AceStack AI

Coding (Platform)

Cloud-native full-stack: Evaluate feature flags for deployment control feature rollout

A distributed workflow needs a localized repair without weakening observability or rollback safety. The affected area is deployment control.

Repair the deployment control feature rollout implementation so it evaluates segment constraints and stable rollout buckets.

Evidence

  • Affected surface: Cloud-native full-stack / deployment control.
  • Observed failure family: evaluate feature flags.
  • Scope policy: authorized must equal true.

What this task practices

This coding (platform) exercise trains the same sequence expected in an interview: understand the prompt, make assumptions explicit, produce a concrete answer, and explain the decisions behind it. The task is marked medium difficulty. The private workspace adds the tools required by this round, such as recording, code execution, diagrams, evidence panels, or structured notes. It also preserves the attempt so later feedback can be compared with previous work. Evaluation is based on task-specific criteria and the candidate seniority selected in the preparation path. Public pages never expose the reference solution, hidden tests, evaluator instructions, or another candidate’s work.

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