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Found 38 Skills
CLI for querying Prometheus and PromQL-compatible engines (Thanos, Cortex, VictoriaMetrics, Grafana Mimir, Grafana Tempo...) — instant queries, range queries, metric discovery (metrics/labels/meta subcommands), output formats (table/csv/json/graph). Apply when executing PromQL queries, troubleshooting performance issues on a software having observability, investigating latency/error rates/saturation, or analyzing time series data.
Execute PromQL instant and range queries against Oodle metrics using the Prometheus-compatible query API.
Query Oodle metrics, discover labels and values, and build PromQL expressions using the label discovery workflow.
Query VictoriaMetrics metrics via curl. Use when running PromQL/MetricsQL queries, discovering metrics/labels, checking alerts and rules, inspecting TSDB status, exporting raw data, checking metric usage statistics, or debugging relabeling/downsampling/retention configs. Triggers on: metric queries, PromQL, MetricsQL, label discovery, series exploration, cardinality checks, alert status, recording rules, active/top queries, export data, metric statistics, relabel debug, downsampling debug, retention debug, flags.
Prometheus monitoring and alerting for cloud-native observability. USE WHEN: Writing PromQL queries, configuring Prometheus scrape targets, creating alerting rules, setting up recording rules, instrumenting applications with Prometheus metrics, configuring service discovery. DO NOT USE: For building dashboards (use /grafana), for log analysis (use /logging-observability), for general observability architecture (use senior-software-engineer with infrastructure focus). TRIGGERS: metrics, prometheus, promql, counter, gauge, histogram, summary, alert, alertmanager, alerting rule, recording rule, scrape, target, label, service discovery, relabeling, exporter, instrumentation, slo, error budget.
Diagnoses, predicts, and mitigates node disruptions during Compute Engine host maintenance and hardware or software maintenance events for GPU and TPU workloads on GKE. Use when diagnosing node disruptions, predicting host maintenance events on GPU/TPU nodepools, inspecting node interruption PromQL metrics, auditing node taints, or configuring workload protection strategies (graceful termination, opportunistic maintenance, PodDisruptionBudgets). Don't use for general GKE cluster creation, network policy configuration, or non-disruption workload deployment.
Monitors and troubleshoots GKE TPU workloads, nodes, and node pools using GKE system metrics and PromQL. Use when monitoring TensorCore duty cycle, TPU memory, node readiness, multi-host TPU node pool availability, host maintenance or preemption interruptions, and calculating MTTR or MTBI metrics for GKE TPUs. Don't use for general non-TPU GKE workload monitoring or non-metric TPU debugging.
Prometheus/Grafana metrics analysis and PromQL queries. Use when investigating latency, error rates, resource usage, or any time-series metrics.
Comprehensive observability and monitoring skill covering Prometheus, Grafana, metrics collection, alerting, exporters, PromQL, and production monitoring patterns for distributed systems and cloud-native applications
Prometheus metrics and PromQL queries. Use when writing PromQL queries, creating recording or alerting rules, debugging metric scraping issues, or understanding counter/gauge/histogram behavior.
Comprehensive toolkit for generating best practice PromQL (Prometheus Query Language) queries following current standards and conventions. Use this skill when creating new PromQL queries, implementing monitoring and alerting rules, or building observability dashboards.
Use these skills when you need to troubleshoot slow performance, analyze query execution plans, identify resource-heavy processes, and monitor system-level PromQL metrics.