SF-PD2 Testing, Debugging, and Deployment Practice Question
A developer needs to measure the performance of a specific Apex code block in production. Which tool should be used to analyze CPU time without impacting end-user experience?
⚠ Common exam trap
Candidates might suggest running anonymous blocks or heavy developer console monitoring in production, which can degrade performance and impact users.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Debug logs with Apex Profiling categories set to 'Finest'.
The Apex Debug log with profiling enabled is the appropriate tool. By analyzing the 'CPU Time' and 'Total Time' entries, the developer can measure the performance cost of specific method calls. This approach is minimally invasive and can be targeted to specific users, ensuring that performance metrics are gathered in the production environment without causing system-wide impact or performance degradation for the general user base.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Test.startTest() and Test.stopTest() for profiling.
Why it's wrong here
These are only available in a testing context, not in production. Using them in production code would lead to compilation errors or unexpected behavior. Performance measurement in production must be done using execution logs or specialized performance monitoring tools, never by relying on unit testing primitives.
- ✓
Debug logs with Apex Profiling categories set to 'Finest'.
Why this is correct
Setting the Apex Profiling category to 'Finest' provides granular data on CPU time per method. This is the intended way to profile code performance on the Salesforce platform. It provides the necessary visibility into the execution cost of specific logic blocks, allowing for performance tuning without requiring any production code changes.
- ✗
System.debug() statements added throughout the code.
Why it's wrong here
Adding System.debug() is inefficient and provides timing data that is inaccurate. It is also a bad practice to litter production code with these statements. It does not provide the structured CPU time data that the platform's native profiling tools provide, making it a poor choice for serious performance analysis.
- ✗
The Salesforce Optimizer tool.
Why it's wrong here
The Optimizer tool is designed for identifying org-wide configuration issues, not for profiling specific lines of Apex code. It does not provide the method-level performance timing data required to identify a bottleneck within a specific custom Apex method or logic block.
About these practice questions
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Salesforce exam blueprint
This SF-PD2 practice question is part of Courseiva's free Salesforce certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the SF-PD2 exam.