Investigate cost efficiency in an existing AKS cluster by examining pod placement, node scaling bottlenecks, and verified storage mappings. It returns evidence for findings such as NAP readiness, bin packing, blocked scale-down, or storage costs.
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).
Run score Not tested
See how to installReview the instructions the agent will receive before you install.
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.
Prefer fitting Azure MCP reads. Never invent tools or use az/kubectl
without approved shell access and a target-bound context.
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Create Python agents on Azure AI Foundry that retain conversation context and use multiple tools. The skill covers code execution, file and web search, external tool connections, streaming responses, and outputs organized into defined fields.
Set up AI Runway on an existing AKS cluster, from checking cluster health and GPU compatibility to installing model serving software, deploying a first AI model, and verifying that it runs.
Investigate GPU and KAITO failures in AKS using read-only evidence. Helps distinguish scheduling problems, memory shortages, workspace readiness issues, and scaling failures, then organizes findings with confidence levels and missing evidence.
Find documented fixes for known AKS errors by matching the exact error message and required conditions. Get an explanation of the cause, a proposed fix, a Microsoft Learn reference, and read-only verification steps.
Collect bounded packet captures from AKS nodes or pods alongside Azure network settings. Use the captured traffic as evidence when investigating where packets are lost, after initial checks that do not change the environment.
Investigate live Azure Kubernetes Service incidents through read-only checks of logs, events, and resource state. Trace workload, node, networking, or upgrade failures and produce an incident report with supporting evidence, confidence, and proposed remediation.