autoscaling-configuration

@aj-geddes · 收录于 5 天前 · 上游提交 4 个月前

Configure autoscaling for Kubernetes, VMs, and serverless workloads based on metrics, schedules, and custom indicators.

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适合你，如果管理着需要动态伸缩的云上工作负载

/ 下载安装

https://github.com/aj-geddes/useful-ai-prompts/tree/main/skills/autoscaling-configuration ↗

/ 通过 npx 安装 校验哈希

npx oh-my-skill add aj-geddes/useful-ai-prompts/autoscaling-configuration

/ 通过 bash 安装

curl -fsSL https://oh-my-skill.com/install.sh | bash -s -- aj-geddes/useful-ai-prompts/autoscaling-configuration

/ 已经装过?验证本机副本,不用重装

npx oh-my-skill verify aj-geddes/useful-ai-prompts/autoscaling-configuration

安装目标可用 --agent / --scope 或 --to 明确指定;省略时只会在唯一已存在的 agent 目录上自动选择,零命中或多命中会停止并提示。content_hash 缺失或不一致均拒装。

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~407最小装载

~1.6K含声明引用

~1.7K文本包总量

索引托管

怎么用

商店整理自技能原文 · 版本 3f5182c · 表述以原文为准

它做什么

安装后，Claude 可以根据你的需求生成或修改自动扩缩容配置，例如 Kubernetes HPA、AWS Auto Scaling 等，基于 CPU、内存等指标或时间计划。

什么时候触发

当你提到需要配置自动扩缩容、调整资源弹性，或者要求设置基于指标或时间的扩缩规则时触发。

装好后可以这样说

将生成对应的YAML配置。

会创建基于时间的扩缩策略。

生成自定义指标自动扩缩配置。

技能原文 SKILL.md作者撰写 · MIT · 3f5182c

Autoscaling Configuration

[Overview](#overview)
[When to Use](#when-to-use)
[Quick Start](#quick-start)
[Reference Guides](#reference-guides)
[Best Practices](#best-practices)

Overview

Implement autoscaling strategies to automatically adjust resource capacity based on demand, ensuring cost efficiency while maintaining performance and availability.

When to Use

Traffic-driven workload scaling
Time-based scheduled scaling
Resource utilization optimization
Cost reduction
High-traffic event handling
Batch processing optimization
Database connection pooling

Quick Start

Minimal working example:

# hpa-configuration.yaml
apiVersion: autoscaling/v2
kind: HorizontalPodAutoscaler
metadata:
  name: myapp-hpa
  namespace: production
spec:
  scaleTargetRef:
    apiVersion: apps/v1
    kind: Deployment
    name: myapp
  minReplicas: 2
  maxReplicas: 20
  metrics:
    - type: Resource
      resource:
        name: cpu
        target:
          type: Utilization
          averageUtilization: 70
    - type: Resource
      resource:
        name: memory
        target:
          type: Utilization
// ... (see reference guides for full implementation)

Reference Guides

Detailed implementations in the references/ directory:

| Guide | Contents | |---|---| | [Kubernetes Horizontal Pod Autoscaler](references/kubernetes-horizontal-pod-autoscaler.md) | Kubernetes Horizontal Pod Autoscaler | | [AWS Auto Scaling](references/aws-auto-scaling.md) | AWS Auto Scaling | | [Custom Metrics Autoscaling](references/custom-metrics-autoscaling.md) | Custom Metrics Autoscaling | | [Autoscaling Script](references/autoscaling-script.md) | Autoscaling Script | | [Monitoring Autoscaling](references/monitoring-autoscaling.md) | Monitoring Autoscaling |

Best Practices

✅ DO

Set appropriate min/max replicas
Monitor metric aggregation window
Implement cooldown periods
Use multiple metrics
Test scaling behavior
Monitor scaling events
Plan for peak loads
Implement fallback strategies

❌ DON'T

Set min replicas to 1
Scale too aggressively
Ignore cooldown periods
Use single metric only
Forget to test scaling
Scale below resource needs
Neglect monitoring
Deploy without capacity tests

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