Search Results for "observability"
ln-627-observability-auditor
★ 25Observability audit worker (L3). Checks structured logging, health check endpoints, metrics collection, request tracing, log levels. Returns findings with severity, location, effort, recommendations.
ln-620-codebase-auditor
★ 25Coordinates 9 specialized audit workers (security, build, architecture, code quality, dependencies, dead code, observability, concurrency, lifecycle). Researches best practices, delegates parallel audits, aggregates results into single Linear task in Epic 0.
performance-monitor
★ 21Expert performance monitor specializing in system-wide metrics collection, analysis, and optimization. Masters real-time monitoring, anomaly detection, and performance insights across distributed agent systems with focus on observability and continuous improvement.
infrastructure-monitor
★ 19Set up monitoring, logging, and alerting for infrastructure and applications. Use when implementing observability, creating dashboards, or configuring alerts.
kafka-observability
★ 17Kafka monitoring and observability expert. Guides Prometheus + Grafana setup, JMX metrics, alerting rules, and dashboard configuration. Activates for kafka monitoring, prometheus, grafana, kafka metrics, jmx exporter, kafka observability, monitoring setup, kafka dashboards, alerting, kafka performance monitoring, metrics collection.
grey-haven-observability-engineering
★ 15Production-ready monitoring, logging, and tracing using Prometheus, Grafana, OpenTelemetry, DataDog, and Sentry. Use when setting up production monitoring, implementing SLOs, distributed tracing, or performance tracking.
grey-haven-observability-monitoring
★ 15Implement observability and monitoring using Cloudflare Workers Analytics, wrangler tail for logs, and health checks. Use when setting up monitoring, implementing logging, configuring alerts, or debugging production issues.
cicd-optimization
★ 15Comprehensive CI/CD pipeline methodology with quality gates, release automation, smoke testing, observability, and performance tracking. Use when setting up CI/CD from scratch, build time over 5 minutes, no automated quality gates, manual release process, lack of pipeline observability, or broken releases reaching production. Provides 5 quality gate categories (coverage threshold 75-80%, lint blocking, CHANGELOG validation, build verification, test pass rate), release automation with conventional commits and automatic CHANGELOG generation, 25 smoke tests across execution/consistency/structure categories, CI observability with metrics tracking and regression detection, performance optimization including native-only testing for Go cross-compilation. Validated in meta-cc with 91.7% pattern validation rate (11/12 patterns), 2.5-3.5x estimated speedup, GitHub Actions native with 70-80% transferability to GitLab CI and Jenkins.
methodology-bootstrapping
★ 15Apply Bootstrapped AI Methodology Engineering (BAIME) to develop project-specific methodologies through systematic Observe-Codify-Automate cycles with dual-layer value functions (instance quality + methodology quality). Use when creating testing strategies, CI/CD pipelines, error handling patterns, observability systems, or any reusable development methodology. Provides structured framework with convergence criteria, agent coordination, and empirical validation. Validated in 8 experiments with 100% success rate, 4.9 avg iterations, 10-50x speedup vs ad-hoc. Works for testing, CI/CD, error recovery, dependency management, documentation systems, knowledge transfer, technical debt, cross-cutting concerns.
observability-instrumentation
★ 15Comprehensive observability methodology implementing three pillars (logs, metrics, traces) with structured logging using Go slog, Prometheus-style metrics, and distributed tracing patterns. Use when adding observability from scratch, logs unstructured or inadequate, no metrics collection, debugging production issues difficult, or need performance monitoring. Provides structured logging patterns (contextual logging, log levels DEBUG/INFO/WARN/ERROR, request ID propagation), metrics instrumentation (counter/gauge/histogram patterns, Prometheus exposition), tracing setup (span creation, context propagation, sampling strategies), and Go slog best practices (JSON formatting, attribute management, handler configuration). Validated in meta-cc with 23-46x speedup vs ad-hoc logging, 90-95% transferability across languages (slog specific to Go but patterns universal).
error-tracking
★ 13Track errors with CloudWatch Logs, implement structured logging, and monitor application health. Use when debugging production issues, investigating errors, or improving observability.
monitoring-expert
★ 12Use when setting up monitoring systems, logging, metrics, tracing, or alerting. Invoke for dashboards, Prometheus/Grafana, load testing, profiling, capacity planning. Keywords: monitoring, observability, logging, metrics, tracing, alerting, Prometheus, Grafana.
service-mesh
★ 11A service mesh is an infrastructure layer that provides transparent service-to-service communication with built-in observability, traffic management, and security features without requiring application code changes.
monitoring-observability
★ 11Master monitoring and observability for distributed systems
logging
★ 11Logging standards for logging in Observability environments. Covers best
metrics
★ 11Metrics standards for metrics in Observability environments. Covers best
workers-observability
★ 9Cloudflare Workers observability with logging, Analytics Engine, Tail Workers, metrics, and alerting. Use for monitoring, debugging, tracing, or encountering log parsing, metric aggregation, alert configuration errors.
observability
★ 8Establish observability for research systems, experiments, and data pipelines with guardrails and confidence ceilings.
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