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1Fix the driver behind crashes, sound loss and screen glitches2Repair Windows errors before they cause bigger problems3Scan for outdated or missing drivers - takes under a minuteUse Docker Compose when you need a quick local trial or a single virtual machine. Choose the Kubernetes Helm deployment when Langfuse must tolerate failures, handle higher throughput, or fit an existing production cluster. Langfuse documents Compose as the simplest starting point, but explicitly notes that the setup does not provide high availability, scaling capabilities, or backup functionality. Its Kubernetes documentation is aimed at high-availability and high-throughput installations.
The right choice therefore depends less on Langfuse features than on your operational requirements: how much telemetry you will retain, whether downtime is acceptable, who will operate databases and object storage, and whether your team already runs Kubernetes.
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Langfuse is an open-source LLM observability platform for collecting and inspecting traces, evaluating model behavior, managing prompts, organizing datasets, and accessing those functions through APIs. A self-hosted installation runs the web application and its supporting data services in infrastructure you control instead of sending platform data to Langfuse Cloud.
The SDKs and integrations work identically against Langfuse Cloud and a self-hosted instance, according to Langfuse’s Kubernetes Helm documentation. Your application code can therefore point at the self-hosted endpoint while the deployment team controls networking, storage, upgrades, retention, and access policies.
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There are two documented deployment paths:
- Docker Compose: a straightforward route for experimenting locally or running Langfuse on a VM.
- Kubernetes Helm: the route Langfuse recommends when you need higher availability or throughput.
These are not two editions of the product. They are different operating models with different resilience and maintenance expectations.
Docker Compose vs. Kubernetes Helm
| Decision factor | Docker Compose | Kubernetes Helm |
|---|---|---|
| Typical fit | Local trial or one VM; simplest documented way to get started. | Kubernetes environments and installations requiring higher availability or throughput. |
| Core prerequisites | Git, Docker, and Docker Compose. | Kubernetes and Helm. A chart-managed ClickHouse also needs the relevant operator and cert-manager resources. |
| Availability and scaling | Langfuse says the Compose setup lacks high availability and scaling capabilities. | Langfuse presents Kubernetes for high-availability and high-throughput deployments. |
| Backup responsibility | The documented Compose setup does not provide backup functionality; you must design and operate backups separately. | Backup, replication, and recovery still require an explicit plan for each stateful service and storage class. |
| Data services | The default stack includes MinIO for blob storage. | You can use bundled services or connect existing PostgreSQL, ClickHouse, Redis, and blob storage. |
| Best next action | Follow the current Compose guide, then adapt secrets, exposure, storage, and log rotation to your environment. | Validate chart, cluster, operator, and component versions before installing the current langfuse-k8s chart. |
How to deploy Langfuse with Docker Compose
1. Confirm the prerequisites
Install Git, Docker, and Docker Compose on the machine where the stack will run. For a local evaluation, that can be a developer workstation. For a remote installation, Langfuse’s example VM sizing is at least 4 CPU cores, 16 GiB of memory, and 100 GiB of storage. Those figures are recommendations for the guide’s example cloud VM, not universal minimums or a capacity formula. Actual requirements vary with trace volume, retention, evaluation workloads, database growth, and the number of users.
Before creating the VM, decide where persistent data will live and how it will be protected. A disposable disk is appropriate only for a throwaway test. A longer-lived installation needs persistent volumes, a retention policy, and a recovery plan for the databases and object storage.
2. Obtain the Compose deployment files
Use the current Langfuse Docker Compose deployment guide and its repository instructions rather than copying an old file from a blog post. Deployment files, environment variables, and service versions can change. Keep the files under version control, restrict access to them, and separate test and production configurations.
3. Change the secrets before starting the stack
The guide requires you to update the secrets in the Compose configuration before starting the containers. Treat every generated credential as production-sensitive: store it in a protected secret manager or an access-controlled environment file, avoid committing it to a public repository, and rotate it if the file is exposed.
Review the configuration for database credentials, encryption or signing secrets, object-storage credentials, and any URL or host values that will be visible outside the VM. Keep internal service addresses on the private container network wherever possible.
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4. Start the services and wait for readiness
Start the stack using the command specified in the current Compose guide. The web container should eventually report “Ready”. Do not treat a running container as proof that the installation is usable: the application also needs its dependent data services and correctly configured secrets.
If the web service never reaches “Ready,” inspect the container logs and verify, in order, that the environment file is being loaded, dependent services are reachable, persistent volumes are writable, and no required port is already occupied. Correct the configuration and restart the affected service rather than deleting data volumes indiscriminately.
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5. Open the UI and create the first account
The default Compose stack publishes the Langfuse UI on port 3000. Once the web container is ready, open the UI at the local or private address appropriate for your installation. There is no default login. The first person to use the interface signs up, then creates an organization and a project.
Plan the organization and project structure before instrumenting applications. Project boundaries affect who can view traces and how data is separated, so creating a temporary project and later moving production telemetry can create unnecessary cleanup work.
6. Restrict network exposure
The default stack also publishes MinIO on port 9090. Do not expose both ports broadly just because they are convenient defaults. Put the UI behind the reverse proxy, firewall, VPN, or identity-aware gateway used by your environment, and expose only the services that genuinely need external access. Keep MinIO on an internal network unless a documented administrative or application requirement calls for otherwise.
Use TLS at the externally accessible endpoint, limit administrative access, and record which ports are reachable from the public internet, corporate network, and application subnets. A firewall rule that permits port 3000 from everywhere can turn a test deployment into an unintended public service.
7. Plan maintenance before calling it production
Compose is easy to start but not self-maintaining. Langfuse’s guide calls out log rotation and disk-space management; follow the current operational instructions for both. Monitor container health, database and object-storage growth, filesystem usage, and certificate or proxy expiry.
The guide explicitly states that this setup lacks high availability, scaling capabilities, and backup functionality. If the VM fails, the service may be unavailable until you restore or rebuild it. Create and test backups for every stateful component, document restore steps, and decide how much telemetry loss and downtime the team can accept. If those requirements are unacceptable, move to the Kubernetes route or another architecture that provides the needed redundancy.
How to deploy Langfuse on Kubernetes with Helm
Cluster and Helm prerequisites
The current Helm documentation describes installation through the langfuse-k8s chart. New installations should use Kubernetes 1.28 or newer and Helm 3.17 or newer, subject to the versions supported by the live guide when you deploy.
If the chart deploys ClickHouse for you, the cluster must already contain the required ClickHouse operator and cert-manager custom-resource definitions. Those prerequisites are not needed when ClickHouse is fully external. In either case, verify that your cluster permits the required CRDs, storage classes, ingress configuration, and workload security settings.
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Version guidance for new Langfuse v4 setups
| Component | Documented guidance | Qualification |
|---|---|---|
| Kubernetes | 1.28 or newer | Minimum listed by the current Helm guide. |
| Helm | 3.17 or newer | Minimum listed by the current Helm guide. |
| ClickHouse | 25.12 minimum; 26.4 recommended | Guidance for new Langfuse v4 setups. |
| PostgreSQL | 16 recommended | Guidance for new Langfuse v4 setups. |
| Redis | 7.2 recommended | Guidance for new Langfuse v4 setups. |
These are version-specific compatibility and recommendation details, not permanent requirements. Check the current chart documentation and release notes immediately before installation, especially when upgrading an existing cluster.
Choose bundled or external data services
The chart can connect to existing PostgreSQL, ClickHouse, Redis, and blob storage. External services are useful when your organization already operates managed databases, has centralized backup and monitoring, or needs independent scaling and maintenance windows.
For production blob storage, the Helm guide recommends managed services such as Amazon S3, Google Cloud Storage, or Azure Blob Storage instead of bundled SeaweedFS. A managed service can reduce the operational burden of replication, durability, and capacity planning, but it still requires correct credentials, network paths, lifecycle rules, and access controls.
If you enable bundled ClickHouse, install and validate the operator and cert-manager resources before the Langfuse release. If you use an external ClickHouse, remove the operator dependency from your plan and validate the endpoint, TLS settings, credentials, and database permissions independently.
Install and validate the chart
- Confirm the cluster and Helm versions against the current support matrix.
- Choose a namespace and apply the required secrets through your organization’s approved secret-management process.
- Decide whether PostgreSQL, ClickHouse, Redis, and blob storage are bundled or external.
- If ClickHouse is bundled, install the required operator and cert-manager CRDs and verify that they are healthy.
- Configure the
langfuse-k8schart values for ingress, persistence, credentials, and selected data services. - Install the chart using the current Helm guide, then verify pod readiness, persistent-volume claims, ingress routing, and application logs.
- Open the UI, create the initial account, organization, and project, and send a controlled test trace before connecting production applications.
Keep chart values in version control without committing plaintext credentials. Use separate values files or release configurations for development, staging, and production, and record the chart and component versions that were actually deployed.
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Storage, retention, and capacity planning
The Compose example’s 100 GiB storage recommendation is a starting point for the documented VM scenario, not a prediction of how much your telemetry will consume. Storage demand depends on event volume, payload size, retention period, evaluations, prompt and dataset content, database indexes, and object attachments.
Estimate capacity from your own expected daily trace volume, then leave headroom for indexes, temporary files, upgrades, and recovery operations. Set retention and lifecycle rules before ingestion begins. Monitor both database filesystems and blob storage; a healthy application can still fail when either reaches its disk limit.
For Kubernetes, decide which team owns each stateful service. If a platform team operates PostgreSQL, ClickHouse, Redis, and object storage centrally, using those external services can simplify Langfuse upgrades. If the application team owns the entire namespace, bundled components may be faster to deploy but require stronger runbooks for upgrades, backups, replication, and incident recovery.
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Security and operational checks
- Replace every sample secret before the first startup.
- Keep MinIO and databases private unless an explicit integration requires exposure.
- Terminate TLS at a managed ingress or reverse proxy and restrict administrative routes.
- Use least-privilege credentials for PostgreSQL, ClickHouse, Redis, and blob storage.
- Configure log rotation and alert on disk consumption.
- Back up stateful data and perform a restore test; a backup that has never been restored is not a recovery plan.
- Record Langfuse, chart, database, and Kubernetes versions for each environment.
- Recheck the live deployment documentation before upgrades because supported versions and feature boundaries can change.
Cost and licensing
Langfuse’s self-hosted pricing page describes the Open Source option as free for core platform features, including observability, evaluation, prompt management, datasets, and APIs. “Free” does not mean zero operating cost: you still pay for compute, storage, backups, networking, monitoring, and engineering time.
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Troubleshooting by symptom
The UI is unreachable
For Compose, verify that the web container reached “Ready,” port 3000 is listening on the intended interface, and the firewall or reverse proxy forwards to the correct host. For Kubernetes, check ingress routing, service endpoints, pod readiness, and the namespace’s network policies.
The application starts but cannot write data
Check database and object-storage credentials, DNS resolution, TLS trust, and write permissions on persistent volumes. A MinIO endpoint that is reachable from a browser but not from the application network is a routing or policy problem, not an account-creation problem.
A Helm installation is rejected before workloads start
Compare Kubernetes and Helm versions with the documented minimums. If ClickHouse is bundled, verify that the operator and cert-manager CRDs exist and are ready. If all data services are external, remove unnecessary operator dependencies and test each external endpoint from the cluster.
Disk usage keeps rising
Measure database files, blob objects, container logs, and temporary volumes separately. Apply the documented log-rotation and disk-management procedures, then set retention and object-lifecycle policies that match your observability requirements. Do not delete database or blob files manually while services are running.
A practical decision checklist
Choose Compose when all of the following are true:
- You are testing Langfuse locally or on one VM.
- Short outages are acceptable.
- You can provide persistent storage and handle backups yourself.
- Your expected workload does not require horizontal scaling.
Choose Kubernetes Helm when one or more of these conditions applies:
- High availability or higher throughput is a stated requirement.
- Your organization already operates Kubernetes and managed data services.
- You need independent scaling, rolling updates, or standardized ingress and secret management.
- You require a documented recovery design rather than a single-server restart procedure.
A common progression is to begin with Compose for instrumentation and workflow validation, then move to Helm after telemetry volume, retention, access controls, and recovery objectives are known. Treat that move as a data migration and architecture project: preserve the required databases and blob objects, test SDK endpoints against the new instance, and switch applications only after a controlled validation trace succeeds.
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