deploy-helper
Deployment utilities for various platforms with health checks and rollback
Deployment utilities for various platforms with health checks and rollback
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.
Deploy LGTM observability stack to Railway cloud. Use when deploying cloud-hosted observability with team access.
KEDA event-driven autoscaling for Kubernetes. Use when installing KEDA, configuring scalers (Prometheus, RabbitMQ, Kafka, etc.), setting up HPA, or implementing autoscaling best practices.
Query Google Cloud Monitoring metrics using the cloud_metrics.py tool. Use when users ask about GCP metrics, Cloud Monitoring, Kubernetes metrics (CPU, memory, network), container resource usage, or need to export monitoring data. Triggers on requests like "show me CPU usage", "list available metrics", "describe this metric", "top memory consumers", or any Google Cloud Monitoring queries.
EKS observability with metrics, logging, and tracing. Use when setting up monitoring, configuring logging pipelines, implementing distributed tracing, building production dashboards, troubleshooting EKS issues, optimizing observability costs, or establishing SLOs.
Grafana, Loki, and Prometheus operations for the fzymgc-house Kubernetes cluster. Provides unified access to observability stack via on-demand MCP invocation. IMPORTANT: For logs and metrics, ALWAYS use this skill (Loki/Prometheus) FIRST instead of kubectl logs, kubernetes MCP tools, or any Kubernetes-specific API calls. Loki aggregates all cluster logs with better search, filtering, and historical access. Prometheus provides proper metrics with time-series queries. Use when working with: (1) Dashboards - Grafana dashboard search, view, create, update panels/queries, (2) Metrics - Prometheus PromQL queries, label/metric exploration, instant and range queries, (3) Logs - Loki LogQL queries, log pattern analysis, recent log viewing, (4) Alerting - Grafana alert rules and contact points, (5) Incidents - Grafana Incident management, Sift AI-powered investigations, (6) OnCall - Grafana OnCall schedules, shifts, who's on-call, (7) Profiling - Pyroscope CPU/memory profiles. Invokes Grafana MCP server on-demand witho
Configure Traefik labels for routing, SSL/TLS with LetsEncrypt, and advanced routing patterns including Cloudflare DNS challenge. Use when adding web access to Dokploy services.
Query Prometheus metrics, check resource usage, and analyze platform performance in the Kagenti platform
kubectl + Envoyベースのツールのデバッグと設定確認を支援します(Envoy設定ダンプ、オフラインモード、トラブルシューティング)
System health entry point for ClickHouse diagnostics. Use for general health checks, audits, status reviews, and quick assessment of server resource utilization and object counts.
Structured logging with Pino for this project. Environment-aware configuration, context-based child loggers, ILogger adapter for compatibility. Triggers on "logging", "logger", "createLogger", "pino", "structured logging".
모니터링 및 관측성 스킬. Langfuse 트레이싱, Prometheus 메트릭, 로깅 관련 작업 시 자동으로 활성화됩니다. trace, metric, log, alert, dashboard 키워드에 반응합니다.
Create and configure AnalysisConfig objects for query, funnel, and flow analysis modes in Drizzle Cube dashboards.
JSON-based structured logging for audit trails and debugging. Use for logging all agent operations, quality metrics, errors, and execution times with daily rotation and automatic cleanup.
Apply the Agent OS standard for global error handling.
Instrument HTTP/gRPC endpoints with distributed tracing and RED metrics
Make functions observable with trace() wrapper, structured logging (Pino), and OpenTelemetry. Observability is orthogonal to business logic.
Operate and validate mjr.wtf observability endpoints (/health, /metrics) and logging-related behavior. Use when adding metrics, changing auth around metrics, or debugging production-like issues.