Autoscaling Configuration
This handles autoscaling across Kubernetes HPA, AWS Auto Scaling groups, and custom metrics implementations. You get YAML configs for horizontal pod autoscalers with CPU and memory targets, plus monitoring setups to track scaling events. It covers the basics well: min/max replica bounds, cooldown periods, multi-metric strategies. The best practices section is solid on avoiding single-replica minimums and aggressive scaling that causes flapping. Useful if you're setting up autoscaling from scratch or standardizing configurations across environments. The reference guides break things down by platform, which saves you from hunting through documentation when you need to scale VMs differently than containers.
- skills.sh installs
- 456
- GitHub stars
- 379
- last updated
- Aug 21, 2026
Install
$ npx -y skills add aj-geddes/useful-ai-prompts --skill autoscaling-configuration --agent claude-codeInstalls into .claude/skills of the current project.
Files
Autoscaling Configuration
Table of Contents
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:
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- Repository
- github.com/aj-geddes/useful-ai-prompts
- Categories
- DevOps & CI/CD, AI & Agent Building, Cloud & Infrastructure
- First seen
- Jun 3, 2026
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