Ramping a Microservices Rollout Gradually with a Progressive Exposure Canary Strategy
You plan to deploy a solution that will include multiple microservices. You need to recommend a deployment strategy for the microservices. The solution must meet the following requirements: • Enable testing and monitoring of changes during a gradual rollout. • Control the number of users that will receive new code releases. Which strategy should you recommend?
Community Votes
100% of anonymous learners picked answer A. Votes are pick records left by other test-takers — they are not the verified answer.
Community Insight
Progressive exposure, also called canary releasing, serves the new version to an increasing percentage of users over time, which enables monitoring at each step and directly controls how many users are on the new code.
A solution spans multiple microservices and the deployment strategy must support testing and monitoring during a gradual rollout while controlling how many users receive the new code. The requirement is about releasing incrementally to a growing population rather than switching all users at once.
Choosing blue/green, which does support testing and rollback but switches between two full environments at once rather than gradually exposing a growing share of users, so it cannot limit the rollout to a controlled number of users.
Community Discussion (3 comments)
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Expert Analysis
Why the Answer Is Correct
Both requirements describe a gradual, staged rollout. Progressive exposure, commonly called canary releasing, deploys the new version to a small initial subset of users and then increases that percentage over time, so the team can test and monitor the release at each step and abort if problems appear. Because the population receiving the new code is a percentage that is deliberately raised, the strategy directly satisfies the requirement to control how many users receive new releases. The vote was unanimous at 100 for A. Christian_garcia_martin identified the strategy by name and stated both halves of the reasoning, explaining that it slowly rolls out changes to a small subset of users before rolling out to the entire infrastructure and that this both enables monitoring and testing before full deployment and provides control over the number of users receiving the release.Why the Other Options Are Wrong
Blue/green deployment (D) runs two complete environments side by side and switches traffic between them, so all users move to the new code at once rather than gradually. It offers clean testing and rollback but has no mechanism for exposing the release to a controlled growing share of users, which is the requirement it fails. A feature toggle (C) does control which users see a feature and is genuinely useful for hiding incomplete work, but it is a runtime switch inside a single deployment rather than a rollout strategy, and the question asks for a deployment strategy that supports testing and monitoring during a gradual rollout. An A/B strategy (B) runs two variants side by side to measure which performs better against a live hypothesis, which is an experimentation design requiring hypothesis, sample size, and analysis, none of which the stated requirements call for.Community Comment Notes
The community was unanimous at 100 for A, and Christian_garcia_martin's comment supplied the full reasoning in one place, naming progressive exposure as canary releasing and tying it to both the gradual monitoring behavior and the control over user counts. There is no dissent in the thread. The distinction that matters for future questions on this topic is that blue/green solves promotion and rollback while progressive exposure solves gradual rollout and blast-radius control, and this question is deliberately built to select the latter.Official Reference
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