How do I know if Langfuse is down?

Check Langfuse status by: 1) Visiting Langfuse's official status page for active incidents on Langfuse Cloud, 2) Testing a request against the Langfuse ingestion API with your public/secret key pair, 3) Checking whether traces are queuing locally in your SDK but failing to appear in the dashboard, or 4) Using API Status Check for real-time endpoint monitoring.

What should I do when Langfuse is down?

When Langfuse is unresponsive, your application traffic should keep working since the official SDKs batch and send traces asynchronously in the background rather than blocking your LLM calls. Check the status page, verify your API keys, and consider self-hosting Langfuse if you need guaranteed control over ingestion uptime.

How long do Langfuse outages usually last?

Trace ingestion delays typically clear within 10-20 minutes as backpressure resolves on Langfuse Cloud. Dashboard or evaluation outages tied to broader infrastructure incidents can take longer, though core LLM calls in your application are unaffected since tracing is decoupled from execution.

What are the best alternatives to Langfuse if it's down?

The best Langfuse alternatives for LLM observability include LangSmith (LangChain's managed tracing and evals platform), Helicone (simple proxy-based logging), Arize Phoenix (open-source tracing and evals), and Weights & Biases Weave (broader ML experiment tracking with LLM support).

Is Langfuse Down? How to Check Langfuse Status in 2026

Q: Why does Langfuse go down?

Langfuse disruptions are typically caused by trace ingestion backpressure during high-volume logging spikes, evaluation job queue backlogs, database or ClickHouse storage-layer issues, or underlying cloud infrastructure incidents affecting the hosted Langfuse Cloud offering.

Langfuse is an open-source LLM engineering platform for tracing, evaluating, and managing prompts across LLM applications — used by teams building agents and RAG pipelines who want observability with the option to self-host. Like other tracing tools, Langfuse sits alongside your application rather than in the critical execution path, which changes what a "Langfuse is down" incident actually means for your users.

Whether you're seeing missing traces in the Langfuse Cloud dashboard, stalled evaluation runs, or errors submitting scores, this guide answers the key question: is Langfuse down for everyone, and is your production LLM traffic actually affected?

How to Check if Langfuse is Down (Fastest Methods)

1. Check the Official Langfuse Status Page

Langfuse publishes a status page covering trace ingestion, the evaluation service, and the Langfuse Cloud dashboard UI. Check it first for any active incidents before digging into your own integration.

2. Test the Langfuse Ingestion API Directly

A quick API test isolates whether the issue is on Langfuse's end or your integration:

curl https://cloud.langfuse.com/api/public/health \
  -u "$LANGFUSE_PUBLIC_KEY:$LANGFUSE_SECRET_KEY" \
  -o /dev/null -w "%{http_code}"

A 200 response means Langfuse Cloud is reachable. A 401 means your API keys are invalid. A 5xx or connection timeout means Langfuse is experiencing an outage.

3. Confirm Your Application Isn't Actually Broken

This is the most important step for Langfuse specifically: the official SDKs batch and submit traces asynchronously in the background, and are designed to fail silently rather than block or crash your LLM calls. If Langfuse is down, your chatbot or agent should keep responding to users — only the tracing and evaluation layer is affected.

4. Check Local SDK Flush Warnings

Review your application logs for Langfuse client warnings about failed batch flushes or a growing local event queue. This confirms the tracing pipeline is degraded without you needing to speculate about the cause.

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Why Does Langfuse Go Down?

Langfuse's role as a high-volume telemetry sink for LLM applications creates its own set of failure modes:

Trace Ingestion Backpressure: Teams running high-throughput agents can generate large volumes of nested trace spans. Sudden spikes in trace volume can overwhelm ingestion capacity faster than autoscaling responds.
Evaluation Job Queue Backlogs: Running LLM-as-judge or custom evaluations against large datasets queues significant compute. Backlogs during peak usage can delay eval results without affecting live tracing.
Database / ClickHouse Storage Issues: Langfuse Cloud stores traces and analytics in a database layer that can experience its own incidents independent of the ingestion API.
Dashboard-Only Degradation: The web UI and the ingestion API are separate services. It's possible for traces to be ingesting normally while the dashboard itself is slow or erroring.
Underlying Cloud Provider Issues: As a hosted SaaS platform, Langfuse Cloud runs on cloud infrastructure that can experience regional incidents affecting latency or availability.

Langfuse Troubleshooting Checklist

Step 1: Identify the Error Type

HTTP 401 — Public/secret key pair invalid or expired. Regenerate them in your Langfuse project settings.
HTTP 429 — Rate limit exceeded on trace ingestion. Check your plan's event volume limits.
HTTP 5xx / timeout — Platform-level outage. Check the Langfuse status page.
Traces missing but no SDK errors — Possible dashboard-only degradation; ingestion may still be processing with delay.
Evaluation runs stuck "pending" — Compute queue backlog, typically resolves without action.

Step 2: Confirm Production Traffic Is Unaffected

Since tracing is decoupled from execution in the official SDKs, verify your chatbot, agent, or RAG pipeline is still serving real responses before treating a Langfuse outage as user-facing.

Step 3: Consider Self-Hosting for Guaranteed Uptime

Because Langfuse is open-source, teams with strict uptime requirements can self-host it on their own infrastructure rather than depending on Langfuse Cloud's availability.

Step 4: Set Up Independent Monitoring

Don't rely solely on Langfuse's own status page — monitor the API endpoint directly so you know about ingestion failures even if the status page hasn't updated yet.

Best Langfuse Alternatives When It's Down

LangSmith

LangChain's managed tracing and evaluation platform for LLM applications.

Helicone

Lightweight proxy-based logging for LLM calls, minimal integration overhead.

Arize Phoenix

Open-source tracing and evaluation toolkit with strong OpenTelemetry support.

Weights & Biases Weave

LLM tracing built on W&B's established experiment tracking infrastructure.

Conclusion: Tracing Should Never Take Down Your LLM App

Langfuse gives teams observability they can't get otherwise, but it's built to fail safely — a Langfuse outage should degrade your observability, not your product. Teams that verify this decoupling and monitor the ingestion endpoint independently spot real incidents faster and avoid false alarms.

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