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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://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/storage-decisions.md

AKS Storage Decisions

Use after storage mapping, ownership, and applicable metric evidence has been collected.

Recommend in Order

PriorityEvidenceRecommendation
Remove unusedVerified mapped volume is unused; verified orphan disk is unattached and exhaustively unreferenced; obsolete snapshot is not required for recovery/complianceConfirm owner, failure cause, backend state, backup, and recovery requirements before proposing deletion
Right-size capacityActive Azure Disk PVC has representative usage plus growth/recovery headroom below a cheaper billable sizeManaged disks cannot shrink; back up, create a smaller PVC, copy and validate, cut over, then remove the old volume
Right-size performanceLower SKU or provisioned IOPS/throughput meets historical demand and latency/SLA needsIf Azure supports the SKU transition, scale the workload to zero, verify detachment, change the disk SKU in place, then restore and validate; otherwise migrate through a new StorageClass/PVC. Lower configurable Premium SSD v2/Ultra performance in place when supported
Prevent recurrenceDisposable dynamic volumes use Retain or retained resources lack reviewUse Delete only for future disposable volumes; preserve Retain for recovery/compliance

Deleting a PVC/PV produces savings only when its reclaim flow or approved follow-up deletes the billable Azure resource. Do not recommend a tier or capacity change from allocation alone. Exclude active backups, shared disks, database/log volumes, and compliance-retained data until owners confirm recovery, latency, performance, access-mode, zone, and redundancy needs.

Classify each candidate as recommend optimization, potentially unused, investigate further, insufficient evidence, or no change recommended. A Failed PV can indicate a broken backend, failed provisioning, recovery issue, or stale metadata. An unattached disk or Released, Available, or Failed PV alone does not prove it is unused; verify the Azure resource and all Kubernetes/Azure references, ownership, backup, recovery, and backend state before recommending cleanup.

Migration and Approval Gates

Require explicit approval before migration/cutover; accepting downtime is not authorization. Before migration, take or verify a current recoverable backup; a previously tested restore alone is insufficient. Validate the new volume before cutover. Even after verification, require separate explicit approval before deleting any PVC, PV, snapshot, or Azure storage resource.

Output

Return applicable fields for each candidate: namespace/PVC/PV, exact Azure resource ID, current size/SKU/reclaim behavior, utilization/performance evidence, attributable cost, proposed state, estimated savings, migration/rollback, downtime, risk, and confidence. For mapped volumes, name both sides of the verified mapping. For orphan candidates, report provenance, attachment state, reference checks, owner, and recovery decision.

For migrations, report whether a current recoverable backup is verified or still required, and state which migration or deletion actions still require approval.

Recommend deletion only for verified unused mapped resources or verified orphan candidates, and rightsizing only with required evidence. Otherwise report insufficient telemetry without estimating savings.

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 or Microsoft.

Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download aks-cost-optimization.zip