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Eugene YurtsevandGitHub
200c09b662
- Turn on strict mode to fail docs build if there are any internal broken anchor links. - Fix broken anchor links. - Delete storm tutorial that has fake markdown inside it (we'll figure out how to deal with it later)
91 lines
5.0 KiB
Markdown
91 lines
5.0 KiB
Markdown
---
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search:
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boost: 2
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---
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# LangGraph Control Plane
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The term "control plane" is used broadly to refer to the control plane UI where users create and update [LangGraph Servers](./langgraph_server.md) (deployments) and the control plane APIs that support the UI experience.
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When a user makes an update through the control plane UI, the update is stored in the control plane state. The [LangGraph Data Plane](./langgraph_data_plane.md) "listener" application polls for these updates by calling the control plane APIs.
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## Control Plane UI
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From the control plane UI, you can:
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- View a list of outstanding deployments.
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- View details of an individual deployment.
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- Create a new deployment.
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- Update a deployment.
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- Update environment variables for a deployment.
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- View build and server logs of a deployment.
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- Delete a deployment.
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The Control Plane UI is embedded in [LangSmith](https://docs.smith.langchain.com/langgraph_cloud).
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## Control Plane API
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This section describes data model of the control plane API. The API is used to create, update, and delete deployments. However, they are not publicly accessible.
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### Deployment
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A deployment is an instance of a LangGraph Server. A single deployment can have many revisions.
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### Revision
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A revision is an iteration of a deployment. When a new deployment is created, an initial revision is automatically created. To deploy code changes or update environment variables for a deployment, a new revision must be created.
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### Environment Variable
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Environment variables are set for a deployment. All environment variables are stored as secrets (i.e. saved in a secrets store).
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## Control Plane Features
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This section describes various features of the control plane.
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### Deployment Types
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For simplicity, the control plane offers two deployment types with different resource allocations: `Development` and `Production`.
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| **Deployment Type** | **CPU** | **Memory** | **Scaling** |
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|---------------------|---------|------------|---------------------|
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| Development | 1 CPU | 1 GB | Up to 1 container |
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| Production | 2 CPU | 2 GB | Up to 10 containers |
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CPU and memory resources are per container.
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!!! info "For [Cloud SaaS](../concepts/langgraph_cloud.md)"
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For `Production` type deployments, resources can be manually increased on a case-by-case basis depending on use case and capacity constraints. Contact support@langchain.dev to request an increase in resources.
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!!! info
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Resources for [Self-Hosted Data Plane](../concepts/langgraph_self_hosted_data_plane.md) and [Self-Hosted Control Plane](../concepts/langgraph_self_hosted_control_plane.md) deployments can be fully customized.
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### Database Provisioning
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The control plane and [LangGraph Data Plane](./langgraph_data_plane.md) "listener" application coordinate to automatically create a Postgres database for each deployment. The database serves as the [persistence layer](../concepts/persistence.md) for the deployment.
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When implementing a LangGraph application, a [checkpointer](../concepts/persistence.md#checkpointer-libraries) does not need to be configured by the developer. Instead, a checkpointer is automatically configured for the graph. Any checkpointer configured for a graph will be replaced by the one that is automatically configured.
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There is no direct access to the database. All access to the database occurs through the [LangGraph Server](../concepts/langgraph_server.md).
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The database is never deleted until the deployment itself is deleted.
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!!! info
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A custom Postgres instance can be configured for [Self-Hosted Data Plane](../concepts/langgraph_self_hosted_data_plane.md) and [Self-Hosted Control Plane](../concepts/langgraph_self_hosted_control_plane.md) deployments.
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### Asynchronous Deployment
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Infrastructure for deployments and revisions are provisioned and deployed asynchronously. They are not deployed immediately after submission. Currently, deployment can take up to several minutes.
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- When a new deployment is created, a new database is created for the deployment. Database creation is a one-time step. This step contributes to a longer deployment time for the initial revision of the deployment.
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- When a subsequent revision is created for a deployment, there is no database creation step. The deployment time for a subsequent revision is significantly faster compared to the deployment time of the initial revision.
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- The deployment process for each revision contains a build step, which can take up to a few minutes.
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The control plane and [LangGraph Data Plane](./langgraph_data_plane.md) "listener" application coordinate to achieve asynchronous deployments.
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### LangSmith Integration
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A [LangSmith](https://docs.smith.langchain.com/) tracing project is automatically created for each deployment. The tracing project has the same name as the deployment. When creating a deployment, the `LANGCHAIN_TRACING` and `LANGSMITH_API_KEY`/`LANGCHAIN_API_KEY` environment variables do not need to be specified; they are set automatically by the control plane.
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When a deployment is deleted, the traces and the tracing project are not deleted.
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