@ -0,0 +1,40 @@
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---
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title: Authentication
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weight: 30
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---
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# Authentication
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This page shows you how to use the Qdrant Cloud Console to create a custom API key for a cluster. You will learn how to connect to your cluster using the new API key.
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## Create API keys
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The API key is only shown once after creation. If you lose it, you will need to create a new one.
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However, we recommend rotating the keys from time to time. To create additional API keys do the following.
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1. Go to the **Access** section in the Dashboard.
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2. The **Access Management** list will display all available API keys.
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3. Click **Create** and choose a cluster name from the dropdown menu.
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> **Note:** You can create a key that provides access to multiple clusters. Simply check off which cluster in the dropdown
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4. Click **OK** and retrieve your API key.
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## Authenticate via Python client
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Now that you have created your first cluster and key, you might want to access Qdrant Cloud from within your application.
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Our official Qdrant clients for Python, Go, and Rust all support the API key parameter.
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```python
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from qdrant_client import QdrantClient
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qdrant_client = QdrantClient(
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"xyz-example.eu-central.aws.staging-cloud.qdrant.io",
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prefer_grpc=True,
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api_key="<<-provide-your-own-key->>",
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)
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```
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```bash
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curl \
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-X GET https://xyz-example.eu-central.aws.staging-cloud.qdrant.io:6333 \
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--header 'api-key: <provide-your-own-key>'
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```
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@@ -1,6 +1,6 @@
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---
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title: Backups
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weight: 20
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weight: 30
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---
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# Backups
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@@ -16,7 +16,7 @@ For less critical use-cases you can make use of one of the available options.
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Qdrant engine offers a snapshot API that allows to create a snapshot of a particular collection or even the whole storage.
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Please refer to the [snapshot documentation](../../concepts/snapshots/) for details.
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A quick recipe for successfully snapshotting and recovering a collection:
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Here is how you can quickly snapshot and recover a collection:
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1. Take a snapshot
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- In case of a single node cluster, simply call the snapshot endpoint on the exposed url.
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@@ -29,12 +29,10 @@ A quick recipe for successfully snapshotting and recovering a collection:
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## Automatic backups
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**Note: not available in the beta version.**
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We are currently offering this service on a request-only basis. Please [**let us know**](mailto:cloud@qdrant.io) if you would like to activate automatic backups.
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The cloud platform offers an option for automatic system backups. It is possible to configure periodical system level snapshots to restore a cluster from a hard copy. On the cluster settings section you can choose how often a backup should be done and how many latest copies should be kept on the backup storage.
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Note: not available in the beta version.
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The cloud platform offers an option for automatic system backups.
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It is possible to configure periodical system level snapshots to restore a cluster from a hard copy.
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On the cluster settings section you can choose how often a backup should be done and how many latest copies should be kept on the backup storage.
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To restore a Qdrant cluster from backup, you can select a desired backup copy version and start the reporting process.
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Attention: during the restoring process the affected cluster will not be available because the cluster will be deleted and created from scratch from the backup copy.
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Please also note, that if you changed the cluster topology after the copy was created, the new cluster will reset to the previous configuration.
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+3
-1
@@ -1,6 +1,8 @@
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---
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title: Capacity and sizing
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weight: 20
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weight: 40
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aliases:
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- ../capacity
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---
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# Capacity and sizing
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@@ -1,89 +0,0 @@
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---
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title: Quick Start in Cloud
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weight: 10
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---
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# Getting started with Qdrant Cloud
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To use Qdrant Cloud, you will need to create at least one cluster. There are two ways to start:
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1. Create a Free Tier cluster with 1 node and a default configuration (1GB RAM, 0.5 CPU and 20GB Disk).
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2. Configure a custom cluster with additional nodes and more resources. **You will have to provide billing information.**
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We recommend that you use the Free Tier cluster for testing purposes. The capacity should be enough to serve up to 1M vectors of 768dim. To calculate your needs, refer to [capacity planning](../capacity/).
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## Create a Free Tier cluster
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1. Start in the **Overview** section of the Dashboard.
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2. Under **Set a Cluster Up** enter a **Cluster name**.
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3. Click **Create Free Tier** and then **Continue**.
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4. Under **Get an API Key**, select the cluster and click **Get API Key**.
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5. Save the API key, as you won't be able to request it again. Click **Continue**.
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6. Save the code snippet provided to access your cluster. Click **Complete** to finish setup.
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Now you can test cluster access. Your generated request should be similar to this one:
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```bash
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curl \
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-X GET https://xyz-example.eu-central.aws.cloud.qdrant.io:6333 \
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--header 'api-key: <provide-your-own-key>'
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```
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6. Open Terminal and run the request. You should get a response that looks like this:
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```bash
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{"title":"qdrant - vector search engine","version":"1.1.0"}
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```
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> **Note:** The API key needs to be present in the request header every time you make a request via Rest or gRPC interface.
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## Create a custom cluster
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> **Prerequisite:** Please make sure you have provided billing information before creating a custom cluster.
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1. Start in the **Overview** section of the Dashboard.
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2. Under **Set a Cluster Up** scroll down and click **Create Custom Tier**.
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3. A window will open. Enter a cluster **Name**.
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4. In the Beta version, you can only deploy to AWS. We are currently developing support GCP and Azure.
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5. Choose from one of five data center regions. If you have latency concerns or other topology-related requirements, [let us know](mailto:cloud@qdrant.io).
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6. Configure RAM size for each node (2GB to 64GB).
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> Please read [Capacity and Sizing](https://qdrant.tech/documentation/cloud/capacity/) to make the right choice. If you need more capacity per node, [let us know](mailto:cloud@qdrant.io).
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7. Choose the number of CPUs per node (0.5 core to 16 cores). The max/min number of CPUs is coupled to the chosen RAM size.
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8. Select the number of nodes you want the cluster to be deployed on.
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> Each node is automatically attached with a disk space offering enough space for your data if you decide to put the metadata or even the index on the disk storage.
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9. Click **Create** and wait for your cluster to be provisioned.
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Your cluster will be reachable on port 443 and 6333 (Rest) and 6334 (Grpc).
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10. Follow **Step 6** from the above **Create a Free Tier cluster** instruction set to verify cluster access
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## Create additional API keys
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The API key is only shown once after creation. If you lose it, you will need to create a new one.
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However, we recommend rotating the keys from time to time.
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1. To create more API keys, go to the **Access** section in the Dashboard.
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2. The **Access Management** list will display all available API keys.
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3. Click **Create** and choose a cluster name from the dropdown menu.
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> **Note:** You can create a key that provides access to multiple clusters. Simply check off which cluster in the dropdown
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4. Click **OK** and retrieve your API key.
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## Authentication via Python client
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Now that you have created your first cluster and key, you might want to access Qdrant Cloud from within your application.
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Our official Qdrant clients for Python, Go, and Rust all support the API key parameter.
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Sample Python code
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```python
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from qdrant_client import QdrantClient
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qdrant_client = QdrantClient(
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"xyz-example.eu-central.aws.staging-cloud.qdrant.io",
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prefer_grpc=True,
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api_key="<<-provide-your-own-key->>",
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)
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```
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```bash
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curl \
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-X GET https://xyz-example.eu-central.aws.staging-cloud.qdrant.io:6333 \
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--header 'api-key: <provide-your-own-key>'
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```
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@@ -1,6 +1,6 @@
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---
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title: Cluster scaling
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weight: 30
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weight: 50
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---
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# Cluster scaling
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@@ -33,5 +33,5 @@ Please refer to the [sharding documentation](../../guides/distributed_deployment
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Important: The number of shards means the maximum amount of nodes you can add to your cluster. In the beginning, all the shards can reside on one node.
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With the growing amount of data you can add nodes to your cluster and move shards to the dedicated nodes using the [cluster setup API](../../guides/distributed_deployment/#cluster-scaling).
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We, the Qdrant team, will be glad to consult you on an optimal strategy for scaling.
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We will be glad to consult you on an optimal strategy for scaling.
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[Let us know](mailto:cloud@qdrant.io) your needs and decide together on a proper solution. We plan to introduce an auto-scaling functionality. Since it is one of most desired features, it has a high priority on our Cloud roadmap.
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@@ -0,0 +1,33 @@
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---
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title: Create a cluster
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weight: 20
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---
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# Create a cluster
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This page shows you how to use the Qdrant Cloud Console to create a custom Qdrant Cloud cluster.
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> **Prerequisite:** Please make sure you have provided billing information before creating a custom cluster.
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1. Start in the **Clusters** section of the Dashboard.
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2. Under **Clusters** click **+ Create**.
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3. A window will open. Enter a cluster **Name**.
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4. Currently, you can deploy to AWS or GCP. We are developing support for Azure.
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5. Choose your data center region. If you have latency concerns or other topology-related requirements, [**let us know**](mailto:cloud@qdrant.io).
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6. Configure RAM size for each node (1GB to 64GB).
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> Please read [**Capacity and Sizing**](../../cloud/capacity-sizing/) to make the right choice. If you need more capacity per node, [**let us know**](mailto:cloud@qdrant.io).
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7. Choose the number of CPUs per node (0.5 core to 16 cores). The max/min number of CPUs is coupled to the chosen RAM size.
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8. Select the number of nodes you want the cluster to be deployed on.
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> Each node is automatically attached with a disk space offering enough space for your data if you decide to put the metadata or even the index on the disk storage.
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9. Click **Create** and wait for your cluster to be provisioned.
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Your cluster will be reachable on port 443 and 6333 (Rest) and 6334 (gRPC).
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## Next steps
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You will need to connect to your new Qdrant Cloud cluster. Follow [**Authentication**](../../cloud/authentication/) to create one or more API keys.
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Your new cluster is highly available and responsive to your application requirements and resource load. Read more in [**Cluster Scaling**](../../cloud/cluster-scaling/).
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@@ -0,0 +1,51 @@
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---
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title: Quickstart
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weight: 10
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aliases:
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- ../cloud-quick-start
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---
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# Quickstart
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This page shows you how to use the Qdrant Cloud Console to create a free tier cluster and then connect to it with Qdrant Client.
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## Step 1: Create a Free Tier cluster
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1. Start in the **Overview** section of the Dashboard.
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2. Under **Set a Cluster Up** enter a **Cluster name**.
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3. Click **Create Free Tier** and then **Continue**.
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4. Under **Get an API Key**, select the cluster and click **Get API Key**.
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5. Save the API key, as you won't be able to request it again. Click **Continue**.
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6. Save the code snippet provided to access your cluster. Click **Complete** to finish setup.
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## Step 2: Test cluster access
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After creation, you will receive a code snippet to access your cluster. Your generated request should look very similar to this one:
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```bash
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curl \
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-X GET https://xyz-example.eu-central.aws.cloud.qdrant.io:6333 \
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--header 'api-key: <paste-your-api-key-here>'
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```
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Open Terminal and run the request. You should get a response that looks like this:
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```bash
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{"title":"qdrant - vector search engine","version":"1.4.1"}
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```
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> **Note:** The API key needs to be present in the request header every time you make a request via Rest or gRPC interface.
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## Step 3: Authenticate via Python client
|
||||
|
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Now that you have created your first cluster and key, you might want to access Qdrant Cloud from within your application.
|
||||
Our official Qdrant clients for Python, Go, and Rust all support the API key parameter.
|
||||
|
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```python
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from qdrant_client import QdrantClient
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qdrant_client = QdrantClient(
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"xyz-example.eu-central.aws.staging-cloud.qdrant.io",
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prefer_grpc=True,
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api_key="<paste-your-api-key-here>",
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)
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```
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