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Provides expert guidance for Azure Data Explorer development: troubleshooting, best practices, architecture, security, and deployment. Use for ADX clusters, KQL queries, ingestion, and Power BI integration.
How this skill is triggered — by the user, by Claude, or both
Slash command
/azure-agent-skills:azure-data-explorerThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
This skill provides expert guidance for Azure Data Explorer. Covers troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. It combines local quick-reference content with remote documentation fetching capabilities.
This skill provides expert guidance for Azure Data Explorer. Covers troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. It combines local quick-reference content with remote documentation fetching capabilities.
IMPORTANT for Agent: Use the Category Index below to locate relevant sections. For categories with line ranges (e.g.,
L35-L120), useread_filewith the specified lines. For categories with file links (e.g.,[security.md](security.md)), useread_fileon the linked reference file
IMPORTANT for Agent: If
metadata.generated_atis more than 3 months old, suggest the user pull the latest version from the repository. Ifmcp_microsoftdocstools are not available, suggest the user install it: Installation Guide
This skill requires network access to fetch documentation content:
mcp_microsoftdocs:microsoft_docs_fetch with query string from=learn-agent-skill. Returns Markdown.fetch_webpage with query string from=learn-agent-skill&accept=text/markdown. Returns Markdown.| Category | Lines | Description |
|---|---|---|
| Troubleshooting | L37-L48 | Diagnosing and fixing ADX cluster health, creation, connection, private endpoint, ingestion, and DB/table operation errors, including interpreting ingestion error codes and using Resource Health. |
| Best Practices | L49-L59 | Guidance on ADX performance and reliability: schema design, handling duplicates, JSON ingestion, monitoring queued ingestion, hot/cold data querying, high concurrency, and Power BI integration. |
| Decision Making | L60-L74 | Guidance on ADX cluster sizing and SKUs, cost and reservations, business continuity, confidential/isolated compute, streaming ingestion choices, and migrating from Elasticsearch. |
| Architecture & Design Patterns | L75-L81 | Patterns for ADX deployment: regional DR and replication, cross-cluster access via follower DBs, and multitenant cluster/database design choices. |
| Limits & Quotas | L82-L91 | Cluster limits and behaviors: free cluster quotas, auto-stop, safe delete/recover, ingestion file size and invalid data handling, and supported data/compression formats. |
| Security | L92-L119 | Configuring ADX security: auth/RBAC, managed identities, encryption/CMK, network isolation (private endpoints, outbound/public access), policies, compliance, and data privacy (purge). |
| Configuration | L120-L134 | Configuring ADX clusters, schemas, policies, plugins, and data connections, plus emulator setup, KQL/T-SQL use, monitoring refs, and web UI settings/profiles/shortcuts. |
| Integrations & Coding Patterns | L135-L168 | Integrating ADX with tools and services (SQL, ODBC/JDBC, Power Automate/Apps, Functions, Grafana, Splunk, OpenTelemetry, Tableau, MATLAB, etc.) and managing/automating queries and ingestion. |
| Deployment | L169-L175 | Provisioning and automating ADX environments, deploying schema via Azure DevOps, and migrating clusters to availability zones and from VNet injection to private endpoints. |
| Topic | URL |
|---|---|
| Handle duplicate data in Azure Data Explorer | https://learn.microsoft.com/en-us/azure/data-explorer/dealing-with-duplicates |
| Optimize Azure Data Explorer clusters for high-concurrency workloads | https://learn.microsoft.com/en-us/azure/data-explorer/high-concurrency |
| Use hot windows to efficiently query cold data in Azure Data Explorer | https://learn.microsoft.com/en-us/azure/data-explorer/hot-windows |
| Ingest JSON into Azure Data Explorer with KQL, C#, and Python | https://learn.microsoft.com/en-us/azure/data-explorer/ingest-json-formats |
| Monitor queued ingestion metrics in ADX | https://learn.microsoft.com/en-us/azure/data-explorer/monitor-queued-ingestion |
| Apply Power BI best practices for Azure Data Explorer | https://learn.microsoft.com/en-us/azure/data-explorer/power-bi-best-practices |
| Optimize Azure Data Explorer table schema design | https://learn.microsoft.com/en-us/azure/data-explorer/schema-best-practice |
| Topic | URL |
|---|---|
| Design ADX regional DR and replication solutions | https://learn.microsoft.com/en-us/azure/data-explorer/business-continuity-create-solution |
| Use follower databases for cross-cluster ADX access | https://learn.microsoft.com/en-us/azure/data-explorer/follower |
| Choose multitenant architectures for Azure Data Explorer | https://learn.microsoft.com/en-us/azure/data-explorer/multi-tenant |
| Topic | URL |
|---|---|
| Understand automatic stop behavior for inactive clusters | https://learn.microsoft.com/en-us/azure/data-explorer/auto-stop-clusters |
| Apply Event Grid ingestion file size limits in Azure Data Explorer | https://learn.microsoft.com/en-us/azure/data-explorer/create-event-grid-connection |
| Delete and recover Azure Data Explorer clusters safely | https://learn.microsoft.com/en-us/azure/data-explorer/delete-cluster |
| Understand invalid data behavior during ADX ingestion | https://learn.microsoft.com/en-us/azure/data-explorer/ingest-invalid-data |
| Supported data and compression formats for Azure Data Explorer ingestion | https://learn.microsoft.com/en-us/azure/data-explorer/ingestion-supported-formats |
| Upgrade free Azure Data Explorer clusters and remove limits | https://learn.microsoft.com/en-us/azure/data-explorer/start-for-free-upgrade |
| Topic | URL |
|---|---|
| Automate provisioning of Azure Data Explorer environments | https://learn.microsoft.com/en-us/azure/data-explorer/automated-deploy-overview |
| Use Azure DevOps pipelines for Azure Data Explorer schema deployment | https://learn.microsoft.com/en-us/azure/data-explorer/devops |
| Migrate Azure Data Explorer clusters to availability zones | https://learn.microsoft.com/en-us/azure/data-explorer/migrate-cluster-to-multiple-availability-zone |
| Migrate Azure Data Explorer VNet injection to private endpoints | https://learn.microsoft.com/en-us/azure/data-explorer/security-network-migrate-vnet-to-private-endpoint |
npx claudepluginhub microsoftdocs/agent-skills --plugin azure-agent-skillsQueries and analyzes data in Azure Data Explorer (Kusto/ADX) using KQL for log analytics, telemetry, time series, and anomaly detection.
Run read-only KQL queries against Fabric Eventhouse for real-time intelligence and time-series analytics using az rest. Covers schema discovery, query monitoring, and JSON export.
Run read-only KQL queries against Fabric Eventhouse using `az rest` for real-time intelligence and time-series analytics. Covers schema discovery, KQL operators, ingestion monitoring, and result export.