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Found 47 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.
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.
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.
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.
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.
Use these skills when you need to troubleshoot performance bottlenecks, analyze query execution plans, identify resource-heavy processes, and monitor system-level PromQL metrics.
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.
Generates Google Cloud Monitoring Server-Driven UI (SDUI) Widget and XyChart Protocol Buffer textprotos from resolved PromQL queries. Use when: - Generating valid google.monitoring.dashboard.v1.Widget textprotos, containing PrometheusQuery datasets, for use with the Cloud Monitoring Dashboards API, gcloud CLI, or declarative dashboard definitions. - Synthesizing Server-Driven UI (SDUI) widget titles, axis labels, and plot types for Prometheus queries. Don't use for: - Metric discovery or PromQL query generation. For those tasks, use the cloud-monitoring-metric-selection or cloud-monitoring-promql-query skills.
Prometheus/Grafana metrics analysis and PromQL queries. Use when investigating latency, error rates, resource usage, or any time-series metrics.
Generates valid PromQL queries from Cloud Monitoring metric descriptors and resource parameters. Use when asked to create, generate, write, or format PromQL queries, PromQL strings, or PromQL aggregations for Cloud Monitoring metrics and resources. Don't use for raw metric discovery or metric selection.
This skill should be used when the user asks to "query metrics", "investigate a metrics issue", "check CPU usage", "find slow services", "investigate production issues using metrics", "search for metrics", "search metric names", "run a PromQL query", "check error rate", "check latency", "look up a metric", "analyze system load", "check memory usage", "investigate infrastructure issues", "analyze custom metrics", "check node health", "investigate disk usage", or wants to explore Coralogix metrics data - including application, infrastructure, and custom metrics - using the cx CLI.