Individual skill
castai-performance-tuning
Tune CAST AI node and workload autoscaling against application SLOs, scheduling constraints, and recommendation confidence. Use when optimization causes latency, disruption, slow provisioning, or unstable replica and resource behavior. Trigger with: "tune CAST AI performance", "stabilize CAST AI autoscaling", "fix CAST AI scaling latency".
plugins/saas-packs/castai-pack/skills/castai-performance-tuning/SKILL.md
Source commit 0500b275e963c027f6b410e8c49c0446945c574e
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- Last checked
- Nov 12, 2026
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- 2,916
- Repository last updated
- Nov 12, 2026
- License
- MIT
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- ai Repository topic
- automation Repository topic
- claude-code Repository topic
- devops Repository topic
- mcp Repository topic
- ai-agents Repository topic
- anthropic Repository topic
- claude-code-plugins Repository topic
- developer-tools Repository topic
- llm Repository topic
- saas Declared skill tag
- kubernetes Declared skill tag
- cast-ai Declared skill tag
- performance Declared skill tag
- autoscaling Declared skill tag
- devops Derived category
- devops-containers Derived category
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# CAST AI Performance Guardrail Tuning
## Overview
Tune from evidence across workload demand, requests, replicas, scheduling, and nodes. Keep vertical, horizontal, and node changes separate so a lower bill never hides degraded service.
## Prerequisites
- Workload SLOs, error budget, traffic profile, and representative observation window
- Effective scaling policy, annotations, HPA, PDB, node templates, and cluster limits
- Metrics-server and healthy CAST AI components
## Instructions
