Lunary vs Traceloop
Compare Lunary and Traceloop for OpenTelemetry tracing, conversation review, feedback and prompt workflows, including Traceloop’s ServiceNow transition.
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Lunary is our recommendation when the application team needs customer conversations and agent traces in the same quality-review process.
Lunary fit
Review messages, feedback and the execution behind them.
Traceloop fit
OpenLLMetry tracing, quality monitors and staged prompts.
Keep instrumentation portable
Verify trace mappings before changing destinations.
At a glance
| Workflow | Lunary | Traceloop |
|---|---|---|
| Conversation context | Messages, events and linked agent runs | Sessions grouping multi-turn traces |
| Feedback integration | Message or run IDs with feedback data | Annotation tasks, entities and tags |
| Prompt iteration | Templates, shared drafts and playground | Prompt registry and staged deployments |
| Quality assessment | Model and prompt evaluations | Dataset experiments and span monitors |
See your workflow in Lunary.
Explore conversations, traces and prompt versions with our team.
Make a trace understandable to the team
Lunary reconciles messages with agent and LLM runs, and captures custom events and feedback. Traceloop also supports conversation sessions. Compare both with the same multi-turn issue and the people who actually review customer complaints.
Compare the integration your app needs
Lunary records feedback against a message or run. Traceloop documents annotation tasks with entities and tags, submitted through Python or TypeScript. Test the path from an in-app reaction to a reviewer finding the affected interaction.
Review the next version before rollout
Lunary provides shared drafts and a playground for model or custom-endpoint testing. Traceloop’s registry supports draft prompts and staged environment deployment. Pick the review and release process your team can apply consistently.
Questions & answers
What changed with ServiceNow?
Traceloop announced in March 2026 that it is joining ServiceNow. It stated an intention to continue selling its functionality and keep OpenLLMetry open source.
Does Lunary accept existing OTel traces?
Yes. Validate attribute mappings, trace relationships and conversation metadata with a representative sample before switching.
What makes Lunary worth a pilot?
The combination of conversation replay, message feedback and shared prompt drafts gives an assistant team a concrete workflow to assess.
By Lunary · Documentation reviewed Sep 20, 2026
Sources & methodology (12)
Based on vendor documentation, not an independent benchmark or hands-on rating. Features and plans can change.
Bring your next AI issue to Lunary.
Follow the conversation. Find the cause. Test the fix.
$20 per user / month. Payment required to activate your workspace.