From azure
Expert knowledge for Azure AI Anomaly Detector development including troubleshooting, best practices, architecture & design patterns, limits & quotas, configuration, and deployment. Use when using univariate/multivariate APIs, Docker/IoT Edge containers, predictive maintenance flows, or regional limits, and other Azure AI Anomaly Detector related development tasks. Not for Azure AI Metrics Advisor (use azure-metrics-advisor), Azure Monitor (use azure-monitor), Azure Machine Learning (use azure-machine-learning).
npx claudepluginhub atc-net/atc-agentic-toolkit --plugin azureThis skill uses the workspace's default tool permissions.
This skill provides expert guidance for Azure Anomaly Detector. Covers troubleshooting, best practices, architecture & design patterns, limits & quotas, configuration, and deployment. It combines local quick-reference content with remote documentation fetching capabilities.
Builds anomaly detection applications using Azure AI Anomaly Detector Java SDK for univariate/multivariate detection, time-series analysis, and AI monitoring.
Implements AI-powered anomaly detection for operational metrics using Isolation Forest, Prophet, LSTM time series analysis, alert correlation, and root cause analysis to reduce alert fatigue.
Builds univariate/multivariate anomaly detection for time-series data using Azure AI Anomaly Detector Java SDK.
Share bugs, ideas, or general feedback.
This skill provides expert guidance for Azure Anomaly Detector. Covers troubleshooting, best practices, architecture & design patterns, limits & quotas, configuration, and deployment. It combines local quick-reference content with remote documentation fetching capabilities.
IMPORTANT for Agent: This file may be large. Use the Category Index below to locate relevant sections, then use
read_filewith specific line ranges (e.g.,L136-L144) to read the sections needed for the user's question This skill requires network access to fetch documentation content. Usemcp_microsoftdocs:microsoft_docs_fetchto retrieve full articles.
WebFetch tool if the Microsoft Learn MCP server is not available.| Category | Lines | Description |
|---|---|---|
| Troubleshooting | L28-L32 | Diagnosing and fixing Anomaly Detector issues, including multivariate API error codes, model training/detection failures, data format problems, and common service or configuration errors. |
| Best Practices | L34-L38 | Guidance on preparing data, tuning parameters, interpreting results, and designing workflows for effective use of univariate and multivariate Azure Anomaly Detector APIs. |
| Architecture & Design Patterns | L40-L43 | Designing predictive maintenance solutions using Multivariate Anomaly Detector, including data preparation, model setup, and architecture patterns for monitoring complex equipment. |
| Limits & Quotas | L45-L49 | Details on Anomaly Detector regional endpoints, usage constraints, request/throughput limits, quotas, and how these caps affect model training and inference. |
| Configuration | L51-L54 | How to configure and tune Anomaly Detector Docker containers, including environment variables, resource limits, logging, networking, and runtime behavior settings. |
| Deployment | L56-L61 | How to package and run Anomaly Detector in containers: Docker setup, Azure Container Instances deployment, and IoT Edge module deployment and configuration. |
| Topic | URL |
|---|---|
| Troubleshoot Multivariate Anomaly Detector error codes | https://learn.microsoft.com/en-us/azure/ai-services/anomaly-detector/concepts/troubleshoot |
| Resolve common Azure Anomaly Detector issues | https://learn.microsoft.com/en-us/azure/ai-services/anomaly-detector/faq |
| Topic | URL |
|---|---|
| Apply univariate Anomaly Detector API best practices | https://learn.microsoft.com/en-us/azure/ai-services/anomaly-detector/concepts/anomaly-detection-best-practices |
| Use multivariate Anomaly Detector API effectively | https://learn.microsoft.com/en-us/azure/ai-services/anomaly-detector/concepts/best-practices-multivariate |
| Topic | URL |
|---|---|
| Design predictive maintenance with Multivariate Anomaly Detector | https://learn.microsoft.com/en-us/azure/ai-services/anomaly-detector/concepts/multivariate-architecture |
| Topic | URL |
|---|---|
| Use Anomaly Detector regional endpoints and constraints | https://learn.microsoft.com/en-us/azure/ai-services/anomaly-detector/regions |
| Review Anomaly Detector service limits and quotas | https://learn.microsoft.com/en-us/azure/ai-services/anomaly-detector/service-limits |
| Topic | URL |
|---|---|
| Configure Anomaly Detector container runtime settings | https://learn.microsoft.com/en-us/azure/ai-services/anomaly-detector/anomaly-detector-container-configuration |
| Topic | URL |
|---|---|
| Deploy and run Anomaly Detector Docker containers | https://learn.microsoft.com/en-us/azure/ai-services/anomaly-detector/anomaly-detector-container-howto |
| Run Anomaly Detector in Azure Container Instances | https://learn.microsoft.com/en-us/azure/ai-services/anomaly-detector/how-to/deploy-anomaly-detection-on-container-instances |
| Deploy Anomaly Detector module to Azure IoT Edge | https://learn.microsoft.com/en-us/azure/ai-services/anomaly-detector/how-to/deploy-anomaly-detection-on-iot-edge |