[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6H930AGE2JS6VT7BH9DYXJP":3,"skill-same:01M6H930AGE2JS6VT7BH9DYXJP":59},{"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":30,"linkOnly":31,"markdownContent":32,"markdownBody":33,"frontMatter":34,"refName":37,"commitSha":38,"skillDirectory":39,"forksCount":14,"repositoryHtmlUrl":40,"repositoryHomepageUrl":6,"ownerHtmlUrl":41,"ownerBlogUrl":42,"ownerDescription":43,"updatedAt":44,"install":45,"resources":58},"01M6H930AGE2JS6VT7BH9DYXJP","canary-releases",null,"Progressive rollout deployment strategy","NeuralBlitz\u002FMito","NeuralBlitz","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F79354388?v=4","01M6H8T2TFH477HRS0KTSTKR2E","David Riggs","01M6H8T2YQQDXPYM092P670Z21",0,"MIT","https:\u002F\u002Fgithub.com\u002FNeuralBlitz\u002FMito\u002Fblob\u002Fmain\u002F.opencode\u002Fskills\u002Fcanary-releases\u002FSKILL.md",[],[19,20,21,22,23,24,25,26,27,28,29],"canary","releases","canary releases","deployment","strategy","devops","rollout","opencode","engineer","deployment strategy","platform","2026-11-10 10:12:30",false,"---\nname: canary-releases\ndescription: Progressive rollout deployment strategy\nlicense: MIT\ncompatibility: opencode\nmetadata:\n  audience: devops-engineer, platform-engineer\n  category: devops\n---\n\n## What I do\n\n- Design and implement canary release strategies\n- Gradually shift traffic from stable to new versions\n- Implement automated traffic routing based on metrics\n- Create canary analysis and evaluation frameworks\n- Build rollback triggers based on error rates and latency\n- Monitor and analyze canary performance metrics\n\n## When to use me\n\n- When you want to reduce risk of new deployments\n- When you need to validate changes with real production traffic\n- When deploying to large user bases where failures are costly\n- When you want data-driven deployment decisions\n- When implementing progressive delivery practices\n- When working with microservices architectures\n\n## Key Concepts\n\n### Traffic Splitting\n\n```yaml\n# Kubernetes Istio virtual service for canary routing\napiVersion: networking.istio.io\u002Fv1alpha3\nkind: VirtualService\nmetadata:\n  name: myapp\nspec:\n  hosts:\n    - myapp\n  http:\n    - route:\n        - destination:\n            host: myapp\n            subset: stable\n          weight: 90\n        - destination:\n            host: myapp\n            subset: canary\n          weight: 10\n```\n\n### Metrics-Based Routing\n\n```javascript\n\u002F\u002F Prometheus alert for canary analysis\n- alert: CanaryHighErrorRate\n  expr: |\n    rate(http_requests_total{service=\"canary\"}[5m]) \n    \u002F rate(http_requests_total{service=\"stable\"}[5m]) > 0.1\n  for: 5m\n  labels:\n    severity: critical\n  annotations:\n    summary: \"Canary error rate exceeds 10% of stable\"\n    description: \"Automated rollback recommended\"\n```\n\n### Phased Rollout\n\n1. **Initial**: 1-5% traffic to canary\n2. **Validation**: Monitor error rates and latency\n3. **Expansion**: Increase to 25%, 50%, 75%\n4. **Promotion**: Full 100% traffic\n5. **Cleanup**: Remove old version\n\n### Key Metrics to Monitor\n\n- **Error Rate**: Compare canary vs. stable\n- **Latency**: P50, P95, P99 response times\n- **Success Rate**: Request completion percentage\n- **Resource Usage**: CPU, memory, network\n- **Business Metrics**: Conversion rates, session duration\n- **Custom Metrics**: Domain-specific indicators\n\n### Rollback Triggers\n\n- Error rate exceeds 2x stable environment\n- P99 latency exceeds threshold (e.g., 500ms)\n- CPU or memory usage exceeds 80%\n- Custom business metric degradation\n- Manual override triggered\n","## What I do\n\n- Design and implement canary release strategies\n- Gradually shift traffic from stable to new versions\n- Implement automated traffic routing based on metrics\n- Create canary analysis and evaluation frameworks\n- Build rollback triggers based on error rates and latency\n- Monitor and analyze canary performance metrics\n\n## When to use me\n\n- When you want to reduce risk of new deployments\n- When you need to validate changes with real production traffic\n- When deploying to large user bases where failures are costly\n- When you want data-driven deployment decisions\n- When implementing progressive delivery practices\n- When working with microservices architectures\n\n## Key Concepts\n\n### Traffic Splitting\n\n```yaml\n# Kubernetes Istio virtual service for canary routing\napiVersion: networking.istio.io\u002Fv1alpha3\nkind: VirtualService\nmetadata:\n  name: myapp\nspec:\n  hosts:\n    - myapp\n  http:\n    - route:\n        - destination:\n            host: myapp\n            subset: stable\n          weight: 90\n        - destination:\n            host: myapp\n            subset: canary\n          weight: 10\n```\n\n### Metrics-Based Routing\n\n```javascript\n\u002F\u002F Prometheus alert for canary analysis\n- alert: CanaryHighErrorRate\n  expr: |\n    rate(http_requests_total{service=\"canary\"}[5m]) \n    \u002F rate(http_requests_total{service=\"stable\"}[5m]) > 0.1\n  for: 5m\n  labels:\n    severity: critical\n  annotations:\n    summary: \"Canary error rate exceeds 10% of stable\"\n    description: \"Automated rollback recommended\"\n```\n\n### Phased Rollout\n\n1. **Initial**: 1-5% traffic to canary\n2. **Validation**: Monitor error rates and latency\n3. **Expansion**: Increase to 25%, 50%, 75%\n4. **Promotion**: Full 100% traffic\n5. **Cleanup**: Remove old version\n\n### Key Metrics to Monitor\n\n- **Error Rate**: Compare canary vs. stable\n- **Latency**: P50, P95, P99 response times\n- **Success Rate**: Request completion percentage\n- **Resource Usage**: CPU, memory, network\n- **Business Metrics**: Conversion rates, session duration\n- **Custom Metrics**: Domain-specific indicators\n\n### Rollback Triggers\n\n- Error rate exceeds 2x stable environment\n- P99 latency exceeds threshold (e.g., 500ms)\n- CPU or memory usage exceeds 80%\n- Custom business metric degradation\n- Manual override triggered\n",{"name":5,"license":15,"metadata":35,"description":7,"compatibility":26},{"audience":36,"category":24},"devops-engineer, platform-engineer","main","2ea764e153842704d24a2e9aa4170441a7f03081",".opencode\u002Fskills\u002Fcanary-releases","https:\u002F\u002Fgithub.com\u002FNeuralBlitz\u002FMito","https:\u002F\u002Fgithub.com\u002FNeuralBlitz","nuralnexus.org","Theoretical and Futuristic AI Nerd 🤓 ","2026-04-21 14:37:05",{"source":8,"skillName":5,"commands":46,"prompt":56,"zipAvailable":57},[47,50,53],{"tool":48,"command":49},"npx","npx skills add NeuralBlitz\u002FMito --skill canary-releases",{"tool":51,"command":52},"bunx","bunx skills add NeuralBlitz\u002FMito --skill canary-releases",{"tool":54,"command":55},"pnpm","pnpm dlx skills add NeuralBlitz\u002FMito --skill canary-releases","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FNeuralBlitz\u002FMito\u002Fblob\u002Fmain\u002F.opencode\u002Fskills\u002Fcanary-releases\u002FSKILL.md",true,[],[60,76,89,102,110,135],{"skillNo":61,"name":62,"nameZh":6,"description":63,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":64,"categories":65,"keywords":66,"publishedAt":30},"01M6HAZSAQK1S27CEZYAYJTQDX","wireless-communications","Wireless systems, mobile networks, and 5G\u002F6G","https:\u002F\u002Fgithub.com\u002FNeuralBlitz\u002FMito\u002Fblob\u002Fmain\u002F.opencode\u002Fskills\u002Fwireless-communications\u002FSKILL.md",[],[67,68,69,70,71,72,73,74,26,75],"communications","wireless communications","wireless","systems","engineering","networks","5G","students","mobile",{"skillNo":77,"name":78,"nameZh":6,"description":79,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":80,"categories":81,"keywords":82,"publishedAt":30},"01M6HAZFX6E8NK3WZWDX5YCKYY","websockets","WebSocket implementation and best practices","https:\u002F\u002Fgithub.com\u002FNeuralBlitz\u002FMito\u002Fblob\u002Fmain\u002F.opencode\u002Fskills\u002Fwebassembly\u002Fwebsockets\u002FSKILL.md",[],[78,83,84,85,26,86,87,88],"websocket implementation","time","implementation","real-time","websocket","best practices",{"skillNo":90,"name":91,"nameZh":6,"description":92,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":93,"categories":94,"keywords":95,"publishedAt":30},"01M6HAZ6DAXBQ7QHXXM1EM7715","vulnerability-auditing","Vulnerability assessment and auditing","https:\u002F\u002Fgithub.com\u002FNeuralBlitz\u002FMito\u002Fblob\u002Fmain\u002F.opencode\u002Fskills\u002Fvulnerability-auditing\u002FSKILL.md",[],[96,97,98,99,26,100,101],"vulnerability","vulnerability auditing","security","vulnerability assessment","cybersecurity","assessment",{"skillNo":103,"name":104,"nameZh":6,"description":105,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":106,"categories":107,"keywords":108,"publishedAt":30},"01M6HAZ3FKF3CS9Z3J96RVE2ZE","vulnerability-assessment","Finding and assessing security vulnerabilities","https:\u002F\u002Fgithub.com\u002FNeuralBlitz\u002FMito\u002Fblob\u002Fmain\u002F.opencode\u002Fskills\u002Fvue\u002Fvulnerability-assessment\u002FSKILL.md",[],[99,96,101,98,109,26],"vulnerabilities",{"skillNo":111,"name":112,"nameZh":6,"description":113,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":114,"categories":115,"keywords":126,"publishedAt":30},"01M6HAYSHM6HKRKEHFP0SGZQX7","vlsi-design","Very-Large-Scale Integration circuit design and semiconductor engineering","https:\u002F\u002Fgithub.com\u002FNeuralBlitz\u002FMito\u002Fblob\u002Fmain\u002F.opencode\u002Fskills\u002Fvlsi-design\u002FSKILL.md",[116,121],{"categoryNo":117,"categoryName":118,"taxonomyType":119,"taxonomyTypeDesc":120},"01JBSEEDCAT000000000000015","视觉设计","SCENARIO","使用场景",{"categoryNo":122,"categoryName":123,"taxonomyType":124,"taxonomyTypeDesc":125},"01JBSEEDCAT000000000000032","设计师","PROFESSION","适用职业",[127,128,129,130,131,71,132,26,133,74,134],"vlsi design","VLSI","design","hardware","integration","computer","scale","circuit",{"skillNo":136,"name":137,"nameZh":6,"description":138,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":139,"categories":140,"keywords":141,"publishedAt":30},"01M6HAYPQ30FFE2JXD7WQJ8R6C","unsupervised","Unsupervised learning concepts","https:\u002F\u002Fgithub.com\u002FNeuralBlitz\u002FMito\u002Fblob\u002Fmain\u002F.opencode\u002Fskills\u002Fvisualization\u002Funsupervised\u002FSKILL.md",[],[137,142,26,143,144,145,146,147],"learning","intelligence","unsupervised learning","machine","concepts","machine-learning"]