py-observability
Observability patterns for Python backends. Use when adding logging, metrics, tracing, or debugging production issues.
Observability patterns for Python backends. Use when adding logging, metrics, tracing, or debugging production issues.
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 practices.
Use this when working with OpenTelemetry, telemetry, observability, traces, spans, metrics, logs, OTLP, semantic conventions, or instrumentation. Triggers on questions like "what attributes should I use", "how do I configure the collector", "what's the semconv for X".
Implement comprehensive observability for service meshes including distributed tracing, metrics, and visualization. Use when setting up mesh monitoring, debugging latency issues, or implementing SLOs for service communication.
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 component configuration, subscription patterns, publishing events, and Kubernetes deployment. NOT when using direct Kafka clients or non-Dapr messaging patterns.
Structured logging, distributed tracing, and metrics for production applications. [What: OpenTelemetry setup, log level strategy, correlation IDs, SLI/SLO alerting thresholds, Grafana dashboard design, PagerDuty integration] [When: setting up production logging, adding observability to a service, debugging distributed systems, designing alerting, implementing traces/metrics/logs] [Keywords: logging, observability, OpenTelemetry, OTel, structured logs, distributed tracing, correlation ID, metrics, Grafana, Prometheus, PagerDuty, Winston, Pino, structlog, log levels, SLI, SLO, alerting] NOT for application performance profiling (use a profiler), load testing, or database query optimization.
Convert arrays with hardcoded pointer addresses to use ROM_START/ROM_END symbols. This automates the process of adding USE_ASSET declarations, updating array initialization, and configuring YAML segments.
Guide collection and analysis of performance traces. Use when a mid-level developer needs to diagnose slowness.
Coordinate debugging across multiple services. Use when a senior developer needs to trace a distributed issue.
Summarize noisy logs into likely causes and next steps. Use when a junior developer needs help interpreting logs.
Set up metrics, logs, and traces for a service. Use when a mid-level developer needs basic observability coverage.
Guides when to use docs create/edit CLI tools versus direct file editing for InfluxData documentation.
Set up InfluxDB 3 Core and Enterprise instances for running documentation code block tests. Handles service initialization, worktree-specific databases, and test environment configuration.
Use when designing Universal CI/CD, Multi-Cloud Infrastructure, or Observability systems.
Generate or refresh the local Claude adapter surface for DocMason from canonical committed sources.
Logging best practices focused on wide events (canonical log lines) for powerful debugging and analytics
Analyze OpenShift must-gather diagnostic data including cluster operators, pods, nodes, and network components. Use this skill when the user asks about cluster health, operator status, pod issues, node conditions, or wants diagnostic insights from must-gather data. Triggers: "analyze must-gather", "check cluster health", "operator status", "pod issues", "node status", "failing pods", "degraded operators", "cluster problems", "crashlooping", "network issues", "etcd health", "analyze clusteroperators", "analyze pods", "analyze nodes"
Grade component health based on regression triage metrics for OpenShift releases
Implement PostHog analytics, feature flags, and session replay for Next.js apps. Use this skill for event tracking, user identification, A/B testing, experiments, and session recording setup. Also handles analytics reporting (funnel analysis, retention, SEO) with Google Search Console integration.
Register the orchestrator as active with the Crewly backend. Must be called on startup.
Create a new NgRx SignalStore following the patterns used in this codebase. Use when asked to add a new store, state slice, or signal-based state container. Produces feature functions first, combines them in signalStore(), and adds a spec file.
Proactively discover Israeli tech founders about to start new companies via LinkedIn signals. Syncs leads to HubSpot and tracks approach status.