Question 285 of 500

Quick Answer

The answer is to reduce `containerConcurrency` to 10. High tail latency under moderate load in Cloud Run typically means requests are piling up in a queue behind a single instance, as the default concurrency allows too many simultaneous requests to compete for CPU and memory. By capping concurrency at 10, you limit request multiplexing, which reduces queueing delay and ensures each request gets processed faster, directly lowering the tail of the latency distribution. On the Google Professional Cloud Developer exam, this scenario tests your understanding of how Cloud Run’s concurrency model affects performance under load—a common trap is to scale up instances or increase CPU, but those don’t address the root cause of request queuing. Remember the memory tip: “Concurrency controls chaos—lower it to lose the tail.”

PCD Practice Question: Designing highly scalable, available, and reliable cloud-native applications

This PCD practice question tests your understanding of designing highly scalable, available, and reliable cloud-native applications. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.

Exhibit

apiVersion: serving.knative.dev/v1
kind: Service
metadata:
  name: my-app
spec:
  template:
    spec:
      containerConcurrency: 80
      containers:
      - image: gcr.io/my-project/my-app:latest
        ports:
        - containerPort: 8080
        resources:
          limits:
            cpu: "1"
            memory: "512Mi"
      timeoutSeconds: 300

Refer to the exhibit. The Cloud Run service is experiencing high tail latency under moderate load. Which change would most effectively reduce latency?

Question 1mediummultiple choice
Full question →

Exhibit

apiVersion: serving.knative.dev/v1
kind: Service
metadata:
  name: my-app
spec:
  template:
    spec:
      containerConcurrency: 80
      containers:
      - image: gcr.io/my-project/my-app:latest
        ports:
        - containerPort: 8080
        resources:
          limits:
            cpu: "1"
            memory: "512Mi"
      timeoutSeconds: 300

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

Reduce containerConcurrency to 10.

High tail latency under moderate load often indicates that requests are queuing behind each other due to excessive concurrency. Reducing `containerConcurrency` to 10 limits the number of simultaneous requests each container instance handles, which reduces queueing delay and improves per-request response time. This is the most effective change because it directly controls the request multiplexing level, preventing a single instance from being overwhelmed.

Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.

Answer analysis

Option-by-option breakdown

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

  • Increase CPU limit to 2.

    Why it's wrong here

    While more CPU may help, the primary issue is concurrency; simply adding CPU without adjusting concurrency may not resolve the latency spikes.

  • Increase containerConcurrency to 250.

    Why it's wrong here

    Raising concurrency further increases contention, making tail latency worse.

  • Increase timeoutSeconds to 600.

    Why it's wrong here

    Increasing timeout allows longer requests but does not reduce latency; it may mask the problem.

  • Reduce containerConcurrency to 10.

    Why this is correct

    Lower concurrency reduces request queuing per container, improving tail latency under load.

    Related concept

    Read the scenario before looking for a memorised answer.

Common exam traps

Common exam trap: answer the scenario, not the keyword

Cisco often tests the misconception that increasing resources (CPU/memory) or timeouts always improves performance, when in fact controlling concurrency is the key to reducing tail latency in serverless platforms like Cloud Run.

Detailed technical explanation

How to think about this question

Cloud Run's `containerConcurrency` setting controls the maximum number of requests that can be routed to a single container instance concurrently. When concurrency is high, requests can queue at the container's HTTP server, leading to increased tail latency due to head-of-line blocking. Under the hood, Cloud Run uses the Knative serving layer, which respects this concurrency limit to decide when to scale out new instances. In practice, for latency-sensitive workloads, a lower concurrency (e.g., 10) ensures each request gets more predictable CPU and memory resources, reducing jitter.

KKey Concepts to Remember

  • Read the scenario before looking for a memorised answer.
  • Find the constraint that changes the correct option.
  • Eliminate answers that are true in general but not in this case.

TExam Day Tips

  • Watch for words such as best, first, most likely and least administrative effort.
  • Review why wrong options are wrong, not only why the correct option is correct.

Key takeaway

Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.

Real-world example

How this comes up in practice

A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.

What to study next

Got this wrong? Here's your next step.

Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.

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FAQ

Questions learners often ask

What does this PCD question test?

Designing highly scalable, available, and reliable cloud-native applications — This question tests Designing highly scalable, available, and reliable cloud-native applications — Read the scenario before looking for a memorised answer..

What is the correct answer to this question?

The correct answer is: Reduce containerConcurrency to 10. — High tail latency under moderate load often indicates that requests are queuing behind each other due to excessive concurrency. Reducing `containerConcurrency` to 10 limits the number of simultaneous requests each container instance handles, which reduces queueing delay and improves per-request response time. This is the most effective change because it directly controls the request multiplexing level, preventing a single instance from being overwhelmed.

What should I do if I get this PCD question wrong?

Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.

What is the key concept behind this question?

Read the scenario before looking for a memorised answer.

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Last reviewed: Jun 25, 2026

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