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WHEN: create AKS environment, provision AKS, enable AKS observability, design AKS networking, choose AKS SKU, secure AKS, optimize AKS, AKS spot nodes, AKS cluster-autoscaler, rightsize AKS pod, pod rightsizing, over-provisioned AKS pod, pod resource requests and limits, Vertical Pod Autoscaler, VPA recommendations.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},"microsoft","Microsoft","https:\u002F\u002Fpexgzepcugksgbtrxkhf.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Forg-logos\u002Fmicrosoft.png",[12,16,19,22,25],{"name":13,"slug":14,"type":15},"Azure","azure","tag",{"name":17,"slug":18,"type":15},"Networking","networking",{"name":20,"slug":21,"type":15},"Deployment","deployment",{"name":23,"slug":24,"type":15},"AI Infrastructure","ai-infrastructure",{"name":26,"slug":27,"type":15},"Kubernetes","kubernetes",1324,"https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fazure-skills","2026-07-31T05:56:15.058215","MIT",220,[34],"agent-skills",{"repoUrl":29,"stars":28,"forks":32,"topics":36,"description":37},[34],"Official agent plugin providing skills and MCP server configurations for Azure scenarios.","https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fazure-skills\u002Ftree\u002FHEAD\u002Fskills\u002Fazure-kubernetes","---\nname: azure-kubernetes\nlicense: MIT\nmetadata:\n  author: Microsoft\n  version: \"1.2.1\"\ndescription: \"Plan, create, and configure production-ready Azure Kubernetes Service (AKS) clusters. Covers Day-0 checklist, SKU selection (Automatic vs Standard), networking options (private API server, Azure CNI Overlay, egress configuration), security, and operations (autoscaling, upgrade strategy, cost analysis). WHEN: create AKS environment, provision AKS, enable AKS observability, design AKS networking, choose AKS SKU, secure AKS, optimize AKS, AKS spot nodes, AKS cluster-autoscaler, rightsize AKS pod, pod rightsizing, over-provisioned AKS pod, pod resource requests and limits, Vertical Pod Autoscaler, VPA recommendations.\"\n---\n\n# Azure Kubernetes Service\n\n> **AUTHORITATIVE GUIDANCE — MANDATORY COMPLIANCE**\n>\n> 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](.\u002Freferences\u002Fcli-reference.md) for commands.\n\n## Quick Reference\n| Property | Value |\n|----------|-------|\n| Best for | AKS cluster planning and Day-0 decisions |\n| MCP Tools | `mcp_azure_mcp_aks` |\n| CLI | `az aks create`, `az aks show`, `kubectl get`, `kubectl describe` |\n| Related skills | azure-diagnostics (troubleshooting AKS), azure-validate (readiness checks), azure-kubernetes-automatic-readiness (migrate existing cluster to AKS Automatic) |\n\n## When to Use This Skill\nActivate this skill when user wants to:\n- Create a new AKS cluster\n- Plan AKS cluster configuration for production workloads\n- Design AKS networking (API server access, pod IP model, egress)\n- Set up AKS identity and secrets management\n- Configure AKS governance (Azure Policy, Deployment Safeguards)\n- Enable AKS observability (Container Insights, Managed Prometheus, Grafana)\n- Define AKS upgrade and patching strategy\n- Understand AKS Automatic vs Standard SKU differences\n- Get a Day-0 checklist for AKS cluster setup and configuration\n\n## Rules\n1. Start with the user's requirements for provisioning compute, networking, security, and other settings.\n2. Use the `azure` MCP server and select `mcp_azure_mcp_aks` first 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.\n3. 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.\n4. Document decisions and rationale for cluster configuration choices, especially for Day-0 decisions that are hard to change later (networking, API server access).\n\n\n## Required Inputs (Ask only what’s needed)\nIf the user is unsure, use safe defaults.\n- AKS environment type: dev\u002Ftest or production\n- Region(s), availability zones, preferred node VM sizes\n- Expected scale (node\u002Fcluster count, workload size)\n- Networking requirements (API server access, pod IP model, ingress\u002Fegress control)\n- Security and identity requirements, including image registry\n- Upgrade and observability preferences\n- Cost constraints\n\n## Workflow\n\n### 1. Cluster Type\n- **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).\n- **AKS Standard**: Use if you need full control over environment configuration, which requires additional overhead to set up and manage.\n\n### 2. Networking (Pod IP, Egress, Ingress, Dataplane)\n\n**Pod IP Model** (Key Day-0 decision):\n- **Azure CNI Overlay** (recommended): pod IPs from private overlay range, not VNet-routable, scales to large environments and good for most workloads\n- **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\n  - Docs: https:\u002F\u002Flearn.microsoft.com\u002Fazure\u002Faks\u002Fazure-cni-overlay\n\n**Dataplane & Network Policy**:\n- **Azure CNI powered by Cilium** (recommended): eBPF-based for high-performance packet processing, network policies, and observability\n\n**Egress**:\n- **Static Egress Gateway** for stable, predictable outbound IPs\n- For restricted egress: UDR + Azure Firewall or NVA\n\n**Ingress**:\n- **App Routing addon with Gateway API** — recommended default for HTTP\u002FHTTPS workloads\n- **Istio service mesh with Gateway API** - for advanced traffic management, mTLS, canary releases\n- **Application Gateway for Containers** — for L7 load balancing with WAF integration\n\n**DNS**:\n- Enable **LocalDNS** on all node pools for reliable, performant DNS resolution\n\n### 3. Security\n- Use **Microsoft Entra ID** everywhere (control plane, Workload Identity for pods, node access). Avoid static credentials.\n- Azure Key Vault via **Secrets Store CSI Driver** for secrets\n- Enable **Azure Policy** + **Deployment Safeguards**\n- Enable **Encryption at rest** for etcd\u002FAPI server; **in-transit** for node-to-node\n- Allow only signed, policy-approved images (Azure Policy + Ratify), prefer **Azure Container Registry**\n- **Isolation**: Use namespaces, network policies, scoped logging\n\n### 4. Observability\n- Use Managed Prometheus and Container Insights with Grafana for AKS observability (logs + metrics).\n- Enable Diagnostic Settings to collect control plane logs and audit logs in a Log Analytics workspace for security monitoring and troubleshooting.\n- For other monitoring and troubleshooting tools, use features like the Agentic CLI for AKS, Application Insights, Resource Health Center, AppLens detectors, and Azure Advisors.\n\n### 5. Upgrades & Patching\n- Configure **Maintenance Windows** for controlled upgrade timing\n- Enable **auto-upgrades** for control plane and node OS to stay up-to-date with security patches and Kubernetes versions\n- Consider **LTS versions** for enterprise stability (2-year support) by upgrading your AKS environment to the Premium tier\n- **Fleet upgrades**: Use **AKS Fleet Manager** for staged rollout across test to production environments\n\n### 6. Performance\n- Use **Ephemeral OS disks** (`--node-osdisk-type Ephemeral`) for faster node startup\n- Select **Azure Linux** as node OS (smaller footprint, faster boot)\n- Enable **KEDA** for event-driven autoscaling beyond HPA\n\n### 7. Node Pools & Compute\n- **Dedicated system node pool**: At least 2 nodes, tainted for system workloads only (`CriticalAddonsOnly`)\n- Enable **Node Auto Provisioning (NAP)** on all pools for cost savings and responsive scaling\n- Use **latest generation SKUs (v5\u002Fv6)** for host-level optimizations\n- **Avoid B-series VMs** — burstable SKUs cause performance\u002Freliability issues\n- Use SKUs with **at least 4 vCPUs** for production workloads\n- Set **topology spread constraints** to distribute pods across hosts\u002Fzones per SLO\n\n### 8. Reliability\n- Deploy across **3 Availability Zones** (`--zones 1 2 3`)\n- Use **Standard tier** for zone-redundant control plane + 99.95% SLA for API server availability\n- Enable **Microsoft Defender for Containers** for runtime protection\n- Configure **PodDisruptionBudgets** for all production workloads\n- Use **topology spread constraints** to ensure pod distribution across failure domains\n\n### 9. Cost Controls\n- Use **Spot node pools** for batch\u002Finterruptible workloads (up to 90% savings)\n- **Stop\u002FStart** dev\u002Ftest clusters: `az aks stop\u002Fstart`\n- Consider **Reserved Instances** or **Savings Plans** for steady-state workloads\n\n**Deep-dive scenarios** — load only the relevant reference file:\n\n| Scenario | Trigger Keywords | Reference |\n|----------|-----------------|-----------|\n| Pod Rightsizing | over-provisioned pods, CPU requests, memory requests, rightsize workloads | [azure-aks-rightsizing.md](.\u002Freferences\u002Fazure-aks-rightsizing.md) |\n| VPA Setup | vertical pod autoscaler, VPA recommendations, VPA enable | [azure-aks-vpa.md](.\u002Freferences\u002Fazure-aks-vpa.md) |\n| Cluster Autoscaler | idle nodes, CAS off, enable autoscaler, scale-down profile, node utilization | [azure-aks-autoscaler.md](.\u002Freferences\u002Fazure-aks-autoscaler.md) |\n| Spot Node Pools | Spot VMs, Spot nodes, batch workloads, cheaper nodes | [azure-aks-spot.md](.\u002Freferences\u002Fazure-aks-spot.md) |\n\n> **Disambiguation:** If a prompt matches multiple rows (e.g., \"cheaper nodes\" could suggest both Spot and autoscaler), prefer the most specific match. If ambiguous, ask the user to clarify their intent before loading a reference file.\n\n## Guardrails \u002F Safety\n- Do not request or output secrets (tokens, keys).\n- Do not ask the user to paste subscription IDs. Discover subscription and resource scope via MCP tools (e.g., list subscriptions, list resource groups) or `az account show` \u002F `az account list` so the agent can resolve context without exposing identifiers.\n- 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.\n- Do not promise zero downtime; advise workload safeguards (PDBs, probes, replicas) and staged upgrades along with best practices for reliability and performance.\n\n## MCP Tools\n| Tool | Purpose | Key Parameters |\n|------|---------|----------------|\n| `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 |\n\n## Error Handling\n| Error \u002F Symptom | Likely Cause | Remediation |\n|-----------------|--------------|-------------|\n| 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 |\n| Quota exceeded | Regional vCPU or resource limits | Request quota increase or select different region\u002FVM SKU |\n| Networking conflict (IP exhaustion) | Pod subnet too small for overlay\u002FCNI | Re-plan IP ranges; may require cluster recreation (Day-0) |\n| Workload Identity not working | Missing OIDC issuer or federated credential | Enable `--enable-oidc-issuer --enable-workload-identity`, configure federated identity |\n",{"data":41,"body":44},{"name":4,"license":31,"metadata":42,"description":6},{"author":9,"version":43},"1.2.1",{"type":45,"children":46},"root",[47,56,105,112,223,229,234,284,290,336,342,347,385,391,398,421,427,437,475,485,498,507,525,534,567,576,591,597,678,684,702,708,763,769,814,820,897,903,967,973,1021,1031,1146,1159,1165,1204,1209,1257,1263],{"type":48,"tag":49,"props":50,"children":52},"element","h1",{"id":51},"azure-kubernetes-service",[53],{"type":54,"value":55},"text","Azure Kubernetes Service",{"type":48,"tag":57,"props":58,"children":59},"blockquote",{},[60,70],{"type":48,"tag":61,"props":62,"children":63},"p",{},[64],{"type":48,"tag":65,"props":66,"children":67},"strong",{},[68],{"type":54,"value":69},"AUTHORITATIVE GUIDANCE — MANDATORY COMPLIANCE",{"type":48,"tag":61,"props":71,"children":72},{},[73,75,80,82,87,89,94,96,103],{"type":54,"value":74},"This skill produces a ",{"type":48,"tag":65,"props":76,"children":77},{},[78],{"type":54,"value":79},"recommended AKS cluster configuration",{"type":54,"value":81}," based on user requirements, distinguishing ",{"type":48,"tag":65,"props":83,"children":84},{},[85],{"type":54,"value":86},"Day-0 decisions",{"type":54,"value":88}," (networking, API server — hard to change later) from ",{"type":48,"tag":65,"props":90,"children":91},{},[92],{"type":54,"value":93},"Day-1 features",{"type":54,"value":95}," (can enable post-creation). 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If ambiguous, ask the user to clarify their intent before loading a reference file.",{"type":48,"tag":106,"props":1160,"children":1162},{"id":1161},"guardrails-safety",[1163],{"type":54,"value":1164},"Guardrails \u002F Safety",{"type":48,"tag":235,"props":1166,"children":1167},{},[1168,1173,1194,1199],{"type":48,"tag":239,"props":1169,"children":1170},{},[1171],{"type":54,"value":1172},"Do not request or output secrets (tokens, keys).",{"type":48,"tag":239,"props":1174,"children":1175},{},[1176,1178,1184,1186,1192],{"type":54,"value":1177},"Do not ask the user to paste subscription IDs. Discover subscription and resource scope via MCP tools (e.g., list subscriptions, list resource groups) or ",{"type":48,"tag":165,"props":1179,"children":1181},{"className":1180},[],[1182],{"type":54,"value":1183},"az account show",{"type":54,"value":1185}," \u002F ",{"type":48,"tag":165,"props":1187,"children":1189},{"className":1188},[],[1190],{"type":54,"value":1191},"az account list",{"type":54,"value":1193}," so the agent can resolve context without exposing identifiers.",{"type":48,"tag":239,"props":1195,"children":1196},{},[1197],{"type":54,"value":1198},"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.",{"type":48,"tag":239,"props":1200,"children":1201},{},[1202],{"type":54,"value":1203},"Do not promise zero downtime; advise workload safeguards (PDBs, probes, replicas) and staged upgrades along with best practices for reliability and performance.",{"type":48,"tag":106,"props":1205,"children":1207},{"id":1206},"mcp-tools",[1208],{"type":54,"value":160},{"type":48,"tag":113,"props":1210,"children":1211},{},[1212,1233],{"type":48,"tag":117,"props":1213,"children":1214},{},[1215],{"type":48,"tag":121,"props":1216,"children":1217},{},[1218,1223,1228],{"type":48,"tag":125,"props":1219,"children":1220},{},[1221],{"type":54,"value":1222},"Tool",{"type":48,"tag":125,"props":1224,"children":1225},{},[1226],{"type":54,"value":1227},"Purpose",{"type":48,"tag":125,"props":1229,"children":1230},{},[1231],{"type":54,"value":1232},"Key Parameters",{"type":48,"tag":136,"props":1234,"children":1235},{},[1236],{"type":48,"tag":121,"props":1237,"children":1238},{},[1239,1247,1252],{"type":48,"tag":143,"props":1240,"children":1241},{},[1242],{"type":48,"tag":165,"props":1243,"children":1245},{"className":1244},[],[1246],{"type":54,"value":170},{"type":48,"tag":143,"props":1248,"children":1249},{},[1250],{"type":54,"value":1251},"AKS MCP entry point used to discover the exact AKS-specific tools exposed by the client",{"type":48,"tag":143,"props":1253,"children":1254},{},[1255],{"type":54,"value":1256},"Discover the callable AKS tool first, then use that tool's parameters",{"type":48,"tag":106,"props":1258,"children":1260},{"id":1259},"error-handling",[1261],{"type":54,"value":1262},"Error Handling",{"type":48,"tag":113,"props":1264,"children":1265},{},[1266,1287],{"type":48,"tag":117,"props":1267,"children":1268},{},[1269],{"type":48,"tag":121,"props":1270,"children":1271},{},[1272,1277,1282],{"type":48,"tag":125,"props":1273,"children":1274},{},[1275],{"type":54,"value":1276},"Error \u002F Symptom",{"type":48,"tag":125,"props":1278,"children":1279},{},[1280],{"type":54,"value":1281},"Likely Cause",{"type":48,"tag":125,"props":1283,"children":1284},{},[1285],{"type":54,"value":1286},"Remediation",{"type":48,"tag":136,"props":1288,"children":1289},{},[1290,1323,1341,1359],{"type":48,"tag":121,"props":1291,"children":1292},{},[1293,1298,1303],{"type":48,"tag":143,"props":1294,"children":1295},{},[1296],{"type":54,"value":1297},"MCP tool call fails or times out",{"type":48,"tag":143,"props":1299,"children":1300},{},[1301],{"type":54,"value":1302},"Invalid credentials, subscription, or AKS context",{"type":48,"tag":143,"props":1304,"children":1305},{},[1306,1308,1314,1316,1321],{"type":54,"value":1307},"Verify ",{"type":48,"tag":165,"props":1309,"children":1311},{"className":1310},[],[1312],{"type":54,"value":1313},"az login",{"type":54,"value":1315},", confirm the active subscription context with ",{"type":48,"tag":165,"props":1317,"children":1319},{"className":1318},[],[1320],{"type":54,"value":1183},{"type":54,"value":1322},", and check the target resource group without echoing subscription identifiers back to the user",{"type":48,"tag":121,"props":1324,"children":1325},{},[1326,1331,1336],{"type":48,"tag":143,"props":1327,"children":1328},{},[1329],{"type":54,"value":1330},"Quota exceeded",{"type":48,"tag":143,"props":1332,"children":1333},{},[1334],{"type":54,"value":1335},"Regional vCPU or resource limits",{"type":48,"tag":143,"props":1337,"children":1338},{},[1339],{"type":54,"value":1340},"Request quota increase or select different region\u002FVM SKU",{"type":48,"tag":121,"props":1342,"children":1343},{},[1344,1349,1354],{"type":48,"tag":143,"props":1345,"children":1346},{},[1347],{"type":54,"value":1348},"Networking conflict (IP exhaustion)",{"type":48,"tag":143,"props":1350,"children":1351},{},[1352],{"type":54,"value":1353},"Pod subnet too small for overlay\u002FCNI",{"type":48,"tag":143,"props":1355,"children":1356},{},[1357],{"type":54,"value":1358},"Re-plan IP ranges; may require cluster recreation (Day-0)",{"type":48,"tag":121,"props":1360,"children":1361},{},[1362,1367,1372],{"type":48,"tag":143,"props":1363,"children":1364},{},[1365],{"type":54,"value":1366},"Workload Identity not working",{"type":48,"tag":143,"props":1368,"children":1369},{},[1370],{"type":54,"value":1371},"Missing OIDC issuer or federated credential",{"type":48,"tag":143,"props":1373,"children":1374},{},[1375,1376,1382],{"type":54,"value":583},{"type":48,"tag":165,"props":1377,"children":1379},{"className":1378},[],[1380],{"type":54,"value":1381},"--enable-oidc-issuer --enable-workload-identity",{"type":54,"value":1383},", configure federated identity",{"items":1385,"total":1509},[1386,1400,1414,1435,1456,1473,1491],{"slug":1387,"name":1387,"fn":1388,"description":1389,"org":1390,"tags":1391,"stars":28,"repoUrl":29,"updatedAt":1399},"airunway-aks-setup","set up AI Runway on Azure Kubernetes Service","Set up AI Runway on AKS — from bare cluster to running model. Covers cluster verification, controller install, GPU assessment, provider setup, and first deployment. WHEN: \"setup AI Runway\", \"onboard AKS cluster\", \"install AI Runway\", \"airunway setup\", \"deploy model to AKS\", \"GPU inference on AKS\", \"KAITO setup on AKS\", \"run LLM on AKS\", \"vLLM on AKS\", \"set up model serving on AKS\", \"AI Runway controller\".",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1392,1393,1394,1395,1396],{"name":23,"slug":24,"type":15},{"name":13,"slug":14,"type":15},{"name":20,"slug":21,"type":15},{"name":26,"slug":27,"type":15},{"name":1397,"slug":1398,"type":15},"Runway","runway","2026-07-31T05:56:13.054971",{"slug":1401,"name":1401,"fn":1402,"description":1403,"org":1404,"tags":1405,"stars":28,"repoUrl":29,"updatedAt":1413},"appinsights-instrumentation","instrument webapps with Azure Application Insights","Guidance for instrumenting webapps with Azure Application Insights. Provides telemetry patterns, SDK setup, and configuration references. WHEN: how to instrument app, App Insights SDK, telemetry patterns, what is App Insights, Application Insights guidance, instrumentation examples, APM best practices.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1406,1407,1410],{"name":13,"slug":14,"type":15},{"name":1408,"slug":1409,"type":15},"Monitoring","monitoring",{"name":1411,"slug":1412,"type":15},"Observability","observability","2026-07-31T05:56:09.068625",{"slug":1415,"name":1415,"fn":1416,"description":1417,"org":1418,"tags":1419,"stars":28,"repoUrl":29,"updatedAt":1434},"azure-ai","build applications with Azure AI services","Use for Azure AI: Search, Speech, OpenAI, Document Intelligence. Helps with search, vector\u002Fhybrid search, speech-to-text, text-to-speech, transcription, OCR. WHEN: AI Search, query search, vector search, hybrid search, semantic search, speech-to-text, text-to-speech, transcribe, OCR, convert text to speech.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1420,1421,1422,1425,1428,1431],{"name":23,"slug":24,"type":15},{"name":13,"slug":14,"type":15},{"name":1423,"slug":1424,"type":15},"LLM","llm",{"name":1426,"slug":1427,"type":15},"OpenAI","openai",{"name":1429,"slug":1430,"type":15},"Search","search",{"name":1432,"slug":1433,"type":15},"Speech","speech","2026-07-31T05:56:19.069133",{"slug":1436,"name":1436,"fn":1437,"description":1438,"org":1439,"tags":1440,"stars":28,"repoUrl":29,"updatedAt":1455},"azure-aigateway","configure Azure API Management as an AI Gateway","Configure Azure API Management as an AI Gateway for AI models, MCP tools, and agents. WHEN: semantic caching, token limit, content safety, load balancing, AI model governance, MCP rate limiting, jailbreak detection, add Azure OpenAI backend, add AI Foundry model, test AI gateway, LLM policies, configure AI backend, token metrics, AI cost control, convert API to MCP, import OpenAPI to gateway.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1441,1442,1445,1446,1449,1452],{"name":23,"slug":24,"type":15},{"name":1443,"slug":1444,"type":15},"API Development","api-development",{"name":13,"slug":14,"type":15},{"name":1447,"slug":1448,"type":15},"Caching","caching",{"name":1450,"slug":1451,"type":15},"Governance","governance",{"name":1453,"slug":1454,"type":15},"Security","security","2026-07-31T05:56:23.05242",{"slug":1457,"name":1457,"fn":1458,"description":1459,"org":1460,"tags":1461,"stars":28,"repoUrl":29,"updatedAt":1472},"azure-cloud-migrate","migrate cross-cloud workloads to Azure","Assess and migrate cross-cloud workloads to Azure with reports and code conversion. Supports Lambda→Functions, Beanstalk\u002FHeroku\u002FApp Engine→App Service, Fargate\u002FKubernetes\u002FCloud Run\u002FSpring Boot→Container Apps. WHEN: migrate Lambda to Functions, AWS to Azure, migrate Beanstalk, migrate Heroku, migrate App Engine, Cloud Run migration, Fargate to ACA, ECS\u002FKubernetes\u002FGKE\u002FEKS to Container Apps, Spring Boot to Container Apps, cross-cloud migration.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1462,1465,1466,1469],{"name":1463,"slug":1464,"type":15},"AWS","aws",{"name":13,"slug":14,"type":15},{"name":1467,"slug":1468,"type":15},"Google Cloud","google-cloud",{"name":1470,"slug":1471,"type":15},"Migration","migration","2026-07-31T05:56:29.049979",{"slug":1474,"name":1474,"fn":1475,"description":1476,"org":1477,"tags":1478,"stars":28,"repoUrl":29,"updatedAt":1490},"azure-compliance","audit Azure compliance and security","Run Azure compliance and security audits with azqr plus Key Vault expiration checks. Covers best-practice assessment, resource review, policy\u002Fcompliance validation, and security posture checks. WHEN: compliance scan, security audit, BEFORE running azqr (compliance cli tool), Azure best practices, Key Vault expiration check, expired certificates, expiring secrets, orphaned resources, compliance assessment.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1479,1482,1483,1486,1489],{"name":1480,"slug":1481,"type":15},"Audit","audit",{"name":13,"slug":14,"type":15},{"name":1484,"slug":1485,"type":15},"Compliance","compliance",{"name":1487,"slug":1488,"type":15},"Regulatory Compliance","regulatory-compliance",{"name":1453,"slug":1454,"type":15},"2026-07-31T05:56:11.06797",{"slug":1492,"name":1492,"fn":1493,"description":1494,"org":1495,"tags":1496,"stars":28,"repoUrl":29,"updatedAt":1508},"azure-compute","manage and optimize Azure compute resources","Azure VM\u002FVMSS router. WHEN: create \u002F provision \u002F deploy \u002F spin-up VM, recommend VM size, compare VM pricing, VMSS, scale set, autoscale, burstable, lightweight server, website, backend, GPU, machine learning, HPC simulation, dev\u002Ftest, workload, family, load balancer, Flexible orchestration, Uniform orchestration, cost estimate, capacity reservation (CRG), reserve, guarantee capacity, pre-provision, CRG association, CRG disassociation, machine enrollment (EMM), Essential Machine Management, monitor. PREFER OVER mcp__azure__get_azure_bestpractices for VM create intents — use compute_vm_list-skus \u002F compute_vm_list-images \u002F compute_vm_check-quota.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1497,1498,1499,1502,1505],{"name":23,"slug":24,"type":15},{"name":13,"slug":14,"type":15},{"name":1500,"slug":1501,"type":15},"Cost Optimization","cost-optimization",{"name":1503,"slug":1504,"type":15},"Performance","performance",{"name":1506,"slug":1507,"type":15},"Virtual Machines","virtual-machines","2026-07-31T05:56:16.042469",28,{"items":1511,"total":1692},[1512,1534,1551,1570,1581,1596,1607,1618,1633,1648,1667,1680],{"slug":1513,"name":1513,"fn":1514,"description":1515,"org":1516,"tags":1517,"stars":1531,"repoUrl":1532,"updatedAt":1533},"rushstack-best-practices","manage Rush monorepos with best practices","Provides best practices and guidance for working with Rush monorepos. Use when the user is working in a Rush-based repository, asks about Rush commands (install, update, build, rebuild), needs help with project selection, dependency management, build caching, subspace configuration, or troubleshooting Rush-specific issues.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1518,1521,1524,1525,1528],{"name":1519,"slug":1520,"type":15},"Engineering","engineering",{"name":1522,"slug":1523,"type":15},"Local Development","local-development",{"name":9,"slug":8,"type":15},{"name":1526,"slug":1527,"type":15},"Project Management","project-management",{"name":1529,"slug":1530,"type":15},"Rush","rush",6484,"https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Frushstack","2026-04-06T18:34:44.965032",{"slug":1535,"name":1535,"fn":1536,"description":1537,"org":1538,"tags":1539,"stars":1548,"repoUrl":1549,"updatedAt":1550},"azure-ai-agents-persistent-dotnet","build AI agents with Azure .NET SDK","Azure AI Agents Persistent SDK for .NET. Low-level SDK for creating and managing AI agents with threads, messages, runs, and tools. Use for agent CRUD, conversation threads, streaming responses, function calling, file search, and code interpreter. Triggers: \"PersistentAgentsClient\", \"persistent agents\", \"agent threads\", \"agent runs\", \"streaming agents\", \"function calling agents .NET\".\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1540,1543,1546,1547],{"name":1541,"slug":1542,"type":15},".NET","net",{"name":1544,"slug":1545,"type":15},"Agents","agents",{"name":13,"slug":14,"type":15},{"name":1423,"slug":1424,"type":15},2804,"https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fskills","2026-07-03T16:32:10.297433",{"slug":1552,"name":1552,"fn":1553,"description":1554,"org":1555,"tags":1556,"stars":1548,"repoUrl":1549,"updatedAt":1569},"azure-ai-anomalydetector-java","build anomaly detection applications with Java","Build anomaly detection applications with Azure AI Anomaly Detector SDK for Java. Use when implementing univariate\u002Fmultivariate anomaly detection, time-series analysis, or AI-powered monitoring.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1557,1560,1561,1564,1567,1568],{"name":1558,"slug":1559,"type":15},"Analytics","analytics",{"name":13,"slug":14,"type":15},{"name":1562,"slug":1563,"type":15},"Data Analysis","data-analysis",{"name":1565,"slug":1566,"type":15},"Java","java",{"name":9,"slug":8,"type":15},{"name":1408,"slug":1409,"type":15},"2026-05-13T06:14:16.261754",{"slug":1571,"name":1571,"fn":1572,"description":1573,"org":1574,"tags":1575,"stars":1548,"repoUrl":1549,"updatedAt":1580},"azure-ai-contentsafety-java","build content moderation applications with Azure AI","Build content moderation applications with Azure AI Content Safety SDK for Java. Use when implementing text\u002Fimage analysis, blocklist management, or harm detection for hate, violence, sexual content, and self-harm.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1576,1577,1578,1579],{"name":23,"slug":24,"type":15},{"name":13,"slug":14,"type":15},{"name":1565,"slug":1566,"type":15},{"name":1453,"slug":1454,"type":15},"2026-07-07T06:53:31.293235",{"slug":1582,"name":1582,"fn":1583,"description":1584,"org":1585,"tags":1586,"stars":1548,"repoUrl":1549,"updatedAt":1595},"azure-ai-contentsafety-py","detect harmful content with Azure AI Content Safety","Azure AI Content Safety SDK for Python. Use for detecting harmful content in text and images with multi-severity classification.\nTriggers: \"azure-ai-contentsafety\", \"ContentSafetyClient\", \"content moderation\", \"harmful content\", \"text analysis\", \"image analysis\".\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1587,1588,1589,1590,1591,1594],{"name":13,"slug":14,"type":15},{"name":1484,"slug":1485,"type":15},{"name":1423,"slug":1424,"type":15},{"name":9,"slug":8,"type":15},{"name":1592,"slug":1593,"type":15},"Python","python",{"name":1453,"slug":1454,"type":15},"2026-07-18T05:14:23.017504",{"slug":1597,"name":1597,"fn":1598,"description":1599,"org":1600,"tags":1601,"stars":1548,"repoUrl":1549,"updatedAt":1606},"azure-ai-language-conversations-py","implement conversational language understanding with Python","Implement Conversational Language Understanding (CLU) using the azure-ai-language-conversations Python SDK. Use when working with ConversationAnalysisClient to analyze conversation intent and entities, building NLP features, or integrating language understanding into applications.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1602,1603,1604,1605],{"name":1558,"slug":1559,"type":15},{"name":13,"slug":14,"type":15},{"name":1423,"slug":1424,"type":15},{"name":1592,"slug":1593,"type":15},"2026-07-31T05:54:29.068751",{"slug":1608,"name":1608,"fn":1609,"description":1610,"org":1611,"tags":1612,"stars":1548,"repoUrl":1549,"updatedAt":1617},"azure-ai-translation-text-py","translate text using Azure AI services","Azure AI Text Translation SDK for real-time text translation, transliteration, language detection, and dictionary lookup. Use for translating text content in applications.\nTriggers: \"text translation\", \"translator\", \"translate text\", \"transliterate\", \"TextTranslationClient\".\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1613,1614,1615,1616],{"name":1443,"slug":1444,"type":15},{"name":13,"slug":14,"type":15},{"name":9,"slug":8,"type":15},{"name":1592,"slug":1593,"type":15},"2026-07-18T05:14:16.988376",{"slug":1619,"name":1619,"fn":1620,"description":1621,"org":1622,"tags":1623,"stars":1548,"repoUrl":1549,"updatedAt":1632},"azure-ai-vision-imageanalysis-py","analyze images with Azure AI Vision","Azure AI Vision Image Analysis SDK for captions, tags, objects, OCR, people detection, and smart cropping. Use for computer vision and image understanding tasks.\nTriggers: \"image analysis\", \"computer vision\", \"OCR\", \"object detection\", \"ImageAnalysisClient\", \"image caption\".\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1624,1625,1628,1631],{"name":13,"slug":14,"type":15},{"name":1626,"slug":1627,"type":15},"Computer Vision","computer-vision",{"name":1629,"slug":1630,"type":15},"Images","images",{"name":1592,"slug":1593,"type":15},"2026-07-18T05:14:18.007737",{"slug":1634,"name":1634,"fn":1635,"description":1636,"org":1637,"tags":1638,"stars":1548,"repoUrl":1549,"updatedAt":1647},"azure-appconfiguration-java","manage configuration with Azure App Configuration","Azure App Configuration SDK for Java. Centralized application configuration management with key-value settings, feature flags, and snapshots.\nTriggers: \"ConfigurationClient java\", \"app configuration java\", \"feature flag java\", \"configuration setting java\", \"azure config java\".\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1639,1640,1643,1646],{"name":13,"slug":14,"type":15},{"name":1641,"slug":1642,"type":15},"Configuration","configuration",{"name":1644,"slug":1645,"type":15},"Feature Flags","feature-flags",{"name":1565,"slug":1566,"type":15},"2026-07-03T16:32:01.278468",{"slug":1649,"name":1649,"fn":1650,"description":1651,"org":1652,"tags":1653,"stars":1548,"repoUrl":1549,"updatedAt":1666},"azure-cosmos-rust","build applications with Azure Cosmos DB","Azure Cosmos DB library for Rust (NoSQL API). Document CRUD, containers, and globally distributed data.\nTriggers: \"cosmos db rust\", \"CosmosClient rust\", \"document crud rust\", \"NoSQL rust\", \"partition key rust\".\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1654,1657,1660,1663],{"name":1655,"slug":1656,"type":15},"Cosmos DB","cosmos-db",{"name":1658,"slug":1659,"type":15},"Database","database",{"name":1661,"slug":1662,"type":15},"NoSQL","nosql",{"name":1664,"slug":1665,"type":15},"Rust","rust","2026-07-31T05:54:27.021432",{"slug":1668,"name":1668,"fn":1650,"description":1669,"org":1670,"tags":1671,"stars":1548,"repoUrl":1549,"updatedAt":1679},"azure-cosmos-ts","Azure Cosmos DB JavaScript\u002FTypeScript SDK (@azure\u002Fcosmos) for data plane operations. Use for CRUD operations on documents, queries, bulk operations, and container management. Triggers: \"Cosmos DB\", \"@azure\u002Fcosmos\", \"CosmosClient\", \"document CRUD\", \"NoSQL queries\", \"bulk operations\", \"partition key\", \"container.items\".\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1672,1673,1674,1675,1676],{"name":1655,"slug":1656,"type":15},{"name":1658,"slug":1659,"type":15},{"name":9,"slug":8,"type":15},{"name":1661,"slug":1662,"type":15},{"name":1677,"slug":1678,"type":15},"TypeScript","typescript","2026-07-03T16:31:19.368382",{"slug":1681,"name":1681,"fn":1682,"description":1683,"org":1684,"tags":1685,"stars":1548,"repoUrl":1549,"updatedAt":1691},"azure-data-tables-java","build table storage applications with Java","Build table storage applications with Azure Tables SDK for Java. Use when working with Azure Table Storage or Cosmos DB Table API for NoSQL key-value data, schemaless storage, or structured data at scale.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1686,1687,1688,1689,1690],{"name":13,"slug":14,"type":15},{"name":1655,"slug":1656,"type":15},{"name":1658,"slug":1659,"type":15},{"name":1565,"slug":1566,"type":15},{"name":1661,"slug":1662,"type":15},"2026-05-13T06:14:17.582229",267]