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AnanyaDBJ
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load-testing

Load test Databricks Apps to determine maximum QPS and generate interactive dashboards.

6|10|Updated Mar 23, 2026
Search Tags:#benchmarking#load testing#performance testing#Databricks#QPS
One-click install
npx skills add https://github.com/AnanyaDBJ/databricks-ai-workshops --skill load-testing-ananyadbj
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: load-testing
Source: https://github.com/AnanyaDBJ/databricks-ai-workshops/tree/main/medium/.claude/skills/load-testing
Command: npx skills add https://github.com/AnanyaDBJ/databricks-ai-workshops --skill load-testing-ananyadbj

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires locust, and includes scripts (resource) components.

What problem does it solve?

This Skill allows you to load test your Databricks Apps to determine their maximum queries per second (QPS) and overall performance.

Core Features & Use Cases

  • Load Testing: Simulate high traffic to your Databricks App to find its maximum QPS and identify performance bottlenecks.
  • Customization: Configure test parameters such as app URLs, compute sizes, worker counts, and OAuth credentials.
  • Results Dashboard: Generate an interactive HTML dashboard to visualize QPS, latency, and other performance metrics.
  • Use Case: Before deploying a new Databricks App, use this Skill to ensure it can handle the expected load and perform optimally.

Quick Start

Use the load-testing skill to benchmark the performance of your Databricks App 'my-app' with medium compute and 4 workers.

Frequently Asked Questions about load-testing

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

FAQPage Schema
How do I benchmark my Databricks App to find its maximum QPS?▼

To benchmark Databricks Apps for maximum QPS, you can simulate high traffic using this Skill. It configures test parameters like app URLs, compute sizes, and worker counts to identify performance bottlenecks and determine overall throughput.

What is performance load testing for Databricks Apps and how does it work?▼

Performance load testing simulates high traffic against your Databricks App to measure its maximum QPS and latency. By generating requests with Locust, it identifies performance bottlenecks before deployment, visualizing results in an interactive HTML dashboard.

Do I need Locust and M2M OAuth to run load tests on Databricks Apps?▼

Yes, Locust is required as the dependency for load testing, and M2M OAuth is necessary for authentication. These components allow the simulation of high traffic to accurately measure your Databricks App's QPS and overall performance metrics.

Can I customize compute sizes and worker counts when load testing Databricks Apps?▼

Yes, you can customize load testing parameters including app URLs, compute sizes, worker counts, and OAuth credentials. Configuring these variables allows you to accurately simulate expected traffic and find the maximum QPS for your specific deployment.

What's the best way to visualize QPS and latency results from Databricks load testing?▼

The best way to visualize QPS and latency results is by generating an interactive HTML dashboard. This Skill creates a dashboard after load testing your Databricks App, allowing you to review performance metrics and identify bottlenecks visually.

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