Google ACE Practice Question: Which TWO practices help ensure the reliability…

Answer analysis

Option-by-option breakdown

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

• ✗

  Deploy functions in a single region to minimize latency.

  Why it's wrong here

  Deploying Cloud Functions in a single region creates an availability single point of failure: if that region experiences an outage, the function becomes completely unavailable, undermining reliability. While a single region can reduce cross-region latency, reliability demands a multi-region deployment with global load balancing or traffic splitting to decouple availability from regional failures. The latency benefit is typically outweighed by the risk of a total service outage.

• ✗

  Configure a VPC connector for all functions.

  Why it's wrong here

  A VPC connector is designed solely to give Cloud Functions private access to resources inside a Virtual Private Cloud network, such as databases or internal APIs, not to improve reliability. It does not add redundancy, automatic retries, or failover capabilities, and it does not address the failure modes of the function itself. Enabling a VPC connector for every function can even introduce unexpected latency and deployment complexity without any availability benefit.

• ✗

  Set maximum instances to 1 to avoid resource contention.

  Why it's wrong here

  Setting maximum instances to 1 artificially caps concurrency at a single running instance, so under load the platform scales only by throttling or queueing invocations, increasing latency and ultimately failing requests during traffic spikes. It also makes the application vulnerable to a single-instance crash, leaving no healthy replica to serve traffic. Reliability requires horizontal scaling and redundant instances, not restricting concurrency to avoid contention.

• ✓

  Use Cloud Tasks to decouple function invocations.

  Why this is correct

  Cloud Tasks decouples the direct invocation path by enqueuing messages that are asynchronously delivered to your function, providing built-in retries with configurable deadlines, exponential backoff, and rate limiting that prevent overload and handle transient failures. This decoupling means the caller's success is not dependent on the function being immediately available, and tasks are queued persistently so no request is lost if the function is temporarily unavailable. It also smooths burst traffic, which is a core reliability practice.

• ✓

  Implement retry policies for background functions.

  Why this is correct

  For background functions (triggered by Cloud Storage, Pub/Sub, or Eventarc), implementing retry policies makes the platform automatically redeliver events when your function returns an error or times out, which is essential for handling transient faults like database connection hiccups or third-party API delays. Without a retry policy, a failed background invocation is immediately dropped, causing data loss and broken workflows. Retries with exponential backoff increase the probability of eventual successful processing, directly enhancing reliability.

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