Update cloud configuration pages

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mjang
2024-02-20 10:06:23 -08:00
parent 87ea850b8c
commit a4ff8fbdd1
4 changed files with 90 additions and 33 deletions
@@ -10,24 +10,58 @@ This page shows you how to use the Qdrant Cloud Console to create a custom Qdran
> **Prerequisite:** Please make sure you have provided billing information before creating a custom cluster.
1. Start in the **Clusters** section of the [Cloud Dashboard](https://cloud.qdrant.io).
2. Select **Clusters** and then click **+ Create**.
3. A window will open. Enter a cluster **Name**.
4. Currently, you can deploy to AWS, GCP, or Azure.
5. Choose your data center region. If you have latency concerns or other topology-related requirements, [**let us know**](mailto:cloud@qdrant.io).
6. Configure RAM size for each node (1GB to 64GB).
> 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).
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.
8. Select the number of nodes you want the cluster to be deployed on.
> 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.
9. Click **Create** and wait for your cluster to be provisioned.
1. Select **Clusters** and then click **+ Create**.
1. In the **Create a cluster** screen select **Free** or **Standard**
For more information on a free cluster, see the [Cloud quickstart](/documentation/cloud/quickstart-cloud). The remaining steps assume you want a standard cluster.
1. Select a provider. Currently, you can deploy to:
Your cluster will be reachable on port 443 and 6333 (Rest) and 6334 (gRPC).
- Amazon Web Services (AWS)
- Google Cloud Platform (GCP)
- Microsoft Azure
1. Choose your data center region. If you have latency concerns or other topology-related requirements, [**let us know**](mailto:cloud@qdrant.io).
1. Configure RAM for each node (2 GB to 64 GB).
> For more informtion, see our [**Capacity and Sizing**](/documentation/cloud/capacity-sizing/) guidance. If you need more capacity per node, [**let us know**](mailto:cloud@qdrant.io).
1. Choose the number of vCPUs per node (0.5 core to 16 cores). If you add more
RAM, the menu provides differnet options for vCPUs.
1. Select the number of nodes you want the cluster to be deployed on.
> 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.
1. Select the disk space for your deployment. You can choose from 8 GB to 2 TB.
1. Review your cluster configuration and pricing.
1. When you're ready, select **Create**. It takes some time to provision your cluster.
Once provisioned, you can access your cluster on ports 443 and 6333 (REST)
and 6334 (gRPC).
![Embeddings](/docs/cloud/create-cluster.png)
You should now see the new cluster in the **Clusters** menu.
A custom cluster includes the following resources. The values in the table are maximums.
| Resource | Value (max) |
|------------|-------------|
| RAM | 64 GB |
| vCPU | 16 vCPU |
| Disk space | 2 TB |
| Nodes | 10 |
### Included features
The features included with this paid cluster are:
- Dedicated resources
- Backup and disaster recovery
- Horizontal and vertical scaling
- Monitoring and log management
To learn more about this paid feature, contact us at <FILL IN BLANK>.
## Next steps
You will need to connect to your new Qdrant Cloud cluster. Follow [**Authentication**](../../cloud/authentication/) to create one or more API keys.
You will need to connect to your new Qdrant Cloud cluster. Follow [**Authentication**](/documentation/cloud/authentication/) to create one or more API keys.
Your new cluster is highly available and responsive to your application requirements and resource load. Read more in [**Cluster Scaling**](../../cloud/cluster-scaling/).
Your new cluster is highly available and responsive to your application requirements and resource load. Read more in [**Cluster Scaling**](/documentation/cloud/cluster-scaling/).