Jeff’s Note #
Unlike generic exam dumps, ADH analyzes this scenario through the lens of a Real-World Lead Developer.
For AWS DVA-C02 candidates, the confusion often lies in the correct use of CloudWatch Evidently overrides versus experiments for feature flag management. In production, this is about knowing exactly how to target users or traffic with overrides without interfering with experiment traffic split logic. Let’s drill down.
The Certification Drill (Simulated Question) #
Scenario #
At StellarSoft, a lead developer implemented an A/B test of a new application feature using Amazon CloudWatch Evidently. The project contains two variations of the feature, named Variation ‘A’ and Variation ‘B’. The developer now wants to modify the setup so that only Variation ‘A’ is served to any user who accesses the application’s API endpoint, effectively disabling Variation ‘B’ from appearing.
The Requirement #
Ensure Variation ‘A’ is the exclusive variation served when the application endpoint is accessed, without running an experiment or traffic split.
The Options #
- A) Add an override on the feature. Set the override identifier to the developer’s user ID and assign Variation ‘A’ as the variation.
- B) Add an override on the feature. Set the override identifier to Variation ‘A’ and assign the variation weight to 100%.
- C) Add an experiment to the project. Set the experiment identifier to Variation ‘B’ and assign its traffic split to 0%.
- D) Add an experiment to the project. Set the experiment identifier to the AWS account ID and assign Variation ‘A’ as the variation.
Google adsense #
leave a comment:
Correct Answer #
A.
Quick Insight: The Developer Imperative #
CloudWatch Evidently overrides allow precise targeting at the user or entity level, forcing a specific variation regardless of any existing experiment or traffic allocation. This is the key when you want to exclusively serve a variation for a particular user or group (or yourself as a developer during testing) without modifying or disabling the experiment.
Experiments and traffic splits operate at the aggregate traffic level and do not offer per-identifier deterministic overrides.
Content Locked: The Expert Analysis #
You’ve identified the answer. But do you know the implementation details that separate a Junior from a Senior?
The Expert’s Analysis #
Correct Answer #
Option A
The Winning Logic #
When you want to specifically target only Variation ‘A’ for certain users (or even just yourself as the developer) without affecting the experiment or the global traffic distribution, CloudWatch Evidently’s feature overrides are the tool to use. You configure an override on the feature, identify the user (or entity) by a user ID, and assign Variation ‘A’. This causes any request matching that identifier to always see Variation ‘A’, bypassing traffic splits and experiments.
The Trap (Distractor Analysis) #
- Why not B? Setting the override identifier to the variation name (Variation ‘A’) is incorrect—overrides expect a user or entity ID, not a variation identifier. Also, “100% variation” does not apply in overrides; that applies to traffic splits in experiments.
- Why not C? Changing traffic split to 0% for Variation ‘B’ within an experiment does not guarantee Variation ‘A’ exclusivity for all users, as the experiment still controls routing and may serve Variation ‘B’ to some users due to allocation.
- Why not D? Assigning the experiment identifier to the AWS account ID is a conceptually incorrect method. Experiments require specific experiment IDs and controlled traffic splits, and this does not guarantee exclusive serving of Variation ‘A’.
The Technical Blueprint #
# Example AWS CLI command to add a feature override targeting a specific user ID to Variation 'A'
aws evidently put-feature-override \
--project-name stellarsoft-project \
--feature-name new-feature-flag \
--entity-id user-12345 \
--variation new-feature-flag-variation-A
The Comparative Analysis #
| Option | API Complexity | Behavior | Use Case |
|---|---|---|---|
| A | Simple override API call | Per-entity override of variation | Target specific user(s) with Variation ‘A’ |
| B | Misused override parameter | Invalid override identifier | Conceptually incorrect |
| C | Experiment traffic control | Traffic split=0% for Variation ‘B’ but experiment still controls routing | Attempts to disable variation ‘B’ globally but not guaranteed for exclusivity |
| D | Incorrect use of experiment ID | Invalid experiment identifier | Invalid API usage and logic |
Real-World Application (Practitioner Insight) #
Exam Rule #
“For the exam, always pick AWS CloudWatch Evidently overrides when you want to force a specific variation for a known user/entity.”
Real World #
“In real product development, overrides are our go-to for isolated testing or QA, allowing developers or early testers to see the feature as intended without affecting overall user traffic or experiments.”
(CTA) Stop Guessing, Start Mastering #
Disclaimer
This is a study note based on simulated scenarios for the AWS DVA-C02 exam.