Run KQL queries and explore schemas in Azure Data Explorer.
npx skills add https://github.com/anevjes/agenticinfraops --skill azure-kusto-anevjes
Please help me install this Agent Skill. Skill: azure-kusto Source: https://github.com/anevjes/agenticinfraops/tree/main/.github/skills/azure-kusto Command: npx skills add https://github.com/anevjes/agenticinfraops --skill azure-kusto-anevjes
This Skill enables efficient querying and management of Azure Data Explorer (Kusto) resources, allowing users to perform fast, scalable data analysis on log, telemetry, and time series data, simplifying complex data exploration tasks.
Ask to list available clusters or run a basic Kusto query on your database to begin analyzing telemetry data immediately.
High-intent search queries and answers about installing and using this skill.
You can execute KQL queries in Azure Data Explorer by providing cluster and database parameters to retrieve telemetry data. This enables fast aggregations across millions of log records to extract operational insights.
Schema exploration in Azure Data Explorer uses built-in commands to map table structures and data models. This identifies available columns and types before you query telemetry or time series data.
Yes, you need existing Azure Data Explorer clusters and databases with proper access credentials. The tool connects to your live Kusto environment to list resources and execute queries using your configured parameters.
Yes, you can list and manage Kusto clusters and databases to oversee your environment. This resource management functionality verifies available resources before executing time series or log analytics queries.
Azure Data Explorer handles time series and log analytics by utilizing KQL to perform scalable data analysis. It streamlines complex exploration tasks across massive datasets using optimized retrieval parameters.
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