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hpa-debug

Diagnose HorizontalPodAutoscaler failures in Kubernetes by analyzing status, metrics-server health, and scaling events.

225|28|Updated Mar 2, 2026
Search Tags:#devops#debugging#kubernetes#sre#autoscaling#hpa
One-click install
npx skills add https://github.com/scitix/siclaw --skill hpa-debug
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: hpa-debug
Source: https://github.com/scitix/siclaw/tree/main/skills/core/hpa-debug
Command: npx skills add https://github.com/scitix/siclaw --skill hpa-debug

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill helps you identify why your HorizontalPodAutoscaler (HPA) is not scaling your Kubernetes deployments as expected, whether it's due to issues with metrics, configuration, or resource requests.

Core Features & Use Cases

  • HPA Status Check: Verifies the current status and targets of your HPA.
  • Metrics Server Health: Assesses the health and availability of the metrics-server.
  • Resource Request Validation: Ensures that target pods have necessary resource requests defined for percentage-based scaling.
  • Event Analysis: Parses HPA events to pinpoint scaling decisions, errors, or limitations.
  • Use Case: When your application experiences increased traffic but the number of pods managed by an HPA remains static, this Skill will guide you through the diagnostic steps to find the bottleneck.

Quick Start

Use the hpa-debug skill to diagnose why the HorizontalPodAutoscaler named 'my-hpa' in the 'default' namespace is not scaling.

Frequently Asked Questions about hpa-debug

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
Why is my Kubernetes HorizontalPodAutoscaler not scaling pods under increased traffic?▼

Diagnosing HorizontalPodAutoscaler failures involves checking HPA status, metrics-server health, and scaling events. This skill identifies root causes like unavailable metrics, target mismatches, or missing resource requests on target containers.

How do I check if the metrics-server is causing my HPA scaling issues?▼

Checking metrics-server health is essential for HPA functionality. This skill assesses metrics-server availability and parses HPA events to determine if missing or delayed metrics are preventing your deployment from autoscaling.

Do I need resource requests defined for percentage-based HPA metrics?▼

Resource requests are required on target containers for percentage-based HPA metrics. This skill validates that your target pods have the necessary resource requests defined, ensuring the HorizontalPodAutoscaler can calculate scaling thresholds correctly.

How do I diagnose an HPA target mismatch in Kubernetes?▼

Diagnosing HPA target mismatches requires analyzing the current HPA status against deployment configurations. This skill verifies HPA targets and parses scaling events to identify configuration discrepancies causing the autoscaler to remain static.

What causes a Kubernetes HorizontalPodAutoscaler to remain static during high load?▼

A static HorizontalPodAutoscaler under load is typically caused by unavailable metrics, target mismatches, or missing container resource requests. This skill analyzes HPA events and metrics-server health to isolate the specific failure.

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