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eventhouse-authoring-cli

Execute KQL management commands to create and manage Fabric Eventhouse objects.

Updated Jun 1, 2026
Search Tags:#ingestion#fabric#azure cli#kql#kusto#eventhouse#schema deployment
One-click install
npx skills add https://github.com/weiflycc-cmd/skills-for-fabric --skill eventhouse-authoring-cli-weiflycc-cmd
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: eventhouse-authoring-cli
Source: https://github.com/weiflycc-cmd/skills-for-fabric/tree/main/plugins/fabric-authoring/skills/eventhouse-authoring-cli
Command: npx skills add https://github.com/weiflycc-cmd/skills-for-fabric --skill eventhouse-authoring-cli-weiflycc-cmd

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Manually managing Fabric Eventhouse and KQL Database objects (tables, policies, ingestion, materialized views) is error-prone and time-consuming, especially for repetitive tasks like schema deployments and bulk data ingestion. This skill automates these workflows using standardized, idempotent CLI commands.

Core Features & Use Cases

  • KQL Object Management: Create, alter, and drop KQL tables, stored functions, and materialized views for Fabric Eventhouse and KQL Databases.
  • Data Ingestion: Handle inline, storage, OneLake, and streaming ingestion with configurable data mappings for CSV and JSON sources.
  • Policy Configuration: Set retention, caching, and streaming ingestion policies to optimize data lifecycle and query performance.
  • Schema Deployment: Idempotent, script-based schema deployment for CI/CD workflows, with support for exporting current schema for version control. Use case example: A data engineer can use this skill to deploy a complete KQL schema for an Eventhouse, configure retention and caching policies, and ingest sample data in minutes instead of manually running each individual command.

Quick Start

Use the eventhouse-authoring-cli skill to create a new KQL table named SensorData with Timestamp, DeviceId, and Temperature columns, then set a 90-day retention policy for it.

Frequently Asked Questions about eventhouse-authoring-cli

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

FAQPage Schema
How do I automate Fabric Eventhouse KQL schema deployment for CI/CD?▼

Automate Fabric Eventhouse schema deployment by executing idempotent KQL management commands via the Azure CLI, creating or altering tables, functions, and materialized views with consistent results across pipeline runs.

Can I use Azure CLI to manage KQL Database tables and policies?▼

Yes, you can use Azure CLI to manage KQL Database tables and policies by executing management commands using the az rest pattern with the correct Kusto token audience for authorization.

What is the best way to ingest JSON data into a Fabric Eventhouse?▼

Ingest JSON data into a Fabric Eventhouse using inline, storage, OneLake, or streaming ingestion methods, applying configurable data mappings to ensure the source format aligns with your KQL table schema.

Do I need specific permissions to run Kusto management commands on Fabric?▼

Yes, you need appropriate Kusto and Fabric API permissions configured within your Azure CLI environment to successfully execute KQL management commands for Eventhouse authoring tasks.

How do I configure retention and caching policies for KQL tables?▼

Configure retention and caching policies for KQL tables by executing specific KQL management commands through the CLI, optimizing data lifecycle and query performance for your Fabric Eventhouse.

When should I use streaming ingestion instead of storage-based ingestion for Kusto?▼

Use streaming ingestion for low-latency real-time data loading into Kusto, whereas storage-based ingestion is better suited for bulk historical data loading from CSV or JSON sources.

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