What is autoscaling-configuration?

A configuration for automatically adding or removing computing capacity as demand, schedules, or other measurements change.

Use it to scale Kubernetes workloads, virtual machines, or serverless systems for traffic peaks, scheduled work, cost control, and batch processing.

It helps applications handle busy periods without permanently paying for their highest capacity.

autoscaling-configuration — Skill by aj-geddes/useful-ai-prompts

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent

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

Clone the repo

git clone --depth 1 https://github.com/aj-geddes/useful-ai-prompts

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/skills/aj-geddes/useful-ai-prompts/autoscaling-configuration/github.svg)](https://agentmods.dev/skills/aj-geddes/useful-ai-prompts/autoscaling-configuration)

Your own site

<a href="https://agentmods.dev/skills/aj-geddes/useful-ai-prompts/autoscaling-configuration"><img src="https://agentmods.dev/badge/skills/aj-geddes/useful-ai-prompts/autoscaling-configuration/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/skills/aj-geddes/useful-ai-prompts/autoscaling-configuration"><img src="https://agentmods.dev/badge/skills/aj-geddes/useful-ai-prompts/autoscaling-configuration.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 28 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 556 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits

Socket pass 15 Sept 2026
Snyk pass 15 Sept 2026

How audits are shown

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00028	$0.00556
Opus 5.5	$0.00011	$0.00222
Sonnet 5.5	$0.00006	$0.00111
Haiku 4.5	$0.00003	$0.00056

Measured 2mo ago against content hash 52a2efc54714, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

autoscaling-configuration scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/validate-config.sh), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/autoscaling-configuration/SKILL.md · 100 lines

How it starts

The opening of the file, as written. The whole thing — 100 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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	Kubernetes Horizontal Pod Autoscaler
AWS Auto Scaling	AWS Auto Scaling
Custom Metrics Autoscaling	Custom Metrics Autoscaling
Autoscaling Script	Autoscaling Script
Monitoring Autoscaling	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

Read the full file on GitHub · 100 lines

Files

What ships with it

7 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

2mo ago First seen · 100 lines · 28 tokens per session scan A 52a2efc54714

Subscribe to this mod's changes

autoscaling-configuration is a skill published in the GitHub repository aj-geddes/useful-ai-prompts (376 stars, last pushed 8mo ago), licensed MIT. It adds 28 tokens to every session and 556 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Cloud DevOps and cloud

autoscaling-configuration next to 6 skills from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
autoscaling-configurationaj-geddes/useful-ai-prompts	Skill	376	8mo ago	MIT	A	28	Claude Code, Codex
gke-compute-classesgoogle/skills	Skill	22k	yesterday	Apache-2.0	A	83	Claude Code, Codex
gke-reliabilitygoogle/skills	Skill	22k	yesterday	Apache-2.0	A	85	Claude Code, Codex
gke-workload-securitygoogle/skills	Skill	22k	yesterday	Apache-2.0	A	171	Claude Code, Codex
cloud-architectJeffallan/claude-skills	Skill	12k	7d ago	MIT	A	71	Claude Code
nemo-automodel-launcher-configNVIDIA/skills	Skill	3.9k	yesterday	Apache-2.0	A	30	Claude Code
azure-mgmt-botservice-dotnetmicrosoft/skills	Skill	3.2k	yesterday	MIT	A	78	Claude Code

autoscaling-configuration