181-java-observability-logging
Use when you need to implement or improve Java logging and observability — including selecting SLF4J with Logback/Log4j2, applying proper log levels (ERROR, WARN, INFO, DEBUG, TRACE), parameterized logging, correlation context, secure logging without sensitive data exposure, environment-specific configuration, log aggregation, monitoring, and alerting. This should trigger for requests such as Improve logging; Apply logging; Refactor logging; Add logging support; Review SLF4J structured logging in Java code. Part of Plinth Toolkit
Works with
--- name: 181-java-observability-logging description: Use when you need to implement or improve Java logging and observability — including selecting SLF4J with Logback/Log4j2, applying proper log levels (ERROR, WARN, INFO, DEBUG, TRACE), parameterized logging, correlation context, secure logging without sensitive data exposure, environment-specific configuration, log aggregation, monitoring, and alerting. This should trigger for requests such as Improve logging; Apply logging; Refactor logging; Add logging support; Review SLF4J structured logging in Java code. Part of Plinth Toolkit license: Apache-2.0 --- # Java Logging Best Practices Implement effective Java logging following standardized frameworks, meaningful log levels, core practices (parameterized logging, exception handling, no sensitive data), explicit correlation context, flexible configuration, security-conscious logging, monitoring, and alerting. **What is covered in this Skill?** - Standardized framework selection: SLF4J facade with Logback or Log4j2 - Meaningful and consistent log levels: ERROR, WARN, INFO, DEBUG, TRACE - Core practices: parameterized logging, proper exception handling, avoiding sensitive data - Configuration: environment-specific (logback.xml, log4j2.xml), output formats, log rotation - Security: mask sensitive data, control log access, secure transmission, GDPR/HIPAA compliance - Log monitoring and alerting: centralized aggregation (ELK, Splunk, Loki), automated alerts **Scope:** The reference is organized by examples (good/bad code patterns) for each core area. Apply recommendations based on applicable examples. ## Constraints Before applying any logging recommendations, ensure the project compiles. Compilation failure is a blocking condition. After applying improvements, run full verification. - **MANDATORY**: Run `./mvnw compile` or `mvn compile` before applying any change - **SAFETY**: If compilation fails, stop immediately — do not proceed until resolved - **VERIFY**: Run `./mvnw clean verify` or `mvn clean verify` after applying improvements - **BEFORE APPLYING**: Read the reference for detailed good/bad examples, constraints, and safeguards for each logging pattern ## When to use this skill - Improve logging - Apply logging - Refactor logging - Add logging support - Review SLF4J structured logging in Java code ## Workflow 1. **Compile project before logging changes** Run `./mvnw compile` or `mvn compile` and stop immediately if compilation fails. 2. **Read logging reference and assess current observability** Read `references/181-java-observability-logging.md` and evaluate framework usage, log levels, sensitive-data handling, and config gaps. 3. **Apply logging and observability improvements** Implement selected framework/configuration/practice changes, including secure logging and monitoring integration where applicable. 4. **Verify with full build** Run `./mvnw clean verify` or `mvn clean verify` after applying improvements. ## Reference For detailed guidance, examples, and constraints, see [references/181-java-observability-logging.md](references/181-java-observability-logging.md).
More Observability skills
google-agents-cli-observability
google/agents-cli
>
azure-observability
microsoft/azure-skills
Azure Observability Services including Azure Monitor, Application Insights, Log Analytics, Alerts, and Workbooks. Provides metrics, APM, distributed tracing, KQL queries, and interactive reports. USE FOR: Azure Monitor, Application Insights, Log Analytics, Alerts, Workbooks, metrics, APM, distributed tracing, KQL queries, interactive reports, observability, monitoring dashboards. DO NOT USE FOR: instrumenting apps with App Insights SDK (use appinsights-instrumentation), querying Kusto/ADX clusters (use azure-kusto), cost analysis (use azure-cost-optimization).
workers-best-practices
cloudflare/skills
Reviews and authors Cloudflare Workers code against production best practices. Load when writing new Workers, reviewing Worker code, configuring wrangler.jsonc, or checking for common Workers anti-patterns (streaming, floating promises, global state, secrets, bindings, observability). Biases towards retrieval from Cloudflare docs over pre-trained knowledge.

