logstash-openshift
Manage Logstash pipelines deployed in OpenShift using ConfigMaps. Use for pipeline configuration, deployment, troubleshooting, and maintenance of Logstash in containerized OpenShift environments.
Manage Logstash pipelines deployed in OpenShift using ConfigMaps. Use for pipeline configuration, deployment, troubleshooting, and maintenance of Logstash in containerized OpenShift environments.
Advanced service mesh implementation with Istio, Linkerd, traffic management, mTLS, and observability.
Set up Prometheus for comprehensive metric collection, storage, and monitoring of infrastructure and applications. Use when implementing metrics collection, setting up monitoring infrastructure, or configuring alerting systems.
Implement monitoring, alerting, and observability with CloudWatch
Enforce telemetry contract stability (event naming, JSONL envelopes, /api/health + /api/status shape). Use when investigating telemetry drift, adding new telemetry fields, or updating z-server ingestion/UI.
logger is a structured error logger that integrates well with github.com/rohanthewiz/serr. logger.LogErr will write out all the context stored in the SErr.
Fetch, analyze, and resolve Sentry errors with CLI integration; use when reviewing production errors, resolving issues, analyzing error patterns, or managing Sentry configuration
Configure Grafana Loki logging using mazza-base library for Python/Flask applications with CA certificate (Mazza-specific). Use when setting up Loki logging for Mazza projects or configuring centralized logging.
Instrument code with tracing spans and structured logging. Use for observability and performance analysis.
Create standardized report headers with metadata for all agent-generated reports. Use when generating bug reports, security audits, dependency reports, or any worker output requiring consistent formatting.
Add PostHog feature flags for gradual rollouts, A/B tests, or beta features. Use when implementing feature toggles, experiments, or canary releases.
Expose Prometheus metrics with counters, gauges, and histograms. Use for production monitoring and alerting.
Google Cloud observability - logging, monitoring, tracing
Implements and manages JU-DO-KON! features behind feature flags with observability and safe defaults.
Best practices for structured logging, correlation IDs, performance metrics, and debugging in Bun applications using @sidequest/core/logging and LogTape. Use when implementing logging, setting up observability, debugging production issues, tracking performance metrics, adding correlation IDs, configuring subsystem loggers, or working with JSONL log analysis. Covers plugin logger factory, hierarchical categories, log levels, metrics collection, and operational debugging workflows.
Logging, metrics, and distributed tracing. OpenTelemetry, Prometheus, Grafana, and production debugging.
Design and implement observability stack with metrics, logs, and traces. Use for Prometheus, Grafana, Loki, Tempo, OpenTelemetry, alerting, and SLO/SLI design. Keywords: observability, monitoring, tracing, Prometheus, Grafana, Loki, Tempo, OpenTelemetry, OTEL, alerting, SLO, SLI.
Use PROACTIVELY for JMH benchmarks in this Spark protobuf project. Handles sbt commands, always cleans before benchmarking, saves output to /tmp logs, and uses log-reader agent to parse results.