LLM observability for your platform
Standardize AI tracing with Lunary’s SDKs, OpenTelemetry ingestion and self-hosting options.
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Give application teams consistent traces while keeping deployment and data controls explicit.
Standardize
Agree on task IDs, operation names, environment and release.
Operate
Monitor ingestion and validate backup and upgrade procedures.
Roll out
Start with one application and a known failure case.
At a glance
| Platform responsibility | Acceptance evidence |
|---|---|
| Instrumentation contract | Consistent IDs, environment, release, and parent relationships |
| Data handling | Approved transformation tested on realistic payloads |
| Telemetry reliability | Known behavior during failure, retry, and shutdown |
| Deployment | A demonstrated restore and documented upgrade path |
| Adoption | An application team resolves a real incident |
Set a shared trace contract
Use SDK instrumentation or OpenTelemetry ingestion with consistent parent relationships and metadata. Verify the mapping across services and workers.
Control what gets recorded
Define the payload fields needed for debugging and transform them before transmission. Test nested inputs and outputs so redaction retains useful context.
Validate the deployment
Lunary publishes self-hosting guidance. Confirm edition requirements, restore a backup and test ingestion during network failures and runtime shutdown.
Questions & answers
Does OpenTelemetry remove all integration work?
No. Validate attribute mapping, context propagation and application-specific fields.
Does self-hosting satisfy every security requirement?
No. Controls depend on your configuration, access policies and operating procedures.
By Lunary · Documentation reviewed Sep 16, 2026
Sources & methodology (5)
Based on vendor documentation, not an independent benchmark or hands-on rating. Features and plans can change.
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Trace, evaluate, and improve your AI applications.
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