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az-aks-agentAZ AKS Agent 搜索

Agent Skill

az-aks-agent 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

1,008

周安装

42

GitHub Stars

61

下载量

336
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

3

许可证

MIT

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:az-aks-agent(AZ AKS Agent 搜索)
来源仓库:https://github.com/julianobarbosa/claude-code-skills
仓库路径:skills/az-aks-agent
安装命令:
npx skills add https://github.com/julianobarbosa/claude-code-skills --skill az-aks-agent
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/julianobarbosa/claude-code-skills --skill az-aks-agent

简介

az-aks-agent 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。

  • Azure AKS Agent CLI 工具,提供自然语言查询 Kubernetes 集群健康和配置的 AI 驱动诊断。
  • 通过 npx skills add 命令从指定 GitHub 仓库安装,需 Azure CLI 2.76+ 和扩展支持。
  • 安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写操作。
  • 适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

SKILL.md

Azure AKS Agent CLI Skill

Overview

The Agentic CLI for Azure Kubernetes Service (AKS) is an AI-powered troubleshooting and insights tool (currently in preview) that brings advanced diagnostics directly to your terminal. It allows you to ask natural language questions about your cluster's health, configuration, and issues without requiring deep Kubernetes expertise or knowledge of complex command syntax.

Primary Command: az aks agent

Quick Reference

Installation

# Prerequisites: Azure CLI version 2.76 or higher
az version

# Install the extension (takes 5-10 minutes)
az extension add --name aks-agent --debug

# Verify installation
az extension list
az aks agent --help

# Initialize LLM configuration (interactive wizard)
az aks agent-init

# Remove extension if needed
az extension remove --name aks-agent --debug

Basic Usage

# Get cluster credentials first
az aks get-credentials --resource-group <rg-name> --name <cluster-name>

# Start interactive troubleshooting
az aks agent -g <resource-group> -n <cluster-name>

# Ask a specific question
az aks agent -g <resource-group> -n <cluster-name> --query "What's wrong with my cluster?"

# Non-interactive mode (batch processing)
az aks agent -g <resource-group> -n <cluster-name> --no-interactive --query "Check pod health"

Workflow Decision Tree

What do you need to do?
├── Cluster Health Check?
│   └── Use: az aks agent --query "What's the health status of my cluster?"
├── Troubleshoot Pod Issues?
│   └── Use: az aks agent --query "Why are my pods failing?"
├── Networking Problems?
│   └── Use: az aks agent --query "Diagnose networking issues"
├── Storage Issues?
│   └── Use: az aks agent --query "Check storage configuration"
├── Security/RBAC Issues?
│   └── Use: az aks agent --query "Review RBAC configuration"
├── Node Pool Problems?
│   └── Use: az aks agent --query "Check node pool health"
└── Configuration Review?
    └── Use: az aks agent --query "Review cluster configuration"

Command Reference

Core Commands

CommandDescription
az aks agentStart interactive AI-powered troubleshooting
az aks agent-initInitialize LLM provider configuration
az aks agent --helpShow help and available options

Command Parameters

ParameterDescriptionDefault
-g, --resource-groupResource group nameRequired
-n, --nameAKS cluster nameRequired
--api-keyLLM API keyFrom env or config
--config-fileConfig file path~/.azure/aksAgent.config
--max-stepsMax investigation steps10
--modelLLM model specificationFrom config
--no-interactiveRun in batch modefalse
--show-tool-outputDisplay tool call outputsfalse
--refresh-toolsetsRefresh toolsets statusfalse

LLM Model Specifications

# Azure OpenAI
--model "azure/gpt-4o"
--model "azure/gpt-4o-mini"

# OpenAI
--model "gpt-4o"
--model "gpt-4o-mini"

# Anthropic
--model "anthropic/claude-sonnet-4"
--model "anthropic/claude-3-5-sonnet"

# Gemini
--model "gemini/gemini-pro"

Configuration

Environment Variables

# Azure OpenAI API Key
export AZURE_API_KEY="your-azure-openai-key"

# OpenAI API Key
export OPENAI_API_KEY="your-openai-key"

# Anthropic API Key
export ANTHROPIC_API_KEY="your-anthropic-key"

Config File Structure (~/.azure/aksAgent.config)

# Azure OpenAI Configuration
llm_provider: azure
azure_api_base: https://<your-endpoint>.openai.azure.com/
azure_api_version: 2025-04-01-preview
model: gpt-4o

# OR OpenAI Configuration
llm_provider: openai
model: gpt-4o

# OR Anthropic Configuration
llm_provider: anthropic
model: claude-sonnet-4

Azure OpenAI Requirements

  • Deployment name: Must match model name
  • Minimum TPM: 1,000,000+ (Tokens Per Minute)
  • Minimum context size: 128,000+ tokens
  • API Base Format: https://{endpoint}.openai.azure.com/ (NOT AI Foundry URI)

Common Use Cases

Cluster Health Analysis

# General health check
az aks agent -g myRG -n myCluster --query "What's the overall health of my cluster?"

# Node status
az aks agent -g myRG -n myCluster --query "Are all nodes healthy and ready?"

# Resource utilization
az aks agent -g myRG -n myCluster --query "Show me resource utilization across nodes"

Pod Troubleshooting

# Failed pods analysis
az aks agent -g myRG -n myCluster --query "Why are pods in CrashLoopBackOff?"

# Pending pods
az aks agent -g myRG -n myCluster --query "Why are some pods stuck in Pending state?"

# OOMKilled pods
az aks agent -g myRG -n myCluster --query "Investigate OOMKilled containers"

Networking Issues

# Network policy review
az aks agent -g myRG -n myCluster --query "Are there network policies blocking traffic?"

# DNS troubleshooting
az aks agent -g myRG -n myCluster --query "Diagnose DNS resolution issues"

# Service connectivity
az aks agent -g myRG -n myCluster --query "Why can't pods reach external services?"

Storage Troubleshooting

# PVC issues
az aks agent -g myRG -n myCluster --query "Why are PersistentVolumeClaims pending?"

# Storage class review
az aks agent -g myRG -n myCluster --query "Review storage class configuration"

Security Analysis

# RBAC review
az aks agent -g myRG -n myCluster --query "Are RBAC permissions configured correctly?"

# Security best practices
az aks agent -g myRG -n myCluster --query "What security improvements do you recommend?"

AKS Events Reference

Viewing Cluster Events

# Get cluster credentials first
az aks get-credentials --resource-group $RESOURCE_GROUP --name $AKS_CLUSTER

# List all events
kubectl get events

# Filter by namespace
kubectl get events --namespace default

# Watch auto-repair events
kubectl get events --field-selector=source=aks-auto-repair --watch

# Detailed pod events
kubectl describe pod $POD_NAME

Event Types

TypeDescription
NormalRoutine operations and expected activities
WarningPotentially problematic situations requiring attention

Common Event Reasons

ReasonDescription
FailedSchedulingPod failed to be scheduled on a node
CrashLoopBackOffContainer is in a restart loop
ScheduledPod successfully assigned to a node
PulledContainer image successfully pulled
CreatedContainer created
StartedContainer started
OOMKilledContainer killed due to out of memory

Event Fields

FieldDescription
typeWarning or Normal
reasonShort reason code
messageHuman-readable description
namespaceKubernetes namespace
firstSeenFirst observation timestamp
lastSeenMost recent observation
objectAssociated Kubernetes object

Best Practices

Effective Query Strategies

  1. Start broad, then narrow # Start with general health "What's wrong with my cluster?" # Then focus on specific issues "Why are pods in namespace X failing?"
  2. Provide context about symptoms "Pods are restarting frequently in the production namespace" "Services are experiencing intermittent timeouts"
  3. Ask for specific recommendations "What changes do you recommend to improve cluster performance?" "How can I fix the networking issues you identified?"
  4. Request historical analysis "What patterns do you see in recent pod failures?" "Have there been any unusual events in the last 24 hours?"

Security Considerations

  • Ensure proper RBAC permissions are configured
  • Use Azure AD integration for authentication
  • Follow principle of least privilege
  • Audit command usage through Azure activity logs
  • Service account tokens for automation

Integration Tips

  1. Combine with traditional monitoring: Use alongside Azure Monitor and Container Insights
  2. Proactive monitoring: Run health checks regularly
  3. Document findings: Save important diagnostic outputs
  4. Enable Container Insights: For events beyond 1-hour retention

Troubleshooting the Agent

Installation Issues

# Verify Azure CLI version
az version

# Upgrade Azure CLI if needed
az upgrade

# Force reinstall extension
az extension remove --name aks-agent
az extension add --name aks-agent --debug

Authentication Issues

# Verify Azure login
az account show

# Re-authenticate
az login

# Check subscription
az account set --subscription <subscription-id>

LLM Connection Issues

# Reinitialize LLM configuration
az aks agent-init

# Check API key environment variable
echo $AZURE_API_KEY

# Test with explicit API key
az aks agent -g myRG -n myCluster --api-key "your-key"

Rate Limiting

  • Symptom: Slow responses or errors
  • Solution: Increase TPM quota in Azure OpenAI deployment
  • Minimum recommended: 1,000,000 TPM

Important Notes

  1. Preview Feature: This is currently in preview with limited warranty coverage
  2. Not for Production Critical: Not recommended for production-critical decision making
  3. Event Retention: Kubernetes events only persist for 1 hour by default
  4. Context Window: Requires 128,000+ token context for optimal performance
  5. Authentication: Always authenticate with az login before using

Resources

References

Core References

  • references/cli-commands.md - Complete CLI command reference
  • references/troubleshooting.md - Extended troubleshooting guide
  • references/examples.md - Practical usage examples

Diagnostics & Monitoring

  • references/diagnostics.md - AKS Diagnose and Solve Problems guide
  • references/monitoring.md - Comprehensive AKS monitoring guide
  • references/control-plane-metrics.md - Control plane metrics (API Server, etcd)

Troubleshooting Guides

  • references/kubelet-logs.md - Kubelet logs access and analysis
  • references/memory-saturation.md - Memory saturation identification and resolution
  • references/node-auto-repair.md - Node auto-repair process and monitoring
  • references/api-server-etcd.md - API server and etcd troubleshooting

External Documentation

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

04

需要参考平台分布和安装热度时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Claude Code

29.97%
按下载量换算101

OpenCode

21.63%
按下载量换算73

Gemini CLI

19.55%
按下载量换算66

Antigravity

13.95%
按下载量换算47

Codex

7.22%
按下载量换算24

Cursor

3.51%
按下载量换算12

安全审计

Gen Agent Trust Hub

可疑

Socket

通过

Snyk

未通过

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。

来源信息

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