| title | Self-hosted LangSmith |
|---|---|
| sidebarTitle | Overview |
Self-hosted LangSmith is an add-on to the Enterprise plan designed for our largest, most security-conscious customers. For more details, refer to [Pricing](https://www.langchain.com/pricing). [Contact our sales team](https://www.langchain.com/contact-sales) if you want to get a license key to trial LangSmith in your environment.
LangSmith supports different self-hosted configurations depending on your scale, security, and infrastructure needs.
You can use LangSmith for observability and evaluation without agent deployment. Or, you can set up the full self-hosted platform for observability, evaluation, and agent deployment. Alternatively, you can deploy agents directly without the control plane.
**For step-by-step setup instructions for self-hosted LangSmith on AWS, GCP, or Azure**, refer to our cloud architecture guides: [AWS](/langsmith/aws-self-hosted), [GCP](/langsmith/gcp-self-hosted), or [Azure](/langsmith/azure-self-hosted).This page provides an overview of each self-hosted model:
Host an instance of LangSmith that includes observability, tracing, and evaluations in the UI and API. Best for teams who want self-hosted monitoring and evaluation without deploying agents.<Card title="LangSmith Observability, Evaluation, and Deployment" icon="stack-2" href="#enable-langsmith-deployment"
Enables deploying graphs to Agent Server via the control plane. The control plane and data plane provide the full LangSmith platform for running and monitoring agents. This includes observability, evaluation, and deployment.
<Card title="Standalone server" icon="server" href="#standalone-server"
Host an Agent Server directly without the control plane UI. A lightweight option for running one or a few agents as independent services, with full control over scaling and integration.
| Model | Includes | Best for | Methods |
|---|---|---|---|
| Observability & Evaluation |
|
|
|
| Observability, Evaluation & Deployment |
|
|
|
| Standalone server |
|
|
|
Supported compute platforms: Kubernetes (for LangSmith Deployment), any compute platform (for Standalone Server)
Host an instance of LangSmith that includes observability, tracing, and evaluations in the UI and API, but without the ability to deploy agents through the control plane.
This includes:
Services:
- LangSmith frontend UI
- LangSmith backend API
- LangSmith Platform backend
- LangSmith Playground
- LangSmith queue
- LangSmith ACE (Arbitrary Code Execution) backend
Storage services:
- ClickHouse (traces and feedback data)
- PostgreSQL (operational data)
- Redis (queuing and caching)
- Blob storage (optional, but recommended for production)
To access the LangSmith UI and send API requests, you will need to expose the LangSmith frontend service. Depending on your installation method, this can be a load balancer or a port exposed on the host machine.
| Service | Description |
|---|---|
| ClickHouse | ClickHouse is a high-performance, column-oriented SQL database management system (DBMS) for online analytical processing (OLAP). LangSmith uses ClickHouse as the primary data store for traces and feedback (high-volume data). 💡 Connect to external ClickHouse |
| PostgreSQL | PostgreSQL is a powerful, open source object-relational database system that uses and extends the SQL language combined with many features that safely store and scale the most complicated data workloads. LangSmith uses PostgreSQL as the primary data store for transactional workloads and operational data (almost everything besides traces and feedback). 💡 Connect to external PostgreSQL - AWS RDS, GCP Cloud SQL, Azure Database |
| Redis / Valkey | Redis is a powerful in-memory key-value database that persists on disk. By holding data in memory, Redis offers high performance for operations like caching. LangSmith uses Redis to back queuing and caching operations. Valkey is also officially supported as a drop-in replacement for Redis. 💡 Connect to external Redis or Valkey - AWS ElastiCache, GCP Memorystore, Azure Cache |
| Blob storage | LangSmith supports several blob storage providers, including AWS S3, Azure Blob Storage, and Google Cloud Storage. LangSmith uses blob storage to store large files, such as trace artifacts, feedback attachments, and other large data objects. Blob storage is optional, but highly recommended for production deployments. 💡 Enable blob storage - AWS S3, GCP GCS, Azure Blob |
To install, follow the Kubernetes setup guide.
LangSmith Deployment is an optional add-on that can be enabled on your LangSmith instance. It's ideal for enterprise teams who want a centralized, UI-driven platform to deploy and manage multiple agents and graphs, with all infrastructure, data, and orchestration fully under their control.
This includes everything from LangSmith, plus:
| Component | Responsibilities | Where it runs | Who manages it |
|---|---|---|---|
| Control plane |
|
Your cloud | You |
| Data plane |
|
Your cloud | You |
You run both the control plane and the data plane entirely within your own infrastructure. You are responsible for provisioning and managing all components.
Learn more about the [control plane](/langsmith/control-plane) and [data plane](/langsmith/data-plane) architecture concepts.If you want to self-host LangSmith for observability, evaluation, and agent deployment, follow these steps:
You must already have a [self-hosted LangSmith instance](#langsmith) installed in your cloud with a Kubernetes cluster (required for control plane and data plane). Use `langgraph-cli` or [Studio](/langsmith/studio) to test your graph locally. Follow the [setup guide](/langsmith/deploy-self-hosted-full-platform) to enable LangSmith Deployment on your LangSmith instance.The Standalone server option is the most lightweight and flexible way to run LangSmith. Unlike the other models, you only manage a simplified data plane made up of Agent Servers and their required backing services (PostgreSQL, Redis, etc.).
This includes:
| Component | Responsibilities | Where it runs | Who manages it |
|---|---|---|---|
| Control plane | n/a | n/a | n/a |
| Data plane |
|
Your cloud | You |
This option gives you full control over scaling, deployment, and CI/CD pipelines, while still allowing optional integration with LangSmith for tracing and evaluation.
Do not run standalone servers in serverless environments. Scale-to-zero may cause task loss and scaling up will not work reliably.- Define and test your graph locally using the
langgraph-clior Studio - Package your agent as a Docker image
- Deploy the Agent Server to your compute platform of choice (Kubernetes, Docker, VM)
- Optionally, configure LangSmith API keys and endpoints so the server reports traces and evaluations back to LangSmith (self-hosted or SaaS)
-
Kubernetes: Use the LangSmith Helm chart to run Agent Servers in a Kubernetes cluster. This is the recommended option for production-grade deployments.
-
Docker: Run in any Docker-supported compute platform (local dev machine, VM, ECS, etc.). This is best suited for development or small-scale workloads.





