Write precise KQL queries for Azure Data Explorer and related services.
npx skills add https://github.com/rrbanda/skills --skill kql-rrbanda
Please help me install this Agent Skill. Skill: kql Source: https://github.com/rrbanda/skills/tree/main/skills/devops/kql Command: npx skills add https://github.com/rrbanda/skills --skill kql-rrbanda
Writing correct and efficient KQL queries for Azure Data Explorer and related services can be error-prone and slow. This skill guides users through syntax, patterns, and best practices to accelerate data analysis and reduce mistakes.
Generate a ready-to-run KQL query that filters StormEvents by StartTime and counts events by EventType.
High-intent search queries and answers about installing and using this skill.
To write efficient KQL queries for Azure Data Explorer, apply pattern-focused guidance on filtering, joins, and windowing. Using precise syntax and performance considerations reduces errors and accelerates data analysis.
The best way to troubleshoot logs using KQL in Log Analytics is to use specific query patterns for filtering and aggregating data. This approach quickly isolates errors and identifies root causes within your telemetry data.
Yes, you can perform time-series analysis and graph-style queries with KQL. The query language supports windowing functions and graph-like patterns, enabling complex temporal investigations and relationship mapping across your data.
Yes, this KQL guidance applies to Microsoft Fabric Data Explorer. The syntax mastery and query patterns cover Azure Data Explorer, Log Analytics, and Fabric Data Explorer, ensuring broad compatibility across related services.
KQL queries often fail when joining multiple tables in Azure Data Explorer due to syntax errors or mismatched join keys. Applying robust error handling and correct pattern-focused guidance resolves these structural issues.
To generate a ready-to-run KQL query to count events by type, filter your dataset by a specific column like StartTime, then use the summarize operator to aggregate counts grouped by EventType.
jgezelscorpExecute KQL queries against Azure Data Explorer for log analytics.
ntaksh42Analyze application logs to detect errors, patterns, and anomalies.
anishi1222Execute KQL queries and manage clusters in Azure Data Explorer.
silvainfmRun SQL analytics directly on CSV, Parquet, and JSON files and Pandas or Polars DataFrames.
