CV0-004 Dynamic scaling Practice Question

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

• ✓

  Dynamic scaling (metric-based)

  Why this is correct

  Dynamic scaling (metric-based) triggers capacity changes from a monitored metric rather than a fixed schedule, so it directly satisfies the stem's requirement to scale on pending message count. The queue depth feeds an autoscaling rule that adds or removes instances as the backlog rises or drains, matching demand automatically.

• ✗

  Scheduled scaling

  Why it's wrong here

  Scheduled scaling acts on predefined times or dates, not on live queue depth, so a backlog of pending messages would go unnoticed until the next scheduled event. It suits predictable traffic patterns such as business-hours peaks. Reacting to message count requires a metric-driven policy instead.

• ✗

  Manual scaling

  Why it's wrong here

  Manual scaling requires an administrator to adjust capacity by hand, so pending messages would accumulate until someone intervenes. It suits rare, planned capacity changes. The scenario demands automatic adjustment driven by queue depth, which manual scaling cannot provide.

• ✗

  Static scaling

  Why it's wrong here

  Static scaling holds a fixed capacity regardless of workload, so pending queue messages would never trigger additional instances. It suits predictable, steady demand where capacity is provisioned once. The scenario requires a policy that reacts dynamically to queue depth, which static scaling cannot do.