[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6G19AV5NC5ZWEH2EJWMPRM0":3,"skill-same:01M6G19AV5NC5ZWEH2EJWMPRM0":71},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":15,"categories":16,"keywords":22,"publishedAt":35,"linkOnly":36,"markdownContent":37,"markdownBody":38,"frontMatter":39,"refName":40,"commitSha":41,"skillDirectory":42,"forksCount":43,"repositoryHtmlUrl":44,"repositoryHomepageUrl":6,"ownerHtmlUrl":45,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":46,"install":47,"resources":60},"01M6G19AV5NC5ZWEH2EJWMPRM0","k8s-autoscaling",null,"Configure Kubernetes autoscaling with HPA, VPA, and KEDA. Use for horizontal\u002Fvertical pod autoscaling, event-driven scaling, and capacity management.","kbarbel640-del\u002Fskills","kbarbel640-del","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F255315490?v=4","01M6CJPPQGCCESXMG3K7BBGQ5J","01M6CJPPX2PB2BCZERFVM2C2B3",1,"MIT","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Frohitg00\u002Fk8-autoscaling\u002FSKILL.md",[17],{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000011","运维与部署","SCENARIO","使用场景",[23,24,25,26,27,28,29,30,31,32,33,34],"k8s","k8s autoscaling","kubernetes","capacity","configure","management","use","scaling","driven","event-driven","event","with","2026-11-10 10:12:30",false,"---\nname: k8s-autoscaling\ndescription: Configure Kubernetes autoscaling with HPA, VPA, and KEDA. Use for horizontal\u002Fvertical pod autoscaling, event-driven scaling, and capacity management.\n---\n\n# Kubernetes Autoscaling\n\nComprehensive autoscaling using HPA, VPA, and KEDA with kubectl-mcp-server tools.\n\n## Quick Reference\n\n### HPA (Horizontal Pod Autoscaler)\n\nBasic CPU-based scaling:\n```yaml\napiVersion: autoscaling\u002Fv2\nkind: HorizontalPodAutoscaler\nmetadata:\n  name: my-app-hpa\nspec:\n  scaleTargetRef:\n    apiVersion: apps\u002Fv1\n    kind: Deployment\n    name: my-app\n  minReplicas: 2\n  maxReplicas: 10\n  metrics:\n  - type: Resource\n    resource:\n      name: cpu\n      target:\n        type: Utilization\n        averageUtilization: 70\n```\n\nApply and verify:\n```\napply_manifest(hpa_yaml, namespace)\nget_hpa(namespace)\n```\n\n### VPA (Vertical Pod Autoscaler)\n\nRight-size resource requests:\n```yaml\napiVersion: autoscaling.k8s.io\u002Fv1\nkind: VerticalPodAutoscaler\nmetadata:\n  name: my-app-vpa\nspec:\n  targetRef:\n    apiVersion: apps\u002Fv1\n    kind: Deployment\n    name: my-app\n  updatePolicy:\n    updateMode: \"Auto\"\n```\n\n## KEDA (Event-Driven Autoscaling)\n\n### Detect KEDA Installation\n```\nkeda_detect_tool()\n```\n\n### List ScaledObjects\n```\nkeda_scaledobjects_list_tool(namespace)\nkeda_scaledobject_get_tool(name, namespace)\n```\n\n### List ScaledJobs\n```\nkeda_scaledjobs_list_tool(namespace)\n```\n\n### Trigger Authentication\n```\nkeda_triggerauths_list_tool(namespace)\nkeda_triggerauth_get_tool(name, namespace)\n```\n\n### KEDA-Managed HPAs\n```\nkeda_hpa_list_tool(namespace)\n```\n\nSee [KEDA-TRIGGERS.md](KEDA-TRIGGERS.md) for trigger configurations.\n\n## Common KEDA Triggers\n\n### Queue-Based Scaling (AWS SQS)\n```yaml\napiVersion: keda.sh\u002Fv1alpha1\nkind: ScaledObject\nmetadata:\n  name: sqs-scaler\nspec:\n  scaleTargetRef:\n    name: queue-processor\n  minReplicaCount: 0  # Scale to zero!\n  maxReplicaCount: 100\n  triggers:\n  - type: aws-sqs-queue\n    metadata:\n      queueURL: https:\u002F\u002Fsqs.region.amazonaws.com\u002F...\n      queueLength: \"5\"\n```\n\n### Cron-Based Scaling\n```yaml\ntriggers:\n- type: cron\n  metadata:\n    timezone: America\u002FNew_York\n    start: 0 8 * * 1-5   # 8 AM weekdays\n    end: 0 18 * * 1-5    # 6 PM weekdays\n    desiredReplicas: \"10\"\n```\n\n### Prometheus Metrics\n```yaml\ntriggers:\n- type: prometheus\n  metadata:\n    serverAddress: http:\u002F\u002Fprometheus:9090\n    metricName: http_requests_total\n    query: sum(rate(http_requests_total{app=\"myapp\"}[2m]))\n    threshold: \"100\"\n```\n\n## Scaling Strategies\n\n| Strategy | Tool | Use Case |\n|----------|------|----------|\n| CPU\u002FMemory | HPA | Steady traffic patterns |\n| Custom metrics | HPA v2 | Business metrics |\n| Event-driven | KEDA | Queue processing, cron |\n| Vertical | VPA | Right-size requests |\n| Scale to zero | KEDA | Cost savings, idle workloads |\n\n## Cost-Optimized Autoscaling\n\n### Scale to Zero with KEDA\nReduce costs for idle workloads:\n```\nkeda_scaledobjects_list_tool(namespace)\n# ScaledObjects with minReplicaCount: 0 can scale to zero\n```\n\n### Right-Size with VPA\nGet recommendations and apply:\n```\nget_resource_recommendations(namespace)\n# Apply VPA recommendations\n```\n\n### Predictive Scaling\nUse cron triggers for known patterns:\n```yaml\n# Scale up before traffic spike\ntriggers:\n- type: cron\n  metadata:\n    start: 0 7 * * *  # 7 AM\n    end: 0 9 * * *    # 9 AM\n    desiredReplicas: \"20\"\n```\n\n## Multi-Cluster Autoscaling\n\nConfigure KEDA across clusters:\n```\nkeda_scaledobjects_list_tool(namespace, context=\"production\")\nkeda_scaledobjects_list_tool(namespace, context=\"staging\")\n```\n\n## Troubleshooting\n\n### HPA Not Scaling\n```\nget_hpa(namespace)\nget_pod_metrics(name, namespace)  # Metrics available?\ndescribe_pod(name, namespace)     # Resource requests set?\n```\n\n### KEDA Not Triggering\n```\nkeda_scaledobject_get_tool(name, namespace)  # Check status\nget_events(namespace)                        # Check events\n```\n\n### Common Issues\n\n| Symptom | Check | Resolution |\n|---------|-------|------------|\n| HPA unknown | Metrics server | Install metrics-server |\n| KEDA no scale | Trigger auth | Check TriggerAuthentication |\n| VPA not updating | Update mode | Set updateMode: Auto |\n| Scale down slow | Stabilization | Adjust stabilizationWindowSeconds |\n\n## Best Practices\n\n1. **Always Set Resource Requests**\n   - HPA requires requests to calculate utilization\n\n2. **Use Multiple Metrics**\n   - Combine CPU + custom metrics for accuracy\n\n3. **Stabilization Windows**\n   - Prevent flapping with scaleDown stabilization\n\n4. **Scale to Zero Carefully**\n   - Consider cold start time\n   - Use activation threshold\n\n## Related Skills\n- [k8s-cost](..\u002Fk8s-cost\u002FSKILL.md) - Cost optimization\n- [k8s-troubleshoot](..\u002Fk8s-troubleshoot\u002FSKILL.md) - Debug scaling issues\n","# Kubernetes Autoscaling\n\nComprehensive autoscaling using HPA, VPA, and KEDA with kubectl-mcp-server tools.\n\n## Quick Reference\n\n### HPA (Horizontal Pod Autoscaler)\n\nBasic CPU-based scaling:\n```yaml\napiVersion: autoscaling\u002Fv2\nkind: HorizontalPodAutoscaler\nmetadata:\n  name: my-app-hpa\nspec:\n  scaleTargetRef:\n    apiVersion: apps\u002Fv1\n    kind: Deployment\n    name: my-app\n  minReplicas: 2\n  maxReplicas: 10\n  metrics:\n  - type: Resource\n    resource:\n      name: cpu\n      target:\n        type: Utilization\n        averageUtilization: 70\n```\n\nApply and verify:\n```\napply_manifest(hpa_yaml, namespace)\nget_hpa(namespace)\n```\n\n### VPA (Vertical Pod Autoscaler)\n\nRight-size resource requests:\n```yaml\napiVersion: autoscaling.k8s.io\u002Fv1\nkind: VerticalPodAutoscaler\nmetadata:\n  name: my-app-vpa\nspec:\n  targetRef:\n    apiVersion: apps\u002Fv1\n    kind: Deployment\n    name: my-app\n  updatePolicy:\n    updateMode: \"Auto\"\n```\n\n## KEDA (Event-Driven Autoscaling)\n\n### Detect KEDA Installation\n```\nkeda_detect_tool()\n```\n\n### List ScaledObjects\n```\nkeda_scaledobjects_list_tool(namespace)\nkeda_scaledobject_get_tool(name, namespace)\n```\n\n### List ScaledJobs\n```\nkeda_scaledjobs_list_tool(namespace)\n```\n\n### Trigger Authentication\n```\nkeda_triggerauths_list_tool(namespace)\nkeda_triggerauth_get_tool(name, namespace)\n```\n\n### KEDA-Managed HPAs\n```\nkeda_hpa_list_tool(namespace)\n```\n\nSee [KEDA-TRIGGERS.md](KEDA-TRIGGERS.md) for trigger configurations.\n\n## Common KEDA Triggers\n\n### Queue-Based Scaling (AWS SQS)\n```yaml\napiVersion: keda.sh\u002Fv1alpha1\nkind: ScaledObject\nmetadata:\n  name: sqs-scaler\nspec:\n  scaleTargetRef:\n    name: queue-processor\n  minReplicaCount: 0  # Scale to zero!\n  maxReplicaCount: 100\n  triggers:\n  - type: aws-sqs-queue\n    metadata:\n      queueURL: https:\u002F\u002Fsqs.region.amazonaws.com\u002F...\n      queueLength: \"5\"\n```\n\n### Cron-Based Scaling\n```yaml\ntriggers:\n- type: cron\n  metadata:\n    timezone: America\u002FNew_York\n    start: 0 8 * * 1-5   # 8 AM weekdays\n    end: 0 18 * * 1-5    # 6 PM weekdays\n    desiredReplicas: \"10\"\n```\n\n### Prometheus Metrics\n```yaml\ntriggers:\n- type: prometheus\n  metadata:\n    serverAddress: http:\u002F\u002Fprometheus:9090\n    metricName: http_requests_total\n    query: sum(rate(http_requests_total{app=\"myapp\"}[2m]))\n    threshold: \"100\"\n```\n\n## Scaling Strategies\n\n| Strategy | Tool | Use Case |\n|----------|------|----------|\n| CPU\u002FMemory | HPA | Steady traffic patterns |\n| Custom metrics | HPA v2 | Business metrics |\n| Event-driven | KEDA | Queue processing, cron |\n| Vertical | VPA | Right-size requests |\n| Scale to zero | KEDA | Cost savings, idle workloads |\n\n## Cost-Optimized Autoscaling\n\n### Scale to Zero with KEDA\nReduce costs for idle workloads:\n```\nkeda_scaledobjects_list_tool(namespace)\n# ScaledObjects with minReplicaCount: 0 can scale to zero\n```\n\n### Right-Size with VPA\nGet recommendations and apply:\n```\nget_resource_recommendations(namespace)\n# Apply VPA recommendations\n```\n\n### Predictive Scaling\nUse cron triggers for known patterns:\n```yaml\n# Scale up before traffic spike\ntriggers:\n- type: cron\n  metadata:\n    start: 0 7 * * *  # 7 AM\n    end: 0 9 * * *    # 9 AM\n    desiredReplicas: \"20\"\n```\n\n## Multi-Cluster Autoscaling\n\nConfigure KEDA across clusters:\n```\nkeda_scaledobjects_list_tool(namespace, context=\"production\")\nkeda_scaledobjects_list_tool(namespace, context=\"staging\")\n```\n\n## Troubleshooting\n\n### HPA Not Scaling\n```\nget_hpa(namespace)\nget_pod_metrics(name, namespace)  # Metrics available?\ndescribe_pod(name, namespace)     # Resource requests set?\n```\n\n### KEDA Not Triggering\n```\nkeda_scaledobject_get_tool(name, namespace)  # Check status\nget_events(namespace)                        # Check events\n```\n\n### Common Issues\n\n| Symptom | Check | Resolution |\n|---------|-------|------------|\n| HPA unknown | Metrics server | Install metrics-server |\n| KEDA no scale | Trigger auth | Check TriggerAuthentication |\n| VPA not updating | Update mode | Set updateMode: Auto |\n| Scale down slow | Stabilization | Adjust stabilizationWindowSeconds |\n\n## Best Practices\n\n1. **Always Set Resource Requests**\n   - HPA requires requests to calculate utilization\n\n2. **Use Multiple Metrics**\n   - Combine CPU + custom metrics for accuracy\n\n3. **Stabilization Windows**\n   - Prevent flapping with scaleDown stabilization\n\n4. **Scale to Zero Carefully**\n   - Consider cold start time\n   - Use activation threshold\n\n## Related Skills\n- [k8s-cost](..\u002Fk8s-cost\u002FSKILL.md) - Cost optimization\n- [k8s-troubleshoot](..\u002Fk8s-troubleshoot\u002FSKILL.md) - Debug scaling issues\n",{"name":5,"description":7},"main","e7e336ac628c3e3bd771aff1aaa469c93778f94a","skills\u002Frohitg00\u002Fk8-autoscaling",0,"https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del","2026-08-23 22:39:37",{"source":8,"skillName":5,"commands":48,"prompt":58,"zipAvailable":59},[49,52,55],{"tool":50,"command":51},"npx","npx skills add kbarbel640-del\u002Fskills --skill k8s-autoscaling",{"tool":53,"command":54},"bunx","bunx skills add kbarbel640-del\u002Fskills --skill k8s-autoscaling",{"tool":56,"command":57},"pnpm","pnpm dlx skills add kbarbel640-del\u002Fskills --skill k8s-autoscaling","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Frohitg00\u002Fk8-autoscaling\u002FSKILL.md",true,[61,67],{"path":62,"resourceType":63,"resourceTypeDesc":64,"sizeBytes":65,"sourceHtmlUrl":66},"_meta.json","REFERENCE","参考文档",285,"https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Frohitg00\u002Fk8-autoscaling\u002F_meta.json",{"path":68,"resourceType":63,"resourceTypeDesc":64,"sizeBytes":69,"sourceHtmlUrl":70},"KEDA-TRIGGERS.md",4597,"https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Frohitg00\u002Fk8-autoscaling\u002FKEDA-TRIGGERS.md",[72,102,128,149,155,175],{"skillNo":73,"name":74,"nameZh":6,"description":75,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":76,"categories":77,"keywords":83,"publishedAt":35},"01M6G8J55967D6281ACMKAKTEQ","crowd-prompting","A marketplace where AI agents improve prompts, system instructions, tool descriptions, and other text-based content with domain expertise from real-world operations — and earn tokens for valuable contributions.","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fzzadrian\u002Fcrowd-prompting\u002FSKILL.md",[78],{"categoryNo":79,"categoryName":80,"taxonomyType":81,"taxonomyTypeDesc":82},"01JBSEEDCAT000000000000036","内容创作者","PROFESSION","适用职业",[84,85,86,34,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101],"crowd prompting","prompting","api","tokens","domain","world","prompts","operations","instructions","text","tool","system","improve","productivity","marketplace","https","content","ai agents",{"skillNo":103,"name":104,"nameZh":6,"description":105,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":106,"categories":107,"keywords":111,"publishedAt":35},"01M6G8J0PKPAYVET6BWE8W4C26","dilemm-ai","Compete in DilemmAI, the prisoner's dilemma AI arena at dilemm.ai. Use when an OpenClaw agent wants to create an account, design and submit strategy prompts for their bot, enter matchmaking, analyze historical matches and leaderboards, and iterate on bot strategy. Requires headless browser automation (no API available yet).","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fzyori\u002Fdilemm-ai\u002FSKILL.md",[108],{"categoryNo":109,"categoryName":110,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000023","Skill与智能体开发",[112,86,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,90,29],"dilemm ai","arena","analyze","browser","openclaw agent","create","automation","browser automation","bot","openclaw","design","strategy","headless","compete","submit","matchmaking",{"skillNo":129,"name":130,"nameZh":6,"description":131,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":132,"categories":133,"keywords":137,"publishedAt":35},"01M6G8HWAF3K9SW7NP3Z83CPJ6","arxiv-paper-reviews","Interact with arXiv Crawler API to fetch papers, read reviews, and submit comments. Use when working with arXiv papers, fetching paper lists by date\u002Fcategory\u002Finterest, viewing paper details with comments, or submitting paper reviews via API at http:\u002F\u002F150.158.152.82:8000.","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fzxrys\u002Fweak-accept\u002FSKILL.md",[134],{"categoryNo":135,"categoryName":136,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000021","资料检索与研究",[138,139,140,141,142,143,144,34,145,126,29,146,86,147,148],"arxiv paper reviews","reviews","arxiv","paper","crawler","papers","comments","fetch","read","http","via",{"skillNo":150,"name":130,"nameZh":6,"description":131,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":151,"categories":152,"keywords":154,"publishedAt":35},"01M6G8HQJ7N7WMY6YV7D7SSJ16","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fzxrys\u002Farxiv-paper-reviews\u002FSKILL.md",[153],{"categoryNo":135,"categoryName":136,"taxonomyType":20,"taxonomyTypeDesc":21},[141,140,139,138,148,143,144,34,142,126,29,145,146,86,147],{"skillNo":156,"name":157,"nameZh":6,"description":158,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":159,"categories":160,"keywords":161,"publishedAt":35},"01M6G8HM95Y64JNVFC2HN4E2BG","git-summary","Get a quick summary of the current Git repository including status, recent commits, branches, and contributors.","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fzweack\u002Fgit-summary\u002FSKILL.md",[],[162,163,164,165,166,167,168,169,170,171,172,173,174],"git","summary","git summary","commits","repository","win32","status","linux","contributors","true","quick","get","branches",{"skillNo":176,"name":177,"nameZh":6,"description":178,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":179,"categories":180,"keywords":185,"publishedAt":35},"01M6G8HGEGF05CNEJCGVYFSC4R","agent-constitution","Interact with AgentConstitution governance contracts on Base Sepolia. Check compliance, read rules, log actions, query governance state.","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fztsalexey\u002Fagent-constitution\u002FSKILL.md",[181,182],{"categoryNo":109,"categoryName":110,"taxonomyType":20,"taxonomyTypeDesc":21},{"categoryNo":183,"categoryName":184,"taxonomyType":81,"taxonomyTypeDesc":82},"01JBSEEDCAT000000000000037","律师与法务",[186,187,188,189,34,190,191,40,192,146,193,194,195,196,197,99,198,199,200],"agent constitution","constitution","contracts","tree","query","base","log","check","Rules","projects","compliance","actions","state","governance","github"]