production-observability
Skill344 starsChanged 3 months agoMITView on GitHub
Use when adding service-wide Spring Boot 3 Actuator, Micrometer metrics, distributed tracing, OpenTelemetry export, structured logging, health probes, dashboards, or alerts. Combine with ai-observability only for Spring AI-specific token, prompt, and model telemetry.
2 other projects use a version of this.
Adopted by
Most recently taken up by
- mateonunez/skillstheir own version, first seen Jul 21, 2026
- carmentacollective/carmentatheir own version, first seen Jan 22, 2026
Other versions2 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 2
- mateonunez/skills★ 8same name
- carmentacollective/carmenta★ 2same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository77 other files it gives its agents.
- agent-qa-browser-regressionSkill
- ai-observabilitySkill
- api-versioningSkill
- configuration-propertiesSkill
- container-native-deploymentSkill
- domain-driven-designSkill
- event-driven-messagingSkill
- flyway-migrationsSkill
- hateoasSkill
- hexagonal-architectureSkill
- http-interface-clientsSkill
- idempotency-patternsSkill
- java-supply-chain-securitySkill
- layered-architectureSkill
- mcp-serverSkill
- multi-module-mavenSkill
- multi-tenancySkill
- null-safetySkill
- oauth2-resource-serverSkill
- openapi-firstSkill
- problem-details-rfc9457Skill
- resilience-retrySkill
- rest-api-conventionsSkill
- security-audit-loggingSkill
- spring-ai-integrationSkill
- spring-ai-securitySkill
- spring-batchSkill
- spring-boot-migrationSkill
- spring-cloud-gatewaySkill
- spring-data-jpaSkill
- spring-data-redisSkill
- spring-incident-responseSkill
- spring-modulithSkill
- spring-security-jwtSkill
- spring-security-reviewSkill
- testing-pyramidSkill
- transactional-patternsSkill
- webflux-reactive-patternsSkill
- agent-qa-browser-regressionSkill
- ai-observabilitySkill
- api-versioningSkill
- configuration-propertiesSkill
- container-native-deploymentSkill
- domain-driven-designSkill
- event-driven-messagingSkill
- flyway-migrationsSkill
- hateoasSkill
- hexagonal-architectureSkill
- http-interface-clientsSkill
- idempotency-patternsSkill
- java-supply-chain-securitySkill
- layered-architectureSkill
- mcp-serverSkill
- multi-module-mavenSkill
- multi-tenancySkill
- null-safetySkill
- oauth2-resource-serverSkill
- openapi-firstSkill
- problem-details-rfc9457Skill
- production-observabilitySkill
- The first 60 shown.
The file
We split this skill into the rules it gives an agent
8 rules. About 0 are common, 8 are distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈8
Distinctive · estimate
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 15
Add Actuator and one metrics registry selected by the deployment platform.
- Distinctive: line 16
Use Micrometer Observation for application metrics and traces.
- Distinctive: line 17
Use Micrometer Tracing with the chosen bridge.
- Distinctive: line 24
Keep metric tags low-cardinality: method, outcome, region, or bounded status.
- Distinctive: line 25
Put request IDs, user IDs, order IDs, and exception messages only in traces or logs.
- Distinctive: line 31
Keep liveness independent from remote systems so a dependency outage does not restart every pod.
- Distinctive: line 32
Put required dependencies in readiness groups.
- Distinctive: line 33
Write custom health indicators only for dependencies that affect traffic acceptance.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Production Observability
Instrument user-visible operations and operational boundaries, not every method.
Baseline
- Add Actuator and one metrics registry selected by the deployment platform.
- Use Micrometer Observation for application metrics and traces.
- Use Micrometer Tracing with the chosen bridge; do not mix tracing APIs throughout business code.
- Export through OTLP when the platform standardizes on OpenTelemetry collectors.
- Expose only required actuator endpoints and secure every non-public endpoint.
Observation conventions
- Name observations by stable operation, such as
orders.create. - Keep metric tags low-cardinality: method, outcome, region, or bounded status.
- Put request IDs, user IDs, order IDs, and exception messages only in traces or logs.
- Propagate context across
@Async, executor, and Reactor boundaries. - Record latency, throughput, failures, and saturation for every external dependency.
Health and readiness
- Keep liveness independent from remote systems so a dependency outage does not restart every pod.
- Put required dependencies in readiness groups.
- Write custom health indicators only for dependencies that affect traffic acceptance.
- Set explicit timeouts on health checks.
Logging and alerts
- Emit structured logs with trace and span correlation.
- Redact credentials, tokens, personal data, prompts, and payloads by default.
- Alert on symptoms tied to service objectives, not raw metric noise.
- Include runbook links and enough dimensions to identify the affected service and dependency.
Examples
- See
examples/good-observation.javaandexamples/bad-observation.java.
Gotchas
- Agent tags metrics with user or entity IDs - this creates unbounded cardinality.
- Agent exposes every actuator endpoint publicly - expose the minimum and secure it.
- Agent makes liveness depend on the database - dependency outages then cause restart loops.
- Agent logs request bodies and tokens for debugging - redact sensitive data before emission.
- Agent creates spans but loses context in async work - configure context propagation explicitly.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
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Your trail
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Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

