Azure 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 |