From azure-agent-skills
Azure Stream Analytics skill covering troubleshooting, best practices, architecture, patterns, security, and deployment. Use when building ASA jobs with Event Hubs, Cosmos DB, SQL, ML, IoT Edge, or Power BI.
How this skill is triggered — by the user, by Claude, or both
Slash command
/azure-agent-skills:azure-stream-analyticsThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
This skill provides expert guidance for Azure Stream Analytics. 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 Stream Analytics. 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-L56 | Diagnosing and fixing Stream Analytics job issues: error codes (config, data, internal/external), input/output and query problems, and debugging with job diagrams, metrics, logs, and UDF tools. |
| Best Practices | L57-L74 | Best practices for Stream Analytics job design, query patterns, performance tuning, scaling, reliability, time handling, geospatial logic, ML/Cosmos/SQL outputs, and alerting. |
| Decision Making | L75-L82 | Guidance on choosing tools, migration paths, autoscaling options, and comparing Azure real-time/stream processing services for designing Stream Analytics solutions. |
| Architecture & Design Patterns | L83-L88 | Designing resilient, geo-redundant Stream Analytics topologies and scaling jobs using Streaming Units, input/output partitioning, and performance tuning patterns. |
| Limits & Quotas | L89-L95 | Info on Stream Analytics capacity limits, streaming units (SUs), how to size/resize clusters, performance tuning, and specific constraints for Azure Stream Analytics on IoT Edge. |
| Security | L96-L115 | Securing Stream Analytics jobs with managed identities, private endpoints, VNets, data protection, credential rotation, and Azure Policy for outputs like Event Hubs, SQL, ADX, Cosmos DB, and Power BI |
| Configuration | L116-L149 | Configuring Stream Analytics jobs: inputs, outputs (SQL, Cosmos DB, Event Hubs, Kafka, Power BI, Delta Lake, etc.), autoscale, ordering, error handling, monitoring, and compatibility settings. |
| Integrations & Coding Patterns | L150-L169 | Patterns for integrating Stream Analytics with Kafka, Event Hubs, ML/AML, schema registry, and custom code (C#/JS UDFs/aggregates), plus JSON/Avro parsing and advanced scenarios like HFT. |
| Deployment | L170-L182 | Deploying, starting/stopping, scaling, and moving Stream Analytics jobs and clusters, plus CI/CD automation via ARM/Bicep, GitHub Actions, Azure DevOps, npm/NuGet, and IoT Edge/Stack Hub. |
| Topic | URL |
|---|---|
| Select developer tools for Azure Stream Analytics jobs | https://learn.microsoft.com/en-us/azure/stream-analytics/feature-comparison |
| Migrate Stream Analytics projects from Visual Studio to VS Code | https://learn.microsoft.com/en-us/azure/stream-analytics/migrate-to-vscode |
| Choose and configure autoscale for Stream Analytics SUs | https://learn.microsoft.com/en-us/azure/stream-analytics/stream-analytics-autoscale |
| Choose Azure real-time and stream processing services | https://learn.microsoft.com/en-us/azure/stream-analytics/streaming-technologies |
| Topic | URL |
|---|---|
| Design geo-redundant Azure Stream Analytics job architectures | https://learn.microsoft.com/en-us/azure/stream-analytics/geo-redundancy |
| Scale Azure Stream Analytics jobs with SUs and partitioning | https://learn.microsoft.com/en-us/azure/stream-analytics/stream-analytics-scale-jobs |
| Topic | URL |
|---|---|
| Resize Azure Stream Analytics clusters by streaming units | https://learn.microsoft.com/en-us/azure/stream-analytics/scale-cluster |
| Understand Azure Stream Analytics on IoT Edge limits and support | https://learn.microsoft.com/en-us/azure/stream-analytics/stream-analytics-edge |
| Understand and tune Azure Stream Analytics streaming units | https://learn.microsoft.com/en-us/azure/stream-analytics/stream-analytics-streaming-unit-consumption |
npx claudepluginhub microsoftdocs/agent-skills --plugin azure-agent-skillsProvides expert guidance for Azure Data Explorer (ADX) development including troubleshooting, best practices, architecture, security, and deployment. Activates when working with ADX clusters, private endpoints, ingestion, or Power BI integration.
Manages MongoDB Atlas Stream Processing (ASP) workflows: workspace provisioning, data source/sink connections, processor lifecycle, debugging diagnostics, and tier sizing. Supports Kafka, Atlas clusters, S3, HTTPS, and Lambda integrations.
Manages MongoDB Atlas Stream Processing pipelines: provisions workspaces, configures Kafka/Atlas/S3/Lambda connections, operates processors, debugs issues, sizes tiers.