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azure-kusto

Query and analyze Azure Data Explorer data using KQL.

6|3|Updated Feb 9, 2026
Search Tags:#time series#telemetry#log analytics#kql#kusto#azure data explorer
One-click install
npx skills add https://github.com/jongio/azd-copilot --skill azure-kusto-jongio
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: azure-kusto
Source: https://github.com/jongio/azd-copilot/tree/main/cli/src/internal/assets/ghcp4a-skills/azure-kusto
Command: npx skills add https://github.com/jongio/azd-copilot --skill azure-kusto-jongio

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill simplifies querying and analyzing vast amounts of log, telemetry, and time series data stored in Azure Data Explorer (Kusto), enabling faster insights and data-driven decisions.

Core Features & Use Cases

  • KQL Query Execution: Run complex Kusto Query Language (KQL) queries against large datasets.
  • Schema Exploration: Discover table structures and data types within Kusto databases.
  • Data Analysis: Perform aggregations, time series analysis, and anomaly detection on telemetry and logs.
  • Use Case: Analyze application logs to identify error patterns over the last 24 hours, or aggregate IoT device telemetry to spot performance trends.

Quick Start

Query my Kusto database for events in the last hour.

Frequently Asked Questions about azure-kusto

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I query Azure Data Explorer for telemetry and log analytics?▼

You can query Azure Data Explorer using Kusto Query Language (KQL) to analyze telemetry and log data. This enables executing complex queries, exploring database schemas, and performing aggregations on large datasets for faster insights.

Can I use KQL for time series analysis and anomaly detection?▼

Yes, KQL supports time series analysis and anomaly detection on IoT telemetry and application logs. You can aggregate time-stamped data to spot performance trends and identify error patterns over specific timeframes.

Does this Kusto query approach work with SQL databases or Elasticsearch?▼

No, this Kusto query approach is specifically for Azure Data Explorer (ADX) clusters. It excludes SQL databases, NoSQL queries, Elasticsearch, and AWS analytics tools, focusing entirely on KQL for ADX environments.

What's the best way to explore table structures in a Kusto database?▼

Schema exploration allows you to discover table structures and data types within Kusto databases. By querying the ADX cluster with KQL, you can inspect the underlying schema to understand your data before running complex aggregations.

How do I analyze application logs to identify error patterns over the last 24 hours?▼

You can analyze application logs by running KQL queries against your Kusto database to filter events and identify error patterns over the last 24 hours. This aggregates log data to pinpoint specific issues and anomalies.

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