← Back home · Compare
blogus vs Langfuse
LLM tracing, evals, and prompt management
Langfuse and blogus solve adjacent problems. Langfuse watches what happens in production; blogus makes sure what shipped to production matches what was reviewed. They compose; they do not replace each other.
| Feature | blogus | Langfuse | Advantage |
|---|---|---|---|
| Primary concern | Build-time prompt versioning + lock | Run-time tracing + evaluation | Comparable |
| Where it runs | CLI / pre-commit / CI | Application runtime + hosted (or self-hosted) backend | Comparable |
| Source of truth | .prompt files in your repo | Hosted or self-hosted Langfuse store | blogus |
| CI gate for prompt drift | blogus verify (single exit code) | Not the design centre | blogus |
| Production observability | Out of scope by design | Core feature | Langfuse |
| Evaluation tooling | blogus analyze + blogus test (basic) | Datasets, scorers, human review | Langfuse |
| Self-host complexity | No server to run | Postgres + ClickHouse stack | blogus |
| Open source license | MIT | MIT (core) | Comparable |
| Best used with the other | Lock-in-repo + observe-in-prod | Observe-in-prod + lock-in-repo | Comparable |
| Adoption cost | One CLI, two minutes | Stack to stand up, SDK to integrate | blogus |
Pick blogus when
- ▸You want a build-time guarantee that prompts in production match prompts in git
- ▸You want prompt changes to fail CI loudly when the lock is stale
- ▸You are not yet running an observability stack and want the smallest possible first step
- ▸You want the prompts directory itself, not a hosted abstraction, to be the artifact reviewers approve
- ▸Your team already has a strong PR-based review culture and you want prompt changes to fit into it
Pick Langfuse when
- ▸You need production tracing of LLM calls — latency, cost, errors, token counts
- ▸You want an evaluation harness with scoring, datasets, and human review baked in
- ▸You need to attribute prompt performance to versions in production traffic
- ▸You want a dashboard for prompt experimentation independent of a code deploy
They can compose.
Most teams that adopt blogus keep their existing observability and eval stack. Langfuse answers a question blogus does not try to. Pick what fits each layer.