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Aks Cost Optimization

MicrosoftOfficialCreated by Microsoft

  • Skill
  • Research and analysis
  • Cloud and DevOps
  • MIT
  • No issues found
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From the author

Analyze advanced AKS cost efficiency. WHEN: "AKS NAP readiness", "AKS bin packing", "AKS node scaling bottleneck", "AKS blocked scale-down", "AKS storage cost". DO NOT USE AS DIRECT ENTRY FOR: overall AKS cost assessments or rightsizing/VPA/CAS/Spot (azure-kubernetes); spend/anomalies/commitments (cost-analysis/cost-optimization); incidents (aks-troubleshooting).
— the description by Microsoft

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

This skill provides a structured workflow for analyzing advanced cost efficiency in Azure Kubernetes Service (AKS) clusters. It focuses on technical placement and scheduling factors rather than high-level financial reporting. The skill guides users through evaluating Node Auto-Provisioning (NAP) readiness, bin-packing efficiency, node scaling bottlenecks, and storage costs. It is designed to be used for specific technical investigations, requiring the user to route broader cost or incident-related queries to their respective specialized skills.

What it does

  • Evaluates cluster bin-packing efficiency and identifies consolidation candidates.
  • Assesses readiness for adopting Node Auto-Provisioning (NAP).
  • Identifies root causes for node scaling bottlenecks and blocked scale-down events.
  • Analyzes storage cost and mapping configurations.
  • Provides evidence-based recommendations for pool adjustments or placement changes.
  • Requires explicit user approval before any cluster configuration changes.

When to use it

  • When investigating inefficient resource utilization or poor bin-packing in an AKS cluster.
  • When evaluating whether to migrate from fixed node pools or Cluster Autoscaler to NAP.
  • When troubleshooting persistent node scaling bottlenecks or blocked scale-down operations.
  • When analyzing storage-related costs within an AKS environment.

Advantages

  • Provides deep technical insights into scheduling and placement constraints.
  • Prevents conflicting recommendations by routing to specialized skills for financial or incident data.
  • Ensures safe operations by requiring manual approval for all proposed changes.
  • Uses standardized evidence collection for consistent analysis across clusters.

Usage examples

“Analyze why my AKS cluster is failing to scale down nodes.”
The agent will investigate blocked scale-down events, check for PDBs or disruption budgets, and identify if the nodes are managed by NAP or CAS to provide a resolution path.
“Is my cluster ready for Node Auto-Provisioning?”
The agent will perform an eligibility check, verify current networking and identity configurations, and report if NAP is a viable and cost-effective alternative for your workload.

Install

  1. Download the skill as a ZIP:

    https://mp-staging.autogineer.com/agent-skills/microsoft/aks-cost-optimization/download

  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip aks-cost-optimization.zip -d .agents/skills

Documentation by Microsoft

AKS Cost Optimization

When to Use This Skill

Use for advanced existing-cluster analysis requiring scheduling, placement, or verified storage mapping. Route overall AKS cost assessments to azure-kubernetes, spend/anomalies to cost-analysis, commitments to cost-optimization, and incidents to aks-troubleshooting when those skills are available. When called from an overall assessment, return findings for its ranked report.

MCP Tools

Prefer fitting Azure MCP reads. Never invent tools or use az/kubectl without approved shell access and a target-bound context.

Workflow/Steps

  1. Bind the subscription, cluster, resource group, and kube context.

  2. Route to NAP readiness, bin-packing, node-scaling bottlenecks, or storage optimization.

  3. When invoked for AKS commitment context, use the commitment-demand handoff and return demand evidence without benefit analysis or a transaction.

  4. Keep reads non-mutating; require approval for every change.

Error Handling

  • Missing capability: analyze supplied evidence or provide a collection plan; mark dependent cost or commitment results unavailable.

  • Evidence conflict: mark the conclusion unconfirmed.

Files

references/self-hosted-karpenter-migration.md

Self-Hosted Karpenter to Managed NAP

Use this path only when Karpenter runs in the user cluster and managed NAP is disabled. Do not use normal NAP enablement.

Never delete Karpenter CRDs, NodePools, or NodeClaims; deleting the CRDs deletes underlying NodeClaims and can disrupt workloads. Require explicit approval before each metadata change, Helm uninstall, or AKS update.

Assess and Plan

  1. Confirm the Karpenter controller deployment, Helm release/namespace, chart version, and ownership annotations on Karpenter CRDs.

  2. Record Helm values and all existing NodePool, NodeClaim, and AKSNodeClass resources. Upgrade self-hosted Karpenter to a version compatible with current managed NAP before migration.

  3. Verify current nodes, pending workloads, PDBs, disruption controls, and capacity. Agree on an observation window and a rollback that reinstalls the recorded release and values.

Migrate

Remove these ownership entries from each Helm-owned Karpenter CRD so Helm preserves it:

kubectl annotate crd "<CRD_NAME>" \
  meta.helm.sh/release-name- meta.helm.sh/release-namespace-
kubectl label crd "<CRD_NAME>" app.kubernetes.io/managed-by-

Uninstall the recorded self-hosted release. Scaling pauses until managed NAP starts, but existing nodes must remain:

helm uninstall "<RELEASE_NAME>" --namespace "<RELEASE_NAMESPACE>"

Enable managed NAP without creating default pools so it adopts the preserved configuration:

az aks update \
  --name "<CLUSTER_NAME>" --resource-group "<RESOURCE_GROUP>" \
  --node-provisioning-mode Auto --node-provisioning-default-pools None

Verify

Confirm the cluster reports NAP mode Auto, AKS has assumed ownership of the preserved Karpenter CRDs, and existing NodePools, NodeClaims, and nodes remain. Verify provisioning, consolidation, pending-pod time, workload SLOs, and NAP events during the observation window. If enablement or ownership transfer fails, stop and reinstall the recorded self-hosted Karpenter release with its saved chart version, namespace, and Helm values, following the pre-approved rollback plan.

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 Node.js

Security

No issues found by our static scan· No issues found

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/aks-skills/skills/aks-cost-optimization · commit 0696600
Licence
MIT License (redistribution allowed)
  • LICENSE (added by AutoGineer from .github/plugins/aks-skills/LICENSE)
  • ATTRIBUTION.md (written by AutoGineer)
Synced

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 aks-cost-optimization.zip