azure-stream-analytics
About azure-stream-analytics
A reference skill for agents working with Azure Stream Analytics, pairing local quick-reference material with remote documentation retrieval. It covers job design, troubleshooting, security, integrations, and deployment.
Key features
- 01Job error and performance diagnosis
- 02Query and job design guidance
- 03Scaling and architecture planning
- 04Security configuration references
- 05Integration and coding patterns
Use cases
- 01Finding input, output, or query errors
- 02Improving job performance and parallelization
- 03Planning job scaling and deployment
MCP support
The skill can retrieve remote documentation through mcp_microsoftdocs tools; its instructions describe fetch_webpage as a fallback.
Install
Copy the command and run it in a terminal.
npx skills add https:/ / github.com/ microsoftdocs/ agent-skills --skill azure-stream-analyticsAfter installing, type/azure-stream-analyticsin Claude Code to confirm it loaded.
Details
From the project READMEAzure Stream Analytics 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.
How to Use This Skill
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:
- Preferred: Use
mcp_microsoftdocs:microsoft_docs_fetchwith query stringfrom=learn-agent-skill. Returns Markdown. - Fallback: Use
fetch_webpagewith query stringfrom=learn-agent-skill&accept=text/markdown. Returns Markdown.
Category Index
| Category | Lines | Description |
|---|---|---|
| Troubleshooting | L37-L58 | Diagnosing and fixing Stream Analytics job errors (config, data, internal/external), performance issues, and input/output/query problems using logs and job diagrams (logical/physical). |
| Best Practices | L59-L73 | 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 | L74-L82 | Guidance on choosing Stream Analytics tools and services, migrating from Visual Studio/.NET UDFs, and configuring autoscale and real-time processing options. |
| 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-L96 | Limits, sizing, and performance of Stream Analytics: Event Hubs output size caps, streaming unit/cluster scaling, and IoT Edge-specific limits and support. |
| Security | L97-L117 | Securing Stream Analytics jobs: managed identities for inputs/outputs (Event Hubs, SQL, Synapse, Cosmos, Blob, Service Bus, Power BI), VNet/private endpoints, data protection, and Azure Policy compliance. |
| Configuration | L118-L149 | Configuring Stream Analytics jobs: inputs, outputs (Cosmos DB, SQL, Event Hubs, Kafka, Power BI, Delta Lake, etc.), autoscale, ordering, error handling, monitoring, and compatibility. |
| Integrations & Coding Patterns | L150-L166 | Patterns and code for integrating Stream Analytics with Kafka, SQL, Azure ML, UDFs (C#/JS), anomaly detection, schema registry, and advanced scenarios like HFT and .NET job management |
| Deployment | L167-L180 | Automating deployment, migration, and lifecycle (start/stop/delete) of Stream Analytics jobs and clusters using ARM/Bicep, GitHub Actions, Azure DevOps, REST, and edge/Stack Hub tools |
Troubleshooting
Best Practices
Decision Making
| Topic | URL |
|---|---|
| Choose Azure Stream Analytics portal vs VS Code tools | 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 |
| Migrate from .NET UDFs to JavaScript in Stream Analytics | https://learn.microsoft.com/en-us/azure/stream-analytics/stream-analytics-edge-csharp-udf-methods |
| Choose Azure real-time and stream processing services | https://learn.microsoft.com/en-us/azure/stream-analytics/streaming-technologies |
Architecture & Design Patterns
| 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 |
Limits & Quotas
| Topic | URL |
|---|---|
| Use Event Hubs as Stream Analytics output with size limits | https://learn.microsoft.com/en-us/azure/stream-analytics/event-hubs-output |
| 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 |