azure-kusto

The Azure Kusto skill provides an interface to query and analyze data in Azure Data Explorer (ADX) using the Kusto Query Language (KQL). It enables users to interact with large-scale log, telemetry, and time series datasets efficiently, solving the problem of extracting actionable insights from massive amounts of structured and semi-structured data. By leveraging the high-performance capabilities of ADX, this skill facilitates sub-second query execution on billions of records, making it ideal for real-time monitoring, analytics, and anomaly detection.

This skill offers a range of features including query execution, schema exploration, resource management, and advanced analytics. Users can run KQL queries to retrieve, filter, and aggregate data, explore table structures and column types for query planning, list clusters and databases for resource management, and perform time series analysis or anomaly detection. Core workflows involve discovering available resources, exploring schema to understand data models, executing queries, and analyzing results for reporting and insights. Predefined query patterns support tasks such as basic data retrieval, aggregation analysis, time series analytics, and cross-table joins, ensuring consistent and efficient operations.

Target users include data engineers, analysts, and IT professionals working with telemetry, IoT, security logs, and performance monitoring. Common use cases include monitoring application performance, analyzing security events, performing root cause analysis, and visualizing trends in time series data. Organizations leveraging ADX for large-scale log analytics and telemetry can use this skill to streamline data exploration and reporting workflows, making it suitable for operational monitoring, anomaly detection, and data-driven decision-making.