Managed Langfuse Hosting — production-ready from $15 a month
LLM observability, tracing, and analytics. Deployed on your own dedicated instance in AWS, Azure, or GCP, kept patched, backed up, and monitored by ManageStacks — standard Langfuse, no lock-in.
Langfuse is an open-source LLM engineering platform for tracing, evaluating, and monitoring AI applications. ManageStacks deploys Langfuse with persistent storage, automated backups, and pre-configured dashboards.
What does Langfuse do, and why do teams deploy it?
Langfuse is an open-source observability and analytics platform purpose-built for LLM applications. It provides end-to-end tracing of LLM calls, prompt management, evaluation pipelines, and cost tracking across your AI stack. Langfuse integrates with LangChain, LlamaIndex, OpenAI SDK, and other popular frameworks.
With Langfuse, engineering teams gain visibility into latency, token usage, cost, and quality metrics for every LLM interaction. Its prompt management system enables version-controlled prompt iteration, and its evaluation framework supports both automated scoring and human review workflows.
- End-to-end tracing for LLM chains and agents
- Prompt management with version control
- Cost and latency analytics per model and feature
- Evaluation framework with custom scoring functions
- Integration with LangChain, LlamaIndex, and OpenAI
- Dataset management for testing and benchmarking
LLM observability, tracing, and analytics
What does managed Langfuse hosting cost?
Flat per-app pricing, in your chosen AWS, Azure, or GCP region. No per-user pricing — a busy deployment costs the same as a quiet one.
Starter
Staging and internal tools. Dedicated instance, TLS, daily backups, managed upgrades.
Standard
Production workloads. Adds monitoring, staging environment, region choice, priority support.
Business
High-traffic and compliance workloads. Adds a high-availability replica and same-day support.
24×7 SRE retainer
Round-the-clock on-call across every hosted application, for teams that need a pager answered at 3am.
Self-hosting Langfuse vs managed — what does it really cost?
The software is free. The engineer-hours are not.
Running it yourself
- Instrument LLM calls with print statements or custom logging; lose traces when pods recycle
- Build per-provider cost tracking with spreadsheets and API billing dashboards
- Version prompts in Git with no runtime swap or A/B testing capability
- Write custom evaluation scripts for every new LLM feature and run them ad-hoc
- Correlate latency regressions across LLM chains manually from scattered logs
On ManageStacks
- Subscribe through your AWS, Azure, or GCP marketplace
- Langfuse deploys with PostgreSQL, Redis, and automated SSL — traces flow in via SDK or OpenTelemetry
- Prompt management with version control and runtime deployment baked in
- Evaluation pipelines with custom scoring, human review, and dataset benchmarks ready out of the box
- Cost, latency, and quality dashboards per model, feature, and user segment — no spreadsheet needed
Langfuse on ManageStacks vs the alternatives
How Langfuse on ManageStacks compares to the leading LLM observability platforms.
| Langfuse on ManageStacksUs | LangSmith | Helicone | Datadog LLM Observability | |
|---|---|---|---|---|
| Deployment | Managed on your AWS, Azure, or GCP | Vendor-hosted | Vendor-hosted or self-hosted | Vendor-hosted |
| Data residency | Your cloud region | Vendor infrastructure | Vendor or your infra | Vendor infrastructure |
| Pricing basis | Flat $29/mo per instance | Per seat + per trace tier | Per log event tier | Per host + per span |
| Prompt management | Built-in with versioning | Prompt playground | No (proxy-focused) | No |
| Open source | Yes (MIT) | No (proprietary) | Yes (Apache 2.0) | No (proprietary) |
| Eval framework | Built-in with custom scorers | Online evals + datasets | Limited (request-level analytics) | Partial (trace-level) |
Provisioning, upgrades, backups and monitoring on your team’s plate.
What does running Langfuse yourself involve?
ManageStacks deploys Langfuse with PostgreSQL, Redis, and automated SSL so you get full LLM observability without managing infrastructure. Focus on improving your AI application quality while we handle uptime and backups.
Langfuse key numbers
How long from subscribing to a live instance?
Subscribe
Subscribe to ManageStacks through your AWS, Azure, or GCP marketplace.
Provision
Langfuse spins up with PostgreSQL, Redis, and automated SSL — typically under 4 minutes.
Instrument
Add the Langfuse Python or JS SDK to your application, or route via LiteLLM/LangChain native integration. Traces start appearing immediately.
Iterate
Use prompt management for versioned rollouts, build evaluation datasets, and set up cost alerts per team or feature.
When is self-hosting Langfuse the right answer instead?
“Managed hosting is not always the correct call.”
Self-host when a platform team already runs the infrastructure and on-call rotation to operate Langfuse at genuinely low marginal cost. Self-host when compliance requires an air-gapped or on-premises deployment that no hosted option can satisfy. And self-host when the deployment depends on heavy customisation with a fast internal build-deploy loop, because an internal release process will beat any managed change process.
For everyone else — teams whose engineers have better things to do than shepherd upgrades — managed hosting is cheaper than the hours it replaces.
Which cloud should Langfuse run on — AWS, Azure or GCP?
For most workloads, the choice of cloud matters less than proximity: run Langfuse in the same cloud and region as the applications and data it talks to, because every request between them adds a round trip. The underlying compute performs equivalently across AWS, Azure, and GCP.
In practice, an existing cloud footprint decides it. All plans support all three clouds, and moving regions later is a scheduled migration, not a rebuild.
Deepest managed-service catalog, default when there's no existing footprint
Best fit for teams already on Microsoft 365 or Entra ID
Strongest for data/analytics-adjacent workloads
Every plan supports AWS, Azure, and GCP — region choice included.
Common questions about Langfuse on ManageStacks
What LLM frameworks does Langfuse on ManageStacks integrate with?
Langfuse integrates with LangChain, LlamaIndex, OpenAI SDK, LiteLLM, and Vercel AI SDK via native integrations. Any other framework can send traces using the Langfuse REST API or Python/JS SDKs.
Can I use Langfuse for prompt versioning on ManageStacks?
Yes. Langfuse includes a prompt management system where you can store, version, and deploy prompts. Your application pulls the active prompt version at runtime, enabling A/B testing and rollback.
How does ManageStacks handle Langfuse trace data retention?
ManageStacks provisions Langfuse with a PostgreSQL database and configurable retention policies. Automated daily backups ensure your trace data and evaluation results are protected.
Run Langfuse without carrying the pager
Subscribe through your AWS, Azure, or GCP marketplace. We handle provisioning, SSL, monitoring, backups, updates, and security. From $15/mo.