Monitoring AI Agent Skills

Build anomaly detection applications with Azure AI Anomaly Detector SDK for Java. Use when implementing univariate/multivariate anomaly detection, time-series analysis, or AI-powered monitoring.

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Build production-ready monitoring, logging, and tracing systems.

You are an SLO (Service Level Objective) expert specializing in implementing reliability standards and error budget-based practices. Design SLO frameworks, define SLIs, and build monitoring that balances reliability with delivery velocity.

You are an error tracking and observability expert specializing in implementing comprehensive error monitoring solutions. Set up error tracking systems, configure alerts, implement structured logging, and ensure teams can quickly identify and resolve production issues.

MCP-Dandan is an integrated monitoring service that observes MCP (Model Context Protocol) communications and detects security threats in real time. It features a modern desktop UI built with Electron for easy monitoring and management. Currently, MCP-Dandan is listed in well-known MCP-related open-source collections and can be found in the following repositories: - Awesome MCP Servers – Security -

Design effective KPI dashboards with metrics selection, visualization best practices, and real-time monitoring patterns. Use when building business dashboards, selecting metrics, or designing data visualization layouts.