Agent-Skills azure-stream-analytics
Expert knowledge for Azure Stream Analytics development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when building jobs with Event Hubs/Kafka, Cosmos DB/SQL outputs, ML/Functions integration, autoscale, or SU tuning, and other Azure Stream Analytics related development tasks. Not for Azure Data Factory (use azure-data-factory), Azure Event Hubs (use azure-event-hubs), Azure Synapse Analytics (use azure-synapse-analytics), Azure Databricks (use azure-databricks).
git clone https://github.com/MicrosoftDocs/Agent-Skills
T=$(mktemp -d) && git clone --depth=1 https://github.com/MicrosoftDocs/Agent-Skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/azure-stream-analytics" ~/.claude/skills/microsoftdocs-agent-skills-azure-stream-analytics && rm -rf "$T"
skills/azure-stream-analytics/SKILL.mdAzure 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.,
), useL35-L120with the specified lines. For categories with file links (e.g.,read_file), use[security.md](security.md)on the linked reference fileread_file
IMPORTANT for Agent: If
is more than 3 months old, suggest the user pull the latest version from the repository. Ifmetadata.generated_attools are not available, suggest the user install it: Installation Guidemcp_microsoftdocs
This skill requires network access to fetch documentation content:
- Preferred: Use
with query stringmcp_microsoftdocs:microsoft_docs_fetch
. Returns Markdown.from=learn-agent-skill - Fallback: Use
with query stringfetch_webpage
. Returns Markdown.from=learn-agent-skill&accept=text/markdown
Category Index
| Category | Lines | Description |
|---|---|---|
| Troubleshooting | L37-L56 | Diagnosing and fixing Stream Analytics job issues: error codes (config/data/external/internal), input/output connection failures, query/UDF bugs, and using diagrams, metrics, and resource logs to debug. |
| Best Practices | L57-L75 | Best practices for designing, scaling, and optimizing Stream Analytics jobs: query patterns, performance tuning, reliability, geospatial, time/late events, ML, Cosmos DB, SQL, and alerting. |
| Decision Making | L76-L82 | Guidance on choosing Stream Analytics developer tools, migrating projects from Visual Studio to VS Code, and comparing Azure real-time/stream processing services for your scenario. |
| Architecture & Design Patterns | L83-L87 | Architectural patterns and best practices for designing resilient, geo-redundant Azure Stream Analytics solutions, including reference topologies and high-availability job designs. |
| Limits & Quotas | L88-L93 | Configuring and tuning Stream Analytics streaming units and clusters, including how to resize, scale performance, and understand capacity limits and resource quotas. |
| Security | L94-L113 | Securing Stream Analytics jobs: managed identities for inputs/outputs, private endpoints/VNet integration, data protection, credential rotation, and Azure Policy compliance controls. |
| Configuration | L114-L148 | Configuring Stream Analytics jobs: inputs/outputs (SQL, Cosmos DB, Event Hubs, Kafka, Power BI, Delta Lake, etc.), partitioning, autoscale, compatibility, monitoring, alerts, and error policies. |
| Integrations & Coding Patterns | L149-L168 | Patterns for integrating Stream Analytics with Kafka, Azure ML, Functions, Schema Registry, and for writing UDFs/aggregates, parsing formats, and doing ML/anomaly detection. |
| Deployment | L169-L184 | 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. |
Troubleshooting
Best Practices
Decision Making
| 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 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 |
Limits & Quotas
| Topic | URL |
|---|---|
| Resize Azure Stream Analytics clusters by streaming units | https://learn.microsoft.com/en-us/azure/stream-analytics/scale-cluster |
| Understand and tune Azure Stream Analytics streaming units | https://learn.microsoft.com/en-us/azure/stream-analytics/stream-analytics-streaming-unit-consumption |