Azure Diagnostics
MicrosoftOfficialCreated by Microsoft
- Skill
- Workflow
- Cloud and DevOps
- MIT
- Low risk
- Has scripts
AutoGineer summary
Written by AutoGineer from the skill’s own files, not by the author
Azure Diagnostics provides a structured, authoritative approach to investigating and resolving production issues across various Azure services. It emphasizes a systematic flow: identifying symptoms, checking resource health, reviewing logs, analyzing metrics, and investigating recent changes. The skill supports both live troubleshooting via Azure CLI and AppLens, as well as evidence-only analysis when live access is restricted. It includes specialized guidance for App Service, Container Apps, Azure Functions, AKS, VMs, and Messaging services, ensuring consistent root-cause analysis.
What it does
- Provides a standardized diagnostic workflow for Azure production environments.
- Integrates with AppLens and Azure Monitor for automated issue detection and log analysis.
- Offers service-specific troubleshooting paths for App Service, AKS, VMs, and more.
- Supports evidence-only diagnosis for secure, offline troubleshooting scenarios.
- Includes KQL query patterns for deep-dive log and resource health analysis.
- Facilitates the use of bundled diagnostic scripts for efficient data collection.
When to use it
- When investigating production incidents like high CPU, deployment failures, or service crashes.
- When troubleshooting connectivity issues such as RDP/SSH failures or network blocking.
- When diagnosing Kubernetes-specific issues like pod crashloops or image pull failures.
- When analyzing missing telemetry or messaging errors in Event Hubs and Service Bus.
- When performing root-cause analysis on unhealthy or degraded Azure resources.
Advantages
- Reduces mean time to resolution (MTTR) with a clear, step-by-step diagnostic process.
- Ensures consistent troubleshooting practices across different Azure service types.
- Supports secure workflows by allowing diagnosis without requiring live environment access.
- Leverages powerful built-in tools like AppLens and Azure Resource Graph for rapid insights.
- Provides actionable remediation steps based on identified symptoms.
Usage examples
- “Troubleshoot my App Service that is experiencing high CPU usage.”
- The agent will initiate the App Service diagnostic flow, run the appservice-diagnostics script, check metrics, and guide you through profiling via Kudu.
- “Why is my Azure VM unreachable via SSH?”
- The agent will follow the VM connectivity troubleshooting guide, checking NSG rules, firewall status, and VM agent health.
- “Analyze these logs to find why my Container App is failing to pull the image.”
- The agent will perform an evidence-only analysis of the provided logs to identify image pull errors or registry authentication issues.
- “Check the health of my AKS cluster and identify why pods are in a crashloop.”
- The agent will check resource health, query logs for the affected pods, and route to the AKS-specific troubleshooting documentation.
Install
Download the skill as a ZIP:
https://mp-staging.autogineer.com/agent-skills/microsoft/azure-diagnostics/downloadUnzip it into the cross-client skills folder of your project:
mkdir -p .agents/skills && unzip azure-diagnostics.zip -d .agents/skills
Documentation by Microsoft
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
Troubleshoot App Service issues (high CPU, deployment failures, crashes, slow responses, TLS/custom domains)
Respond to prompts like "troubleshoot app service", "app service high CPU", or "app service deployment failure"
Troubleshoot Azure Function Apps (invocation failures, timeouts, binding errors)
Find the App Insights or Log Analytics workspace linked to a Function App
Troubleshoot AKS clusters, nodes, pods, ingress, or Kubernetes networking issues
Troubleshoot Azure VM connectivity issues (RDP/SSH failures, port 3389/22 timeouts, NSG or firewall blocking, credential resets)
Troubleshoot Azure Messaging SDK issues (Event Hubs, Service Bus connection failures, AMQP errors, message lock issues)
Root-cause a symptom that looks like a healthy-runtime-but-wrong-destination problem (e.g., telemetry/messages stop flowing to the expected resource after a config change) — invoke this skill for the matrix even when MCP tools could answer the surface question alone
Rules
Start with systematic diagnosis flow
Use supplied evidence first. If the user requests evidence-only analysis or prohibits live Azure access, do not query or modify Azure. Diagnose from the supplied logs, metrics, and timeline; identify assumptions and provide optional verification steps.
Use AppLens (MCP) for AI-powered diagnostics when available
Check resource health before deep-diving into logs
Select appropriate troubleshooting guide based on service type
Document findings and attempted remediation steps
Prefer bundled diagnostic scripts over ad hoc calls for permitted live collection when identifiers are known. If supplied evidence suffices or live access is prohibited, don't run them; otherwise run the applicable script first.
Route AKS incidents to the dedicated AKS troubleshooting document
Keep baseline AKS diagnostics available even when the optional
aks-skillsadd-on is absent, declined, or unsupported by the host
Quick Diagnosis Flow
Identify symptoms - What's failing?
Check resource health - Is Azure healthy?
Review logs - What do logs show?
Analyze metrics - Performance patterns?
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/ |
| App Service | High CPU, deployment failures, crashes, slow responses, TLS/custom domains | app-service/ |
| Function Apps | App details, invocation failures, timeouts, binding errors, cold starts, missing app settings | functions/ |
| AKS | Cluster access, nodes, kube-system, scheduling, crash loops, ingress, DNS, upgrades | AKS Troubleshooting |
| Compute | VM RDP/SSH connectivity, NSG/firewall blocks, credential resets, VM agent/tooling issues | VM Connectivity Troubleshooting |
| Messaging | Event Hubs & Service Bus SDK errors, AMQP failures, message lock, connectivity | Messaging Troubleshooting |
Routing
Keep Container Apps and Function Apps diagnostics in this parent skill.
Route active AKS incidents, AKS-specific intake, evidence gathering, and remediation guidance to AKS Troubleshooting.
Route Azure VM RDP/SSH connectivity, NSG/firewall, credential reset, and VM agent troubleshooting to VM Connectivity Troubleshooting.
Route Azure Messaging SDK troubleshooting (Event Hubs, Service Bus) to Messaging Troubleshooting.
Quick Reference
Common Diagnostic Commands
# 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
# Function App logs (query App Insights traces)
az monitor app-insights query --apps APP-INSIGHTS -g RG \
--analytics-query "traces | where timestamp > ago(1h) | order by timestamp desc | take 50"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 recommendationsAzure 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 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
# Check specific resource health
az resource show --ids RESOURCE_ID
# Check recent activity
az monitor activity-log list -g RG --max-events 20References
Files
- ATTRIBUTION.mdAdded by AutoGineer983 B
- LICENSELicence file added by AutoGineer1.1 KiB
- SKILL.md7.3 KiB
- references/app-service/README.md7.8 KiB
- references/azure-resource-graph.md2.8 KiB
- references/container-apps/README.md3.5 KiB
- references/functions/README.md3.9 KiB
- references/functions/durable.md7.6 KiB
- references/functions/triggers.md8.3 KiB
- references/kql-queries.md1.3 KiB
- scripts/aks-baseline.ps1Script7.4 KiB
- scripts/aks-baseline.shScript7.0 KiB
- scripts/appservice-diagnostics.ps1Script2.7 KiB
- scripts/appservice-diagnostics.shScript3.3 KiB
- scripts/containerapp-diagnostics.ps1Script2.5 KiB
- scripts/containerapp-diagnostics.shScript3.1 KiB
- scripts/pod-evidence.ps1Script6.6 KiB
- scripts/pod-evidence.shScript7.1 KiB
- scripts/run-ig.ps1Script5.6 KiB
- scripts/run-ig.shScript6.5 KiB
- scripts/test-messaging-connectivity.ps1Script6.3 KiB
- scripts/test-messaging-connectivity.shScript6.8 KiB
- troubleshooting/aks/aks-troubleshooting.md9.2 KiB
- troubleshooting/aks/general-diagnostics.md2.0 KiB
- troubleshooting/aks/load-balancer-and-ingress.md3.6 KiB
- troubleshooting/aks/network-policy.md832 B
- troubleshooting/aks/networking.md5.5 KiB
- troubleshooting/aks/node-issues.md4.7 KiB
- troubleshooting/aks/optional-aks-operations.md2.3 KiB
- troubleshooting/aks/pod-failures.md7.6 KiB
- troubleshooting/aks/references/aks-mcp.md2.3 KiB
- troubleshooting/aks/references/command-flows.md4.1 KiB
- troubleshooting/aks/references/inspektor-gadget.md7.6 KiB
- troubleshooting/aks/references/structured-input-modes.md1.5 KiB
- troubleshooting/aks/spot-and-zone-issues.md2.5 KiB
- troubleshooting/aks/upgrade-operations.md2.2 KiB
- troubleshooting/compute/references/cannot-connect-to-vm.md3.1 KiB
- troubleshooting/compute/references/credential-auth-errors.md2.3 KiB
- troubleshooting/compute/references/firewall-blocking.md2.3 KiB
- troubleshooting/compute/references/network-connectivity.md2.5 KiB
- troubleshooting/compute/references/rdp-connectivity.md2.7 KiB
- troubleshooting/compute/references/rdp-service-config.md3.2 KiB
- troubleshooting/compute/references/ssh-connectivity.md2.9 KiB
- troubleshooting/compute/references/vm-agent-not-responding.md3.6 KiB
- troubleshooting/compute/vm-troubleshooting.md3.3 KiB
- troubleshooting/messaging/README.md1.6 KiB
- troubleshooting/messaging/auth-best-practices.md6.1 KiB
- troubleshooting/messaging/azure-eventhubs-dotnet.md3.5 KiB
- troubleshooting/messaging/azure-eventhubs-java.md3.2 KiB
- troubleshooting/messaging/azure-eventhubs-js.md2.7 KiB
- troubleshooting/messaging/azure-eventhubs-py.md4.3 KiB
- troubleshooting/messaging/azure-servicebus-dotnet.md2.5 KiB
- troubleshooting/messaging/azure-servicebus-java.md2.2 KiB
- troubleshooting/messaging/azure-servicebus-js.md2.4 KiB
- troubleshooting/messaging/azure-servicebus-py.md2.3 KiB
- troubleshooting/messaging/service-troubleshooting.md5.1 KiB
troubleshooting/aks/aks-troubleshooting.md
AKS Troubleshooting Guide
Primary AKS troubleshooting guide for incidents routed from ../../SKILL.md.
When to Use This Guide
lifecycle, access, node,
kube-system, workload, ingress, DNS, or scaling issueskubectlcannot connect, nodes areNotReady, or pods are unhealthy
Scenario Playbooks
| Scenario | Reference |
|---|---|
| broad cluster investigation | general-diagnostics.md |
| workload, crash, image pull, readiness, or pending pod issues | pod-failures.md |
| node health, scaling, pressure, upgrade, or zone issues | node-issues.md |
| service, ingress, DNS, or network policy issues | networking.md |
Tool Selection For Diagnostics
When gathering AKS diagnostic evidence, use the host-assigned Azure MCP AKS area for cluster and node-pool metadata, then separate Azure MCP areas such as AppLens, Monitor, or Resource Health when their advertised schemas fit the read. Use az aks and kubectl for every check those surfaces do not provide, including all Kubernetes-side inspection; the AKS area does not run kubectl.
When standard diagnostics do not reveal root cause, use Inspektor Gadget for real-time, low-level node and pod observability (DNS traces, TCP traces, process snapshots, file access traces). See references/inspektor-gadget.md for the gadget catalog, the run-ig script, and symptom-to-gadget mapping.
See references/aks-mcp.md, references/structured-input-modes.md, references/command-flows.md
The optional, consent-gated aks-skills add-on is handled by the Workflow's
focused-skill checkpoint below; this baseline guide remains usable when it is
not installed or cannot execute.
Required Inputs
subscription or active Azure context
resource group and cluster name
symptom summary
first observed time or recent change window
impacted namespace, workload, service, or ingress when known
If cluster identity is missing and no kubectl context is active, don't stop and ask
immediately. Resolve the subscription from the request or confirmed existing context.
If none is known, list accessible subscriptions and ask the user to select one; don't
scan AKS resources across every subscription automatically. Run az aks list --subscription <subscription-id> in the selected subscription. If exactly one cluster
is found, establish context with az aks get-credentials --subscription <subscription-id> --resource-group <resource-group> --name <cluster-name>, then use the
relevant script's discovery/auto-select mode (e.g. pod-evidence.sh --all-failing). If
zero or multiple clusters are found, ask the user to identify the target. If
kubectl already has an active context, verify that its cluster matches the incident
before collecting evidence. Use the context only when the user confirms it or its
cluster/subscription/resource-group matches known incident details; otherwise ask which
cluster to use. After confirmation, use the script's discovery/auto-select mode and ask
for remaining details only if discovery comes up empty.
Scope Buckets
Lifecycle: create, update, start, stop, upgrade, or provisioning failures
API access: kubeconfig, auth, private endpoint, DNS, or reachability problems
Nodes: missing nodes,
NotReady, pressure, CNI, kubelet, certificate, or VMSS driftkube-system: CoreDNS, metrics-server, konnectivity, ingress, CNI, CSI, or add-on failuresWorkloads:
Pending,CrashLoopBackOff,OOMKilled, PVC, quota, secret, readiness, or dependency issuesConnectivity and DNS: pod -> service -> endpoints -> ingress/load balancer -> DNS -> network controls
Scaling: node pool sizing, pending pods, autoscaler config, metrics, quota, or subnet constraints
Evidence Order
The classified symptom selects the first read. For lifecycle, API-access, node, scaling, quota, upgrade, or broad and unclassified symptoms, start Azure-side: cluster state, resource health, recent operations, node pool state, detector or monitoring output.
For a clearly identified workload failure (a named pod in
CrashLoopBackOff,ImagePullBackOff,OOMKilled, or a similar pod-local state), start with pod state, events, and current/previous logs — supplied or collected — then expand to node and Azure evidence only as the causal branch requires; no broad Azure sweep first. Otherwise Kubernetes-side state follows the Azure-side read: reachability, nodes,kube-system, events, affected namespace, pod detail, logs.Use detector, warning-event, or metrics modes when the incoming data already matches them.
Deep diagnostics; when the symptom-relevant checks above do not reveal root cause, use inspektor-gadget.md for real-time tracing on the affected node.
Workflow
Get cluster context.
Classify the problem by scope bucket.
Focused-skill checkpoint. For any incident in the Scope Buckets above, complete the handoff in optional-aks-operations.md once before gathering evidence: check the host's available-skill inventory; use the focused skill if present; if it is missing and deeper investigation would materially help the current task, make one offer and ask before installing — never install merely to interpret supplied evidence that already answers the task; if the customer declines or the host cannot install or execute it, continue with this guide and do not ask again. An application-level cause (for example a
CrashLoopBackOfffrom bad config) does not exempt an AKS workload incident from this checkpoint.Follow the Evidence Order above.
Use the matching Azure MCP area for Azure-side metadata where its schema fits, then the documented
az/kubectlflows for everything else.Return evidence, failure domain, confidence, next checks, remediation, and escalation.
Error Patterns
No cluster context: ask for subscription, resource group, and cluster name.
MCP unavailable: fall back to safe
az aksandkubectlreads.kubectlblocked: separate auth problems from network reachability.Logs or metrics missing: use events, node state, and resource descriptions.
Detector noise: ignore
emergingIssues, prefer critical findings, rank the most actionable signal first.
Safe Fallback Checks
When the Azure MCP areas cannot perform the baseline read, run the aks-baseline script. It executes the read-only cluster + Kubernetes baseline sweep (provisioning state, node pools, activity log, node readiness, unhealthy pods, kube-system health, warning events) and returns a single labeled digest:
# bash
./scripts/aks-baseline.sh -g <resource-group> -n <cluster-name> [--namespace <namespace>]# PowerShell
.\scripts\aks-baseline.ps1 -ResourceGroup <resource-group> -Cluster <cluster-name> [-Namespace <namespace>]For unhealthy pods, go straight to the pod-evidence script rather than running
describe/logs/top one at a time — it gathers the full read-only evidence bundle
(describe, current + previous logs, resources vs usage) in a single call:
../../scripts/pod-evidence.sh /
../../scripts/pod-evidence.ps1. If the pod name isn't
known yet, use --all-failing to auto-discover it instead of asking the user for it:
../../scripts/pod-evidence.sh <pod-name> -n <namespace>
../../scripts/pod-evidence.sh --all-failing../../scripts/pod-evidence.ps1 <pod-name> -Namespace <namespace>
../../scripts/pod-evidence.ps1 -AllFailingSee pod-failures.md for how to interpret the digest.
Only fall back to the individual commands below if the bundled script is unavailable or
you need a check it doesn't cover. If kubectl is missing or unconfigured, install or
configure it before running Kubernetes-side checks:
az aks show -g <resource-group> -n <cluster-name>
az aks nodepool list -g <resource-group> --cluster-name <cluster-name>
kubectl cluster-info
kubectl get nodes -o wide
kubectl get pods -n kube-system
kubectl get events -A --sort-by=.lastTimestamp
kubectl describe pod <pod-name> -n <namespace>
kubectl logs <pod-name> -n <namespace> --previousKeep these read-only unless the user explicitly asks for remediation.
Guardrails
default to read-only diagnostics
do not restart, delete, cordon, drain, scale, upgrade, or reconfigure resources unless the user explicitly asks for remediation
do not conclude root cause without quoting the evidence that supports it
Output Checklist
Return scope and impact, evidence, failure domain, root cause, confidence, next checks, remediation, and escalation. State once which focused optional AKS skill applied and its status: used, offered and awaiting consent, installed but not yet active, declined, or not available on this host.
Requirements and compatibility
Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta
“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.
Needs: Needs a command-line tool
Security
What our scanner noticed· Low risk
- Instructions that use the network
- Scripts that your agent may run
This skill includes scripts that your agent may run. Read them before you use it.
A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.
Attribution and licence
- Created by
- Microsoft
- Publisher
- Microsoft (Official)
- Source
- microsoft/skills · .github/plugins/azure-skills/skills/azure-diagnostics · commit 0696600
- Licence
- MIT License (redistribution allowed)
- LICENSE (added by AutoGineer from .github/plugins/azure-skills/LICENSE)
- ATTRIBUTION.md (written by AutoGineer)
- Synced
- Also distributed in
- microsoft/azure-skills
AutoGineer is not affiliated with or endorsed by Microsoft.
Download ZIP
The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download azure-diagnostics.zip