Monitor and Maintain a Tableau Deployment41% of the exam

Load testing strategy, test environments and TabJolt

Plan Tableau Server load testing: when to test, how to build a production-identical test environment, which tool (TabJolt, Replayer, Scout) fits, how to write a test plan, and how to turn CPU, error-rate and process data into scaling and capacity decisions.

Official exam objective
3.2 Perform load testing: 3.2.1 Recommend a load testing strategy; 3.2.2 Configure and use a load testing tool such as TabJolt; 3.2.3 Configure a test environment; 3.2.4 Create appropriate test plans; 3.2.5 Interpret load test results and determine the appropriate action.

~6 min read · 21 practice questions

What the exam expects

  • Recommend a load testing strategy: cadence, triggers and what each test must prove.
  • Configure and use a load testing tool such as TabJolt, and tell it apart from Replayer and Scout.
  • Configure a test environment that matches production in hardware, topology, data, authentication and network path.
  • Create test plans with representative content, realistic usage, peak modelling, duration and think time.
  • Interpret load test results (CPU, error rate, per-process counters) and choose the action: optimize content, keep testing, scale, or retune processes.

Key terms: TabJolt (Tableau-created point-and-run load and performance testing utility for Tableau Server); Replayer (replays log-based real user traffic against another server or configuration); Scout (captures performance metrics across workbooks); think time (pause between virtual user actions); breaking point (the user, request and data volume at which the server fails).

Key facts

Cadence
Detail
Two to four times a year, with upgrades and expansions
Environment
Detail
Identical hardware, topology and data volume
Restore gap
Detail
Configuration and customizations replicated by hand
Load target
Detail
75-85% CPU, under 2% errors
Minimum run
Detail
At least ten minutes, with think time
Scaling trigger
Detail
Threshold met and sustained on default processes
Scaling shape
Detail
Nearly linear when adding nodes
Slow-view rule
Detail
Multiple views over 10 seconds with many sessions
PerfMon sample interval
Detail
30 seconds
Capacity plan inputs
Detail
Performance data, onboarding schedules, load test results
Linux recommendation
Detail
Peak above 1,000 VizQL sessions per hour
Sources for this section (6)
  • How does Tableau Server throughput grow as nodes are added under rising user load?
  • When your test server must run the same, older version as production, where do you get its setup program?
  • Which Replayer capability helps troubleshoot errors one user saw?
  • Why ask users who helped test an upgrade to help announce it?

The questions are free to read. Answers with their sources and self-grading are included with the pack.

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