vinay_ba
New Contributor II

‎05-19-2026 11:09 PM

Thanks for u detailed answer on the dashboard validation testing.

 

Hi,
We also need to perform performance testing and concurrency testing of AI/BI (Lakeview) dashboards at the browser level — measuring actual page load times, time-to-interactive, and how the dashboard behaves under concurrent user load.
 
What we want to measure:
  1. Dashboard page load time (navigation start → all widgets rendered)
  2. Time to First Contentful Paint (FCP) and Largest Contentful Paint (LCP)
  3. Number and duration of backend SQL queries triggered during dashboard load
  4. How response times degrade when 10, 25, 50 users open the same dashboard simultaneously
  5. SQL Warehouse query queuing behavior under concurrent dashboard load
Our planned approach:
  1. Use Playwright (headless Chromium) to open the dashboard URL
  2. Capture performance.timing, paint entries, and network request durations
  3. Simulate concurrent users by launching multiple browser contexts in parallel
  4. Wait for networkidle state as a proxy for "dashboard fully loaded"
Our questions:
 
1. Authentication What is the recommended way to authenticate programmatically for browser-based dashboard access? Can we use PAT tokens via cookie/header injection, or is there a service account login flow that avoids interactive SSO?
 
2. Caching behavior When multiple users open the same dashboard simultaneously, does Lakeview leverage SQL Warehouse result cache? Or does each user session trigger independent query executions?
 
3. Network idle as completion signal Is networkidle (no network requests for ~500ms) a reliable indicator that all dashboard widgets have finished loading? Or are there lazy-loaded widgets or progressive rendering beyond that point?
 
4. Published vs draft dashboard For performance testing, should we test the published dashboard URL (which may have different caching/optimization behavior) vs the draft editor view?
 
5. Warehouse metrics correlation Is there a way to correlate dashboard-triggered queries in Query History API (GET /api/2.0/sql/history/queries) with a specific dashboard session? For example, does Lakeview tag queries with a statement_type or source field?
 
6. Concurrency limits Are there known limits on concurrent sessions viewing the same AI/BI dashboard (for example: warehouse concurrency caps, connection pooling, or API rate limits)?
 
Environment:
  • Databricks on AWS
  • AI/BI Dashboard (Lakeview), published
  • SQL Warehouse (serverless)
  • Playwright (Python) for browser automation
  • 10–50 simulated concurrent users
Thanks in advance!

 

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