129건 · 관련도순
Engineering observability and reliability: SLO/SLI design, distributed tracing, alerting, dashboards, capacity planning, toil automation, reliability review. Use for instrumentation or SLO definition.
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Instruments code so production behavior is visible and diagnosable. Use when adding logging, metrics, tracing, or alerting. Use when shipping any feature that runs in production and you need evidence it works. Use when production issues are reported but you can't tell what happened from the available data.
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Survey existing cloud cost controls — tagging coverage, alerting, and FinOps maturity. Use when asked to "audit our cost controls", "is our tagging complete", or "assess our FinOps maturity".
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Build automated regression suites — golden sets, threshold alerting, CI integration for model changes. Use when asked to "catch model regressions in CI", "build a golden set", or "automate eval regression".
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OpenStack monitoring operations skill for deploying, configuring, and operating the cloud health monitoring stack. Covers Prometheus metric collection and scrape targets, Grafana dashboard provisioning and visualization, Alertmanager notification channels and routing, alerting rules for service health and resource exhaustion, service endpoint health checks, log aggregation strategies, SLA tracking with availability and response time percentiles, and capacity trend analysis from historical metrics. Use when deploying monitoring via Kolla-Ansible, configuring alert thresholds, troubleshooting blank dashboards, tuning noisy alerts, or analyzing cloud performance trends.
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Evaluate operational readiness: SLOs, alerting, runbooks, and rollback plan before launch. Use when reviewing a feature for production readiness.
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Query and manage Datadog monitoring data — logs, metrics, monitors, dashboards, events, SLOs, traces, and incidents. Use this whenever the user wants to search logs, look at a metric, check which monitors are alerting, investigate a trace, pull SLO status, mute an alert, or ask "what's happening in Datadog" — even if they don't say "API". Also use it for any URL under *.datadoghq.com. Always start from this skill when interacting with this service — its bundled scripts and recipes are the fastest path.
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System monitoring, alerting, and observability implementation
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Creates and manages AWS CloudWatch composite alarms using the CloudWatch PutCompositeAlarm API. Builds alarm rule expressions from existing metric alarms with AND/OR/NOT logic for multi-signal alerting.
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配置监控和告警时使用。适用于 Prometheus / Grafana / Loki / PagerDuty / SLO 定义 / 告警规则设计。融合 Google SRE 四大黄金信号 + USE Method + 告警分级。
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Implement comprehensive model drift monitoring using Evidently AI, statistical tests (PSI, KS), and custom metrics to detect data drift and concept drift in production ML systems. Set up automated alerting and reporting workflows to catch degradation before it impacts business metrics. Use when production models show unexplained performance degradation, when new data distributions differ from training data, when seasonal shifts affect input features, or when regulatory requirements mandate model monitoring.
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Use when the user needs to deploy, operate, secure, or scale running infrastructure — cloud architecture (multi-region, VPC, FinOps), CI/CD and deployment strategies, secrets/IAM/supply-chain security, observability and SLO alerting, SRE and incident response, Kubernetes vs ECS and autoscaling, Terraform/Pulumi/CDK, or platform engineering and DORA metrics. Also for generating runbooks, pipeline configs, Terraform modules, or Kubernetes manifests. For choosing the system's architecture or stack before it runs (monolith vs microservices, which database), use software-architect.
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Build AI crisis monitoring and alerting systems. TRIGGERS - Use when user needs help with ai-crisis-monitor related tasks.
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Pino logging, Sentry error tracking, Axiom - structured logging with correlation IDs, error boundaries, performance monitoring, alerting
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Bootstraps Flux CD on Kubernetes clusters, creates and manages GitOps sources (Git/Helm/OCI/Bucket), configures kustomizations and Helm releases, reconciles resources, sets up image automation and alerting, and pushes OCI artifacts. Use this skill whenever the user mentions the flux CLI, flux bootstrap, flux create source, flux create kustomization, flux create helmrelease, flux reconcile, flux get, Flux CD, GitOps with Flux, or asks about managing Kubernetes deployments via GitOps. Also trigger when users ask about creating Git/Helm/OCI/Bucket sources, building or diffing kustomizations, pushing OCI artifacts, setting up image automation, creating Flux alerts/receivers, or bootstrapping Flux on GitHub/GitLab/Gitea/Bitbucket. Even if the user just says "flux" in a Kubernetes context, this skill applies.
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Ship an app from code to production-ready infrastructure: containerize with Docker and multi-stage builds, set up GitHub Actions CI/CD with automated testing and deployment, add monitoring with health checks and alerting, then run preflight verification..
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Audit commercial lease compliance systems -- CAM reconciliation accuracy (pro-rata share, caps, admin fees), lease abstraction completeness, critical date tracking and deadline alerting, clause compliance monitoring (insurance certificates, permitted use, co-tenancy).
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Use when monitoring, diagnosing, or managing Batch Apex, Scheduled Apex, Queueable, and Flow scheduled jobs: Setup > Apex Jobs, AsyncApexJob queries, concurrent limits, failure detection, and notification patterns. NOT for writing the Batch or Schedulable class itself — use apex/batch-apex-patterns or apex/apex-scheduled-jobs. NOT for BatchApexErrorEvent alerting in code — use apex/scheduled-apex-failure-detection-and-monitoring. Trigger keywords: Setup > Scheduled Jobs, Apex Flex Queue, CronTrigger, CronJobDetail, FlowInterview, System.abortJob, System.schedule, CRON expression, Holding status, BLOCKED state, reschedule after sandbox refresh, scheduled job runbook.
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Use when introducing a feature flag system, choosing between release flags / experiment flags / operational flags / kill switches / permission flags, designing percentage rollouts, building kill-switch + circuit-breaker patterns, structuring evaluation contexts (user IDs, plan tier, region), or building flag-cleanup discipline. Triggers: LaunchDarkly / GrowthBook / Unleash / Flagsmith / OpenFeature, percentage ramp, sticky bucketing, kill switch wired to alerting, "we still have flags from 2 years ago", flag debt, OpenFeature provider, evaluation context, default value on provider failure. NOT for A/B test statistical analysis (separate skill), traffic-split routing at the edge, build-time bundler defines, or environment-based config.
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Use when building Grafana dashboards backed by Prometheus, Loki, or Tempo, designing PromQL/LogQL queries, wiring template variables, setting alert rules, building SLO dashboards, or maintaining dashboards as code. Triggers: rate() vs increase() confusion, irate vs rate, label_replace, recording rules, alerting rule expressions, multi-dimensional template variables, ad-hoc filters, dashboard JSON model, provisioning via Terraform/grafonnet, p99 / histogram_quantile usage. NOT for Datadog/New Relic dashboards (vendor-specific), Grafana plugin development, or Loki ingestion pipeline tuning.
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Design error handling strategies for TypeScript and Python applications — exception hierarchies, Result/Either types, retry patterns, error boundaries, and structured error logging. Use when designing error handling architecture, choosing between exceptions and Result types, implementing retry logic, or building error recovery flows. Activate on "error handling", "exception hierarchy", "Result type", "retry pattern", "circuit breaker", "error boundary", "Pokemon exception". NOT for debugging specific runtime errors, logging infrastructure setup, or monitoring/alerting configuration.
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Use when adding logging, metrics, tracing, or alerting to production code, or when a past incident lacks diagnostic data.
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Use when working with Grafana — dashboards, Loki LogQL queries, alerting rules, monitoring panels — even when the user just says 'build me a dashboard' or 'query the logs' without naming Grafana.
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Use when deciding what earns a page — the page, action and info classes stated provider-neutrally, and the rule that a page without an owner, a runbook and a first diagnostic step is malformed.
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