Do Trial Runs

Learning Objectives

After completing this unit, you’ll be able to:

Conduct trial runs to validate your test setup.
Explain the importance of trial runs in identifying and resolving issues.

It’s time to explore the importance of doing trial runs before conducting full-scale tests. Trial runs are scale tests that you execute with a smaller number of users. They help you validate your test setup, identify potential issues, and ensure that your tests are accurate and reliable.

Plan your ramp-up. Be intentional and take your time. Start small. A controlled ramp-up (and ramp-down) is crucial for uncovering issues without overwhelming your system from the start.

Sample ramp plan for 5,000 users:

0–15 mins: Ramp from 0 to 1,000 users → hold for stability
30–45 mins: Ramp to 2,500 users → hold again
60–90 mins: Ramp to 5,000 users
90–150 mins: Hold steady at 5,000 users (collect peak metrics)
150–180 mins: Gradually ramp down to zero

Why Trial Runs Are Important

Validation: Trial runs help you validate your test setup, ensuring that all components, including Agentforce, are functioning correctly.
Issue identification: By running trial runs, you can identify and resolve issues before they impact your full-scale tests.
Confidence: Conducting trial runs builds confidence in your test setup, ensuring that you are prepared for the full-scale test.

Steps to Conduct Trial Runs

Testing Step	Description
Set Up Your Test Environment	Refresh sandbox: Ensure that your test environment is up-to-date by refreshing a full copy sandbox from the Production org. Configure sub-systems: Set up and configure the test sub-systems to ensure they are ready for the trial run.
Define Test Scenarios	Key workflows: Identify the key user workflows that you want to test. Create detailed test scenarios that cover these workflows. Data volume: Determine the volume of data needed for the trial run. Start with a smaller volume to ensure that the test runs smoothly.
Run the Trial Run	Start with low-user baseline runs (20–30 users) to validate scripts and compare against production peaks using Scale Test’s Trial Accuracy Checker. Align with SLAs: Define measurable targets (for example, Page load ≤ 2s or Error rate ≤ 0.5%). This establishes clear pass/fail criteria. Execute test scenarios: Run the test scenarios in your test environment, monitoring the performance and identifying any issues. Monitor performance: Use monitoring tools to track performance metrics, such as response time, throughput, and error rates.
Analyze Results	Identify issues: Analyze the results of the trial run to identify any performance issues or configuration problems. Resolve issues: Address any issues identified during the trial run, making necessary adjustments to your test setup.
Iterate and Improve	Refine test scenarios: Based on the results of the trial run, refine your test scenarios to improve their accuracy and effectiveness. Repeat trial runs: Conduct additional trial runs to ensure that the issues have been resolved and that your test setup is ready for the full-scale test.

Use Case: Route Insurance Cases Based on Criteria

You run a trial with 2,000 users on an insurance application that routes cases through Agentforce based on policy type. Use Playwright logs and screenshots to debug a failed Live Agent handoff. Trial mode allows you to iterate safely before booking the full-scale test. You adjust the retry logic for Named Credential API calls that were timing out under partial load.

Congratulations, you’ve taken all the necessary steps to now book and review an actual Scale Test!

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Do Trial Runs

Learning Objectives

Why Trial Runs Are Important

Steps to Conduct Trial Runs

Use Case: Route Insurance Cases Based on Criteria