Cloud Digital Leader Scaling with Google Cloud operations Practice Question

Which TWO statements correctly describe Cloud Run scaling behavior?

⚠ Common exam trap

Google Cloud often tests the misconception that Cloud Run uses CPU or memory utilization for autoscaling, when in fact it uses request concurrency as the primary metric, and candidates may incorrectly select Option E because they associate autoscaling with resource metrics from other services.

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

✓

You can define a target concurrency to control how many requests each container instance handles.

Cloud Run allows you to set a target concurrency (the number of simultaneous requests a single container instance can handle). This is a key scaling parameter that controls how many requests are routed to each instance before Cloud Run spins up additional instances. By default, concurrency is set to 80, but you can adjust it up to 1000 or set it to 1 for sequential processing.

Answer analysis

Option-by-option breakdown

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

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The maximum number of instances can be set to 'default' which is unlimited.
Why it's wrong here
Cloud Run's default maximum instance count is 100, not unlimited. While you can configure a higher maximum up to the platform's allowed cap, the 'default' setting refers to the service's predefined limit, which is a finite number. There is no configuration that makes the maximum truly unlimited, so this statement is incorrect.
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You can set a minimum number of instances to ensure zero cold starts.
Why it's wrong here
Setting a minimum number of instances keeps a specified number of containers warm, which reduces the likelihood of cold starts for baseline traffic. However, if traffic suddenly spikes beyond the reserved minimum capacity, Cloud Run provisions additional instances that will experience cold starts. Therefore, min instances mitigate but do not guarantee zero cold starts under variable load.
✓
You can define a target concurrency to control how many requests each container instance handles.
Why this is correct
Cloud Run's container concurrency setting defines the maximum number of simultaneous requests each instance can process. Autoscaling uses this concurrency target to decide when to add or remove instances, ensuring that requests are distributed without overloading a single container. By adjusting this value, you can trade off between latency and resource efficiency, as lower concurrency increases instance count while higher concurrency packs more requests per instance.
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The number of container instances can be scaled to zero when there is no traffic.
Why this is correct
When the minimum instance count is set to zero, which is the default, Cloud Run automatically scales down to zero instances during periods of no traffic. This serverless behavior means you incur no compute cost for idle services, and only pay when requests are actively being processed. The first request after idle triggers a cold start as a new instance is provisioned.
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Autoscaling uses CPU and memory utilization to make decisions.
Why it's wrong here
Cloud Run's autoscaling decisions are based primarily on request concurrency, not on CPU or memory utilization. The system tracks the number of in-flight requests relative to the configured container concurrency limit and scales instances accordingly. Unlike virtual machine autoscalers that use resource metrics, Cloud Run does not consider CPU or memory usage when determining the number of instances, making this statement incorrect.

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Cloud Digital Leader Scaling with Google Cloud operations Practice Question

Why each option matters

Option-by-option breakdown

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