azure-diagnostics
Debug and troubleshoot production issues on Azure. Covers Container Apps diagnostics, log analysis with KQL, health checks, and common issue resolution for image pulls, cold starts, and health probes. USE FOR: debug production issues, troubleshoot container apps, analyze logs with KQL, fix image pull failures, resolve cold start issues, investigate health probe failures, check resource health, view application logs, find root cause of errors DO NOT USE FOR: deploying applications (use azure-deploy), creating new resources (use azure-prepare), setting up monitoring (use azure-observability), cost optimization (use azure-cost-optimization)
Best use case
azure-diagnostics is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Debug and troubleshoot production issues on Azure. Covers Container Apps diagnostics, log analysis with KQL, health checks, and common issue resolution for image pulls, cold starts, and health probes. USE FOR: debug production issues, troubleshoot container apps, analyze logs with KQL, fix image pull failures, resolve cold start issues, investigate health probe failures, check resource health, view application logs, find root cause of errors DO NOT USE FOR: deploying applications (use azure-deploy), creating new resources (use azure-prepare), setting up monitoring (use azure-observability), cost optimization (use azure-cost-optimization)
Teams using azure-diagnostics should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/azure-diagnostics/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How azure-diagnostics Compares
| Feature / Agent | azure-diagnostics | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Debug and troubleshoot production issues on Azure. Covers Container Apps diagnostics, log analysis with KQL, health checks, and common issue resolution for image pulls, cold starts, and health probes. USE FOR: debug production issues, troubleshoot container apps, analyze logs with KQL, fix image pull failures, resolve cold start issues, investigate health probe failures, check resource health, view application logs, find root cause of errors DO NOT USE FOR: deploying applications (use azure-deploy), creating new resources (use azure-prepare), setting up monitoring (use azure-observability), cost optimization (use azure-cost-optimization)
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Azure Diagnostics
> **AUTHORITATIVE GUIDANCE — MANDATORY COMPLIANCE**
>
> This document is the **official source** for debugging and troubleshooting Azure production issues. Follow these instructions to diagnose and resolve common Azure service problems systematically.
## Triggers
Activate this skill when user wants to:
- Debug or troubleshoot production issues
- Diagnose errors in Azure services
- Analyze application logs or metrics
- Fix image pull, cold start, or health probe issues
- Investigate why Azure resources are failing
- Find root cause of application errors
## Rules
1. Start with systematic diagnosis flow
2. Use AppLens (MCP) for AI-powered diagnostics when available
3. Check resource health before deep-diving into logs
4. Select appropriate troubleshooting guide based on service type
5. Document findings and attempted remediation steps
---
## Quick Diagnosis Flow
1. **Identify symptoms** - What's failing?
2. **Check resource health** - Is Azure healthy?
3. **Review logs** - What do logs show?
4. **Analyze metrics** - Performance patterns?
5. **Investigate recent changes** - What changed?
---
## Troubleshooting Guides by Service
| Service | Common Issues | Reference |
|---------|---------------|-----------|
| **Container Apps** | Image pull failures, cold starts, health probes, port mismatches | [container-apps/](references/container-apps/README.md) |
---
## Quick Reference
### Common Diagnostic Commands
```bash
# Check resource health
az resource show --ids RESOURCE_ID
# View activity log
az monitor activity-log list -g RG --max-events 20
# Container Apps logs
az containerapp logs show --name APP -g RG --follow
```
### AppLens (MCP Tools)
For AI-powered diagnostics, use:
```
mcp_azure_mcp_applens
intent: "diagnose issues with <resource-name>"
command: "diagnose"
parameters:
resourceId: "<resource-id>"
Provides:
- Automated issue detection
- Root cause analysis
- Remediation recommendations
```
### Azure Monitor (MCP Tools)
For querying logs and metrics:
```
mcp_azure_mcp_monitor
intent: "query logs for <resource-name>"
command: "logs_query"
parameters:
workspaceId: "<workspace-id>"
query: "<KQL-query>"
```
See [kql-queries.md](references/kql-queries.md) for common diagnostic queries.
---
## Check Azure Resource Health
### Using MCP
```
mcp_azure_mcp_resourcehealth
intent: "check health status of <resource-name>"
command: "get"
parameters:
resourceId: "<resource-id>"
```
### Using CLI
```bash
# Check specific resource health
az resource show --ids RESOURCE_ID
# Check recent activity
az monitor activity-log list -g RG --max-events 20
```
---
## References
- [KQL Query Library](references/kql-queries.md)
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