azure-kubernetes▌
microsoft/azure-skills · updated Apr 8, 2026
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AUTHORITATIVE GUIDANCE — MANDATORY COMPLIANCE
Azure Kubernetes Service
AUTHORITATIVE GUIDANCE — MANDATORY COMPLIANCE
This skill produces a recommended AKS cluster configuration based on user requirements, distinguishing Day-0 decisions (networking, API server — hard to change later) from Day-1 features (can enable post-creation). See CLI reference for commands.
Quick Reference
| Property | Value |
|---|---|
| Best for | AKS cluster planning and Day-0 decisions |
| MCP Tools | mcp_azure_mcp_aks |
| CLI | az aks create, az aks show, kubectl get, kubectl describe |
| Related skills | azure-diagnostics (troubleshooting AKS), azure-validate (readiness checks) |
When to Use This Skill
Activate this skill when user wants to:
- Create a new AKS cluster
- Plan AKS cluster configuration for production workloads
- Design AKS networking (API server access, pod IP model, egress)
- Set up AKS identity and secrets management
- Configure AKS governance (Azure Policy, Deployment Safeguards)
- Enable AKS observability (Container Insights, Managed Prometheus, Grafana)
- Define AKS upgrade and patching strategy
- Enable AKS cost visibility and analysis
- Understand AKS Automatic vs Standard SKU differences
- Get a Day-0 checklist for AKS cluster setup and configuration
Rules
- Start with the user's requirements for provisioning compute, networking, security, and other settings.
- Use the
azureMCP server and selectmcp_azure_mcp_aksfirst to discover the exact AKS-specific MCP tools surfaced by the client. Choose the smallest discovered AKS tool that fits the task, and fall back to Azure CLI (az aks) only when the needed functionality is not exposed through the AKS MCP surface. - Determine if AKS Automatic or Standard SKU is more appropriate based on the user's need for control vs convenience. Default to AKS Automatic unless specific customizations are required.
- Document decisions and rationale for cluster configuration choices, especially for Day-0 decisions that are hard to change later (networking, API server access).
Required Inputs (Ask only what’s needed)
If the user is unsure, use safe defaults.
- AKS environment type: dev/test or production
- Region(s), availability zones, preferred node VM sizes
- Expected scale (node/cluster count, workload size)
- Networking requirements (API server access, pod IP model, ingress/egress control)
- Security and identity requirements, including image registry
- Upgrade and observability preferences
- Cost constraints
Workflow
1. Cluster Type
- AKS Automatic (default): Best for most production workloads, provides a curated experience with pre-configured best practices for security, reliability, and performance. Use unless you have specific custom requirements for networking, autoscaling, or node pool configurations not supported by Node Auto-Provisioning (NAP).
- AKS Standard: Use if you need full control over environment configuration, which requires additional overhead to set up and manage.
2. Networking (Pod IP, Egress, Ingress, Dataplane)
Pod IP Model (Key Day-0 decision):
- Azure CNI Overlay (recommended): pod IPs from private overlay range, not VNet-routable, scales to large environments and good for most workloads
- Azure CNI (VNet-routable): pod IPs directly from VNet (pod subnet or node subnet), use when pods must be directly addressable from VNet or on-prem
Dataplane & Network Policy:
- Azure CNI powered by Cilium (recommended): eBPF-based for high-performance packet processing, network policies, and observability
Egress:
- Static Egress Gateway for stable, predictable outbound IPs
- For restricted egress: UDR + Azure Firewall or NVA
Ingress:
- App Routing addon with Gateway API — recommended default for HTTP/HTTPS workloads
- Istio service mesh with Gateway API - for advanced traffic management, mTLS, canary releases
- Application Gateway for Containers — for L7 load balancing with WAF integration
DNS:
- Enable LocalDNS on all node pools for reliable, performant DNS resolution
3. Security
- Use Microsoft Entra ID everywhere (control plane, Workload Identity for pods, node access). Avoid static credentials.
- Azure Key Vault via Secrets Store CSI Driver for secrets
- Enable Azure Policy + Deployment Safeguards
- Enable Encryption at rest for etcd/API server; in-transit for node-to-node
- Allow only signed, policy-approved images (Azure Policy + Ratify), prefer Azure Container Registry
- Isolation: Use namespaces, network policies, scoped logging
4. Observability
- Use Managed Prometheus and Container Insights with Grafana for AKS observability (logs + metrics).
- Enable Diagnostic Settings to collect control plane logs and audit logs in a Log Analytics workspace for security monitoring and troubleshooting.
- For other monitoring and troubleshooting tools, use features like the Agentic CLI for AKS, Application Insights, Resource Health Center, AppLens detectors, and Azure Advisors.
5. Upgrades & Patching
- Configure Maintenance Windows for controlled upgrade timing
- Enable auto-upgrades for control plane and node OS to stay up-to-date with security patches and Kubernetes versions
- Consider LTS versions for enterprise stability (2-year support) by upgrading your AKS environment to the Premium tier
- Fleet upgrades: Use AKS Fleet Manager for staged rollout across test to production environments
6. Performance
- Use Ephemeral OS disks (
--node-osdisk-type Ephemeral) for faster node startup - Select Azure Linux as node OS (smaller footprint, faster boot)
- Enable KEDA for event-driven autoscaling beyond HPA
7. Node Pools & Compute
- Dedicated system node pool: At least 2 nodes, tainted for system workloads only (
CriticalAddonsOnly) - Enable Node Auto Provisioning (NAP) on all pools for cost savings and responsive scaling
- Use latest generation SKUs (v5/v6) for host-level optimizations
- Avoid B-series VMs — burstable SKUs cause performance/reliability issues
- Use SKUs with at least 4 vCPUs for production workloads
- Set topology spread constraints to distribute pods across hosts/zones per SLO
8. Reliability
- Deploy across 3 Availability Zones (
--zones 1 2 3) - Use Standard tier for zone-redundant control plane + 99.95% SLA for API server availability
- Enable Microsoft Defender for Containers for runtime protection
- Configure PodDisruptionBudgets for all production workloads
- Use topology spread constraints to ensure pod distribution across failure domains
9. Cost Controls
- Use Spot node pools for batch/interruptible workloads (up to 90% savings)
- Stop/Start dev/test clusters:
az aks stop/start - Consider Reserved Instances or Savings Plans for steady-state workloads
Guardrails / Safety
- Do not request or output secrets (tokens, keys).
- If requirements are ambiguous for day-0 critical decisions, ask the user clarifying questions. For day-1 enabled features, propose 2–3 safe options with tradeoffs and choose a conservative default.
- Do not promise zero downtime; advise workload safeguards (PDBs, probes, replicas) and staged upgrades along with best practices for reliability and performance.
MCP Tools
| Tool | Purpose | Key Parameters |
|---|---|---|
mcp_azure_mcp_aks |
AKS MCP entry point used to discover the exact AKS-specific tools exposed by the client | Discover the callable AKS tool first, then use that tool's parameters |
Error Handling
| Error / Symptom | Likely Cause | Remediation |
|---|---|---|
| MCP tool call fails or times out | Invalid credentials, subscription, or AKS context | Verify az login, confirm the active subscription context with az account show, and check the target resource group without echoing subscription identifiers back to the user |
| Quota exceeded | Regional vCPU or resource limits | Request quota increase or select different region/VM SKU |
| Networking conflict (IP exhaustion) | Pod subnet too small for overlay/CNI | Re-plan IP ranges; may require cluster recreation (Day-0) |
| Workload Identity not working | Missing OIDC issuer or federated credential | Enable --enable-oidc-issuer --enable-workload-identity, configure federated identity |
How to use azure-kubernetes on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add azure-kubernetes
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches azure-kubernetes from GitHub repository microsoft/azure-skills and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate azure-kubernetes. Access the skill through slash commands (e.g., /azure-kubernetes) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
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Use Cases▌
Task Automation & Efficiency
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Knowledge Enhancement
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Quality Improvement
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client with skill support
- ›Clear understanding of task or problem to solve
- ›Willingness to iterate and refine outputs
Time Estimate
15-45 minutes depending on use case complexity
Installation Steps
- 1.Install skill using provided installation command
- 2.Test with simple use case relevant to your work
- 3.Evaluate output quality and relevance
- 4.Iterate on prompts to improve results
- 5.Integrate into regular workflow if valuable
Common Pitfalls
- ⚠Expecting perfect results without iteration
- ⚠Not providing enough context in prompts
- ⚠Using skill for tasks outside its intended scope
- ⚠Accepting outputs without review and validation
Best Practices▌
✓ Do
- +Start with clear, specific prompts
- +Provide relevant context and constraints
- +Review and refine all outputs before using
- +Iterate to improve output quality
- +Document successful prompt patterns
✗ Don't
- −Don't use without understanding skill limitations
- −Don't skip validation of outputs
- −Don't share sensitive information in prompts
- −Don't expect skill to replace human judgment
💡 Pro Tips
- ★Be specific about desired format and style
- ★Ask for multiple options to choose from
- ★Request explanations to understand reasoning
- ★Combine AI efficiency with human expertise
When to Use This▌
✓ Use When
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid When
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
Learning Path▌
- 1Familiarize yourself with skill capabilities and limitations
- 2Start with low-risk, non-critical tasks
- 3Progress to more complex and valuable use cases
- 4Build expertise through regular use and experimentation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.7★★★★★28 reviews- ★★★★★Olivia Reddy· Dec 28, 2024
azure-kubernetes fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Carlos Menon· Dec 20, 2024
We added azure-kubernetes from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Liam Rahman· Nov 19, 2024
azure-kubernetes is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Harper Taylor· Nov 11, 2024
Keeps context tight: azure-kubernetes is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Chen Farah· Oct 10, 2024
Keeps context tight: azure-kubernetes is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Carlos Rao· Oct 2, 2024
azure-kubernetes is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Michael Bansal· Sep 21, 2024
azure-kubernetes reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Oshnikdeep· Sep 17, 2024
Registry listing for azure-kubernetes matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Michael Gill· Aug 12, 2024
Registry listing for azure-kubernetes matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Ganesh Mohane· Aug 8, 2024
azure-kubernetes reduced setup friction for our internal harness; good balance of opinion and flexibility.
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