Découvrez les skills tools monitoring, comparez leurs dépôts et consultez leurs instructions.
Generic AIOps (AI for IT Operations) patterns and best practices for 2025. Provides comprehensive implementation strategies for intelligent monitoring, automation, incident response, and observability across an...
Implement Linkerd service mesh patterns for lightweight, security-focused service mesh deployments. Use when setting up Linkerd, configuring traffic policies, or implementing zero-trust networking with minimal...
Per-call and aggregated latency tracking for MEV infrastructure. Use when implementing performance monitoring or debugging slow operations. Triggers on: latency, timing, performance, slow, speed, instrumentatio...
Structured logging, metrics, distributed tracing, and alerting strategies
Configures Dapr pub/sub components for event-driven microservices with Kafka or Redis. Use when wiring agent-to-agent communication, setting up event subscriptions, or integrating Dapr sidecars. Covers componen...
Add comprehensive debugging and observability tooling for backend storage layers (PostgreSQL, ChromaDB) and startup metrics. Includes storage drift detection, raw data inspection endpoints, and a Next.js admin...
Monitor system resources (CPU, memory, disk, network) during development and production.
Implement JSON-based structured logging for observability. Use when setting up logging, debugging production issues, or preparing for log aggregation (ELK, Datadog). Covers log levels, context, and best practic...
Observability patterns for Python applications. Triggers on: logging, metrics, tracing, opentelemetry, prometheus, observability, monitoring, structlog, correlation id.
Use when building distributed microservices with Dapr sidecar architecture. Triggers include Dapr components, service invocation, state management, pub/sub, secrets, bindings, configuration, actors, and workflo...
Use when implementing Kubernetes cost visibility (OpenCost, VPA), backup/disaster recovery (Velero, RTO/RPO), or chaos engineering (Chaos Mesh). Triggers on cost optimization, right-sizing, FinOps, backup sched...
Build production traffic engineering for Kubernetes with Envoy Gateway, Gateway API, KEDA autoscaling, and Envoy AI Gateway. Use when implementing ingress, rate limiting, traffic routing, TLS, autoscaling, or L...
Build Kubernetes observability stacks with Prometheus, Grafana, OpenTelemetry, Jaeger, and Loki. Use when implementing metrics, tracing, logging, SRE practices, or cost engineering for cloud-native applications...
Measure what matters with proper event tracking, funnels, cohorts, and metrics. Use when setting up analytics, tracking features, or understanding behavior.
Set up crash instrumentation with actionable context. Use when configuring crash capture, error boundaries, or breadcrumb strategies.
Instrument API requests with spans and distributed tracing. Use when tracking request latency, correlating client-backend traces, or debugging API issues.
Build data visualization and analytics dashboards. Use when creating charts, KPI displays, metrics dashboards, or data visualization components. Triggers on analytics, dashboard, charts, metrics, KPI, data visu...
Configure Spring Boot Actuator for production-grade monitoring, health probes, secured management endpoints, and Micrometer metrics across JVM services.
Implement comprehensive monitoring, logging, metrics, tracing, and alerting for production applications to ensure reliability and quick incident response. Use when setting up application monitoring, implementin...
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.
Framework for monitoring activation, engagement, and monetization guardrails.
Framework for defining, approving, and auditing GTM metrics and KPIs.
Use when defining nurture pacing, triggers, and suppression logic.
Use when defining events, fields, and governance for GTM analytics pipelines.
Le classement utilise les étoiles du dépôt GitHub indexé. Plusieurs skills peuvent partager ce nombre : ce n’est ni un nombre d’installations ni une note de qualité.