azure-kusto

Run KQL queries for log analytics in Azure Data Explorer by executing the azure-kusto skill with your subscription, cluster, database, and query string to analyze massive datasets. It supports schema discovery and telemetry analysis.

Yes, you can perform time series analysis and anomaly detection on telemetry data using Kusto Query Language. The skill executes KQL aggregations and machine learning operations directly on Azure Data Explorer clusters.

To query a Kusto database, you need Azure authentication and access to Azure Data Explorer resources, specifically a valid subscription, an active cluster, and a target database to execute KQL queries.

Discover tables, columns, and data types in an Azure Data Explorer database by using the skill's schema exploration feature. It executes KQL commands to map the structure of your Kusto databases.

The best way to manage Azure Data Explorer clusters and databases for log analytics is by using KQL resource management commands. The skill allows you to list and manage clusters and databases before executing queries.

Yes, this approach works for analyzing massive telemetry datasets without moving data. The skill operates directly on Azure Data Explorer clusters, executing KQL queries natively for fast aggregations and time series analysis.