726 skills · sorted by relevance
Set up WizTelemetry Ruler in KubeSphere to generate alerts from events, audit records, and container logs. Manage alert rules, configure notification destinations, and query alert history or statistics by time range, severity, and other filters.
Create and validate Terraform alerts for GKE using PromQL, a monitoring query language. Cover response times, errors, traffic, memory usage, and cluster health, with checks for alert timing, duplicate signals, and metric ingestion costs.
Create Terraform files that define alerts for AI agent latency, errors, token use, safety, security, and response quality. Check telemetry and existing policies first, then validate the generated configuration. Quality alerts require Vertex AI.
Create and manage Axiom alert rules and notification destinations through its API. Connect alerts to email, Slack, or webhooks, check monitor history, and adjust thresholds and evaluation schedules to address excessive or missing alerts.
Configure Prometheus Alertmanager with routing trees, receivers (Slack, PagerDuty, email), inhibition rules, silences, and notification templates for actionable incident alerting. Use when implementing proactive monitoring with automated incident detection, routing alerts to the appropriate team by severity, reducing alert fatigue through grouping and deduplication, integrating with on-call systems like PagerDuty, or migrating from legacy alerting to Prometheus-based alerting.
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Define reliability goals for Google Cloud services and generate Terraform files for Cloud Monitoring SLO alerts. A guided conversation gathers service scope, measurement metrics, targets, and alert conditions, then explains the PromQL queries used to evaluate them.
Restructure and optimize alert rules for monitoring platforms (Sentry, PagerDuty, Datadog, OpsGenie). Use when someone asks to "reduce alert noise", "fix alert fatigue", "create alert rules", "set up escalation policies", "tune alerting thresholds", or "create on-call runbooks". Generates platform-specific alert configurations and tiered escalation policies.
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Design production alerts, route notifications by severity, and organize on-call schedules. Use configuration examples to define backup contacts, escalation steps when alerts go unanswered, and runbooks that guide responders through incident investigation.
Creates Terraform configuration for Google Cloud Monitoring notification channels, including email, Slack, and Pub/Sub, and attaches channels to existing alert policies. It also checks Pub/Sub topic compatibility and publishing permissions when inspecting the cloud environment.
Investigate an alert, page, or production symptom in an incident channel or a team's oncall / monitoring channel, and report findings a human can verify. Ordinary conversation and chatter are not alerts; leave those alone. Use when an alert or page lands, when error rate, latency or saturation is up, when someone asks "why is X broken", "investigate", "what changed", "root cause this", pastes a monitor, dashboard, trace or error-tracker link, or reports production trouble; also by default when an alert lands in a covered channel unasked. Feed-level asks land here too ("which alerts matter", "triage today's alerts"), plus the scheduled alert-review routine and the ticket path ("customer X can't check out"). Runs a fast first pass posted as a short interim update with a TL;DR, every finding carrying the query or link to verify it, then proposes the fix and — with connector access and confirmation — carries it out, never unattended. Afterwards `incident-postmortem` writes it up.
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Retrieve disease outbreak alerts and air-quality health warnings for countries and cities. Review disease summaries, alert levels, sources, and fine-particle pollution readings to understand reported public-health risks in a location.
Review Monte Carlo alerts, score their likelihood of indicating an incident and their potential impact, and investigate likely causes. Use the same stages to design and test a repeatable triage workflow, starting with recommendations before enabling actions.
Deploy and configure Snort 3 to detect suspicious network traffic. Create custom detection rules, tune community rules to reduce false alerts, test them against captured traffic, and forward alerts to a central security monitoring platform.
Design service monitoring dashboards and improve existing alert configurations. Generate Grafana dashboard files and documentation, analyze noisy or duplicate alerts and coverage gaps, and outline how metrics, logs, and request traces fit together.
Triage Google SecOps alerts by checking logs, related cases, asset importance, and threat intelligence. Classify findings, adjust severity and priority, and document evidence for closing benign cases or handing suspicious activity to incident responders.
Generate Terraform alerts for Cloud Run services, jobs, and worker pools using PromQL, a monitoring query language. Monitor errors, latency, resource usage, job failures, and queue delays, with configurable thresholds and explanations of when each alert triggers.
Investigate Sentry alerts using Datadog logs and recent GitHub changes, then post an initial diagnosis with a severity assessment. Notify the on-call team when severity reaches the configured threshold or the investigation remains inconclusive, without changing monitored systems.
Design service monitoring with Prometheus, write PromQL queries to analyze metrics, and build Grafana dashboards. Configure actionable alerts and manage metric labels so monitoring stays useful as the volume of collected data grows.
Review the configured cost alert rules and the alerts currently fired on the Agent Monitor dashboard, then explain exactly what tripped and why. Uses /api/alerts (fired feed) and /api/alerts/rules (definitions). Use when checking spend alerts or asking why a cost alarm went off.
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Configures best-practice alerting policies for AI agents using OpenTelemetry (OTel) metrics, generating output as Terraform (.tf) configuration files. Use when analyzing, writing, or deploying alerting policies to monitor agent latency, error rates, token usage, and quality metrics. Don't use for standard infrastructure monitoring unrelated to AI agents, or when the agent is not instrumented with OpenTelemetry (for Reliability, Cost, Safety, Security alerts). NOTE: Reliability, Cost, Safety, and Security alerts use generic OTel metrics and work across runtimes (such as Cloud Run, Vertex AI). Quality alerts rely on Vertex AI Online Monitors and are strictly bound to Vertex AI deployments.
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Conviction-trigger surveillance via Quartr keyword alerts — parse every active thesis's Conviction Triggers for named observables, propose keyword alerts scoped to the Vault Active watchlist (or market-wide for macro observables), create them ONLY on explicit user confirmation, and reconcile the alert set against the book as theses open/close. Use when user says "monitor", "set up alerts", "keyword alerts", "watch for X", or "reconcile alerts".
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Design a shared notification workflow across GitHub, Linear, local hooks, desktop alerts, and existing communication tools. Classify urgency and ownership, merge duplicate events, and decide which updates need immediate attention, a digest, or a log entry.
Deploy and operate Falco to monitor running containers in Kubernetes or Docker. Choose a driver, validate detection rules, confirm alerts for suspicious activity, and forward those alerts to a central security monitoring system.
Investigate slow jobs, stale data, and timeout alerts by timing the specific operation and comparing monitoring thresholds. Produce an evidence-based verdict that distinguishes insufficient time, stalled work, and false alerts before proposing changes.