Google PCA Practice Question: Managing Implementation and Ensuring Solution and Operations Reliability
An e-commerce company runs its order-processing service on Cloud Run. During flash sales, the service experiences sudden traffic spikes, and the operations team observes that new instances take too long to start, causing elevated latency and some request failures. The service has a large container image and initializes database connection pools at startup. Which configuration change should the team make to reduce cold-start impact while controlling cost?
⚠ Common exam trap
The trap here is trying to solve startup latency by increasing maximum instances or concurrency settings, which affect scaling capacity rather than the time a new instance needs to become ready.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Set the minimum number of instances to a value greater than zero and enable CPU always allocated for the service.
Cold starts occur when Cloud Run must start a new instance, and the large image plus startup initialization makes this slow. Keeping a minimum number of instances warm removes startup latency for baseline traffic, and allocating CPU outside requests lets those instances maintain connection pools. The service can still scale to the maximum instance count during peaks, so cost stays proportional to actual demand beyond the warm baseline.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Enable Cloud CDN for the Cloud Run service and set a long cache TTL for order-processing responses.
Why it's wrong here
Cloud CDN caches responses at the edge, which helps for cacheable content, but order-processing requests are dynamic and user-specific. Caching them would be incorrect and could expose sensitive data. CDN also does not reduce container startup time, so it does not address the cold-start issue described.
- ✗
Move the service to a GKE cluster with cluster autoscaling and a horizontal pod autoscaler.
Why it's wrong here
Migrating to GKE changes the platform and adds operational overhead. While GKE can keep pods running, it does not inherently solve cold-start latency for a container that initializes connection pools at startup, and it introduces cluster management costs. This is a heavier change than needed when Cloud Run offers a direct warm-instance configuration.
- ✓
Set the minimum number of instances to a value greater than zero and enable CPU always allocated for the service.
Why this is correct
Setting a minimum instance count keeps warm instances ready to serve traffic, eliminating cold starts for the baseline load. Enabling CPU always allocated ensures those instances retain CPU outside request processing, which is necessary for background initialization and connection pool maintenance. Together they reduce latency during spikes while allowing the maximum instance count to scale for peak demand.
- ✗
Increase the maximum number of instances and set the container concurrency to one.
Why it's wrong here
Raising the maximum instance count allows more scaling but does not reduce the time each new instance takes to start. Setting concurrency to one forces a new instance for every concurrent request, which increases the number of cold starts during a spike and can worsen latency. This combination addresses capacity limits, not startup delay.
Go deeper
Related to this question
Learn chapter
Billing, Budgets, and Cost Management
Key term
Service
A service is a software component or system that performs a specific function and is available to be used by other programs or users over a network.
Key term
Latency
Latency is the time delay between a request being sent over a network and the response being received, often measured in milliseconds.
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Google Cloud exam blueprint
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