“prometheus”的搜索结果

Migration monitoring, CDC, and observability infrastructure

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Configures monitoring systems, implements structured logging, creates Prometheus/Grafana dashboards, defines alerting rules, instruments distributed tracing, and performs load testing.

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Expert knowledge for Azure Container Storage development including troubleshooting, decision making, limits & quotas, security, and configuration. Use when configuring Elastic SAN-backed pools, CMK encryption, LRS/ZRS redundancy, volume resizing, or Prometheus/Grafana monitoring, and other Azure Container Storage related development tasks. Not for Azure Blob Storage (use azure-blob-storage), Azure Files (use azure-files), Azure Elastic SAN (use azure-elastic-san), Azure NetApp Files (use azure-netapp-files).

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PromQL queries, alerting rules, recording rules, Grafana dashboard JSON, SLO

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Monitoring, logging, and tracing implementation using OpenTelemetry as the unified standard. Use when building production systems requiring visibility into performance, errors, and behavior. Covers OpenTelemetry (metrics, logs, traces), Prometheus, Grafana, Loki, Jaeger, Tempo, structured logging (structlog, tracing, slog, pino), and alerting.

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Use when you need to implement or improve Java metrics observability with Micrometer — including meter design, naming/tag conventions, cardinality control, timers/counters/gauges/distribution summaries, percentiles/histograms, Actuator/Prometheus integration, and metrics validation through tests. This should trigger for requests such as Improve metrics; Apply Micrometer; Add metrics observability; Refactor Micrometer instrumentation; Add Micrometer timers counters or gauges to Java services. Part of Plinth Toolkit

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Observability patterns for Python applications. Triggers on: logging, metrics, tracing, opentelemetry, prometheus, observability, monitoring, structlog, correlation id.

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Generate/create/write PromQL queries, metric expressions, alerting rules, recording rules, Prometheus dashboards.

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Observability and SRE expert. Use when setting up monitoring, logging, tracing, defining SLOs, or managing incidents. Covers Prometheus, Grafana, OpenTelemetry, and incident response best practices.

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Set up the Graphsignal Profiler for inference workloads — vLLM, SGLang, PyTorch, and dstack services. Use when the user wants GPU profiling, tracing, or monitoring for inference, asks about `graphsignal-run` or `graphsignal.watch()`, or asks about CUPTI / Prometheus / OTLP setup.

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Expert at making systems observable and debuggable. Covers structured logging, metrics collection, distributed tracing, error tracking, and alerting. Knows how to find the needle in the haystack when production breaks at 3 AM. Use when "observability, logging, metrics, tracing, monitoring, error tracking, Sentry, Datadog, OpenTelemetry, debugging production, observability, logging, metrics, tracing, monitoring, sentry, prometheus, opentelemetry" mentioned.

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Use when an "enable observability" card targets self_hosted - a minimal Grafana LGTM stack (Loki, Grafana, Tempo, Mimir or Prometheus, with Alloy or an OpenTelemetry Collector) by docker-compose or Helm, its resources and retention, and adding it back as TaskTrooper data sources

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Use when the repository keeps its alerting in code, or a person asks for alerts outside TaskTrooper - PrometheusRule YAML, a Cloud Monitoring alert policy in Terraform, a Datadog monitor, each routed to TaskTrooper's alert ingest URL so it opens an incident here

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Comprehensive Go backend code review with optional parallel review areas. Use when reviewing changed Go files; detects BubbleTea, Wish SSH, and Prometheus and loads the matching review skills.

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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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Work with a Grafana instance — search and read dashboards, run datasource queries (Prometheus, Loki, PostgreSQL, etc.), inspect alert rules and silences, post annotations, and manage folders. Use this whenever the user mentions a Grafana dashboard, panel, or alert; pastes a Grafana URL; asks "what does this dashboard show", "query this metric in Grafana", "is this alert firing", "silence this alert", or wants to create/export a dashboard — even if they don't say "API". Always start from this skill when interacting with this service — its bundled scripts and recipes are the fastest path.

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实现日志 / 指标 / 追踪三大支柱时使用。覆盖 OpenTelemetry / Prometheus / Grafana / Jaeger / Datadog / Sentry 集成。融合 Google SRE 三支柱 + 结构化日志 + Trace Context 传播。

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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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Establish Service Level Objectives (SLO), Service Level Indicators (SLI), and Service Level Agreements (SLA) with error budget tracking, burn rate alerts, and automated reporting using Prometheus and tools like Sloth or Pyrra. Use when defining reliability targets for customer-facing services, balancing feature velocity against system reliability through error budgets, migrating from arbitrary uptime goals to data-driven metrics, or implementing Site Reliability Engineering practices.

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Create production-ready Grafana dashboards with reusable panels, template variables, annotations, and provisioning for version-controlled dashboard deployment. Use when creating visual representations of Prometheus, Loki, or other data source metrics, building operational dashboards for SRE teams, migrating from manual dashboard creation to version-controlled provisioning, or establishing executive-level SLO compliance reporting.

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Use when asked to execute or investigate a PromQL expression against a Prometheus server. Read-only HTTP queries only. No source or remote-system changes.

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GreptimeDB provider for obz. Covers PromQL metric query, labels, label-values, and series commands via GreptimeDB's Prometheus-compatible API. Use this skill when the user mentions "GreptimeDB", "Greptime", "obz metric -p greptimedb", or needs to query metrics stored in a GreptimeDB instance.

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Grafana Mimir provider for obz. Covers all 6 metric commands using standard PromQL. Mimir is a horizontally-scalable Prometheus-compatible TSDB. This skill should be used when the user mentions "Mimir", "Grafana Mimir", "obz metric -p mimir", or needs to query metrics from a Mimir cluster.

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Post-deploy observability for production services — structured logging, RED metrics + Prometheus, Grafana dashboards, SLO-based alerting. Use when setting up monitoring or instrumenting a live service. Trigger on "add logging", "metrics", "dashboard", "alerting", "observability", "monitor this service".

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