[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6HA5ETG9NFKZH2QEZP4PNS5":3,"skill-same:01M6HA5ETG9NFKZH2QEZP4PNS5":60},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":16,"categories":17,"keywords":18,"publishedAt":31,"linkOnly":32,"markdownContent":33,"markdownBody":34,"frontMatter":35,"refName":38,"commitSha":39,"skillDirectory":40,"forksCount":14,"repositoryHtmlUrl":41,"repositoryHomepageUrl":6,"ownerHtmlUrl":42,"ownerBlogUrl":43,"ownerDescription":44,"updatedAt":45,"install":46,"resources":59},"01M6HA5ETG9NFKZH2QEZP4PNS5","monitoring-sysadmin",null,"System monitoring, metrics, alerting, dashboards, and observability","NeuralBlitz\u002FMito","NeuralBlitz","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F79354388?v=4","01M6H8T2TFH477HRS0KTSTKR2E","David 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Datadog)\n- Quantitative measurements\n- Time-series data\n- Counters, gauges, histograms\n- Aggregations\n\n### Logs (ELK, Loki, Splunk)\n- Detailed event records\n- Structured\u002Funstructured\n- Log levels (DEBUG, INFO, WARN, ERROR)\n- Correlation IDs\n\n### Traces (Jaeger, Zipkin)\n- Request flow across services\n- Latency breakdown\n- Distributed tracing\n- Span context\n\n## Metrics Types\n\n### Golden Signals\n- **Latency**: Response time\n- **Traffic**: Requests per second\n- **Errors**: Error rate\n- **Saturation**: Resource utilization\n\n### RED Metrics (Rate, Errors, Duration)\n- For request-driven services\n\n### USE Metrics (Utilization, Saturation, Errors)\n- For resource-driven services\n\n## Alerting\n\n### Best Practices\n- Alert on symptoms, not causes\n- Tune thresholds\n- Avoid alert fatigue\n- Include context\n- Runbooks for each alert\n\n### Severity Levels\n- **Critical**: Immediate action needed\n- **Warning**: Attention needed\n- **Info**: For awareness\n\n## Dashboards\n\n### Design Principles\n- Show relevant data\n- Include context\n- Time ranges\n- Drill-down capability\n- Shareable links\n\n### Common Dashboards\n- Service overview\n- Infrastructure\n- Application performance\n- Business metrics\n- Incident response\n\n## Tools\n\n### Monitoring\n- **Prometheus**: Metrics, alerting\n- **Datadog**: Full-stack\n- **CloudWatch**: AWS\n- **Stackdriver**: GCP\n\n### Visualization\n- **Grafana**: Dashboards\n- **Kibana**: Logs\n\n### Logging\n- **ELK Stack**: Elasticsearch, Logstash, Kibana\n- **Loki**: Promtail + Loki + Grafana\n- **Splunk**: Enterprise\n\n### Tracing\n- **Jaeger**: Distributed tracing\n- **Zipkin**: Twitter's tracer\n- **AWS X-Ray**: Cloud\n\n## SRE Concepts\n\n### SLI (Service Level Indicator)\n- Metric measuring service level\n- Request latency\n- Error rate\n- Availability\n\n### SLO (Service Level Objective)\n- Target SLI value\n- \"99.9% of requests \u003C 200ms\"\n\n### SLA (Service Level Agreement)\n- Customer-facing commitment\n- SLO + consequences\n","## What I do\n- Set up comprehensive monitoring systems\n- Configure meaningful alerts\n- Create actionable dashboards\n- Analyze metrics and trends\n- Implement observability\n- Establish SLOs and SLIs\n\n## When to use me\nWhen tracking system health, debugging issues, or establishing operational excellence.\n\n## The Three Pillars\n\n### Metrics (Prometheus, Datadog)\n- Quantitative measurements\n- Time-series data\n- Counters, gauges, histograms\n- Aggregations\n\n### Logs (ELK, Loki, Splunk)\n- Detailed event records\n- Structured\u002Funstructured\n- Log levels (DEBUG, INFO, WARN, ERROR)\n- Correlation IDs\n\n### Traces (Jaeger, Zipkin)\n- Request flow across services\n- Latency breakdown\n- Distributed tracing\n- Span context\n\n## Metrics Types\n\n### Golden Signals\n- **Latency**: Response time\n- **Traffic**: Requests per second\n- **Errors**: Error rate\n- **Saturation**: Resource utilization\n\n### RED Metrics (Rate, Errors, Duration)\n- For request-driven services\n\n### USE Metrics (Utilization, Saturation, Errors)\n- For resource-driven services\n\n## Alerting\n\n### Best Practices\n- Alert on symptoms, not causes\n- Tune thresholds\n- Avoid alert fatigue\n- Include context\n- Runbooks for each alert\n\n### Severity Levels\n- **Critical**: Immediate action needed\n- **Warning**: Attention needed\n- **Info**: For awareness\n\n## Dashboards\n\n### Design Principles\n- Show relevant data\n- Include context\n- Time ranges\n- Drill-down capability\n- Shareable links\n\n### Common Dashboards\n- Service overview\n- Infrastructure\n- Application performance\n- Business metrics\n- Incident response\n\n## Tools\n\n### Monitoring\n- **Prometheus**: Metrics, alerting\n- **Datadog**: Full-stack\n- **CloudWatch**: AWS\n- **Stackdriver**: GCP\n\n### Visualization\n- **Grafana**: Dashboards\n- **Kibana**: Logs\n\n### Logging\n- **ELK Stack**: Elasticsearch, Logstash, Kibana\n- **Loki**: Promtail + Loki + Grafana\n- **Splunk**: Enterprise\n\n### Tracing\n- **Jaeger**: Distributed tracing\n- **Zipkin**: Twitter's tracer\n- **AWS X-Ray**: Cloud\n\n## SRE Concepts\n\n### SLI (Service Level Indicator)\n- Metric measuring service level\n- Request latency\n- Error rate\n- Availability\n\n### SLO (Service Level Objective)\n- Target SLI value\n- \"99.9% of requests \u003C 200ms\"\n\n### SLA (Service Level Agreement)\n- Customer-facing commitment\n- SLO + consequences\n",{"name":5,"license":15,"metadata":36,"description":7,"compatibility":28},{"audience":27,"category":37},"systems-administration","main","2ea764e153842704d24a2e9aa4170441a7f03081",".opencode\u002Fskills\u002Fmonitoring-sysadmin","https:\u002F\u002Fgithub.com\u002FNeuralBlitz\u002FMito","https:\u002F\u002Fgithub.com\u002FNeuralBlitz","nuralnexus.org","Independent Multidisciplinary Researcher, Creative Producer, and AI Systems Architect\r\nAn independent creator and research-driven systems designer.","2026-11-12 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