The correct choices are defining resource requests and limits for all containers and using pod anti-affinity to spread pods across nodes. Pod anti-affinity forces the Kubernetes scheduler to distribute replicas of the same application onto different nodes, which prevents a single node failure from taking down the entire service—this is critical for stateless workloads that need high availability. Setting resource requests and limits ensures the scheduler can place pods on nodes with sufficient capacity, while also capping resource usage to avoid one pod starving others of CPU or memory. On the Google Professional Cloud Developer exam, this question tests your understanding of production-grade GKE best practices for resilience and resource governance; a common trap is confusing pod anti-affinity with node affinity, which targets specific node types rather than spreading pods. Remember the mnemonic “Spread and Bound”—spread pods with anti-affinity, bound resource usage with requests and limits.
PCD Deploying applications Practice Question
This PCD practice question tests your understanding of deploying 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.
Which TWO of the following are best practices when deploying applications on Google Kubernetes Engine (GKE)?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "best"
Why it matters: Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Use pod anti-affinity to spread pods across nodes.
Option C is correct because pod anti-affinity ensures pods are scheduled across different nodes, improving fault tolerance and high availability. This is a best practice for stateless applications to avoid a single point of failure during node failures. Option D is correct because defining resource requests and limits allows the Kubernetes scheduler to make informed placement decisions and prevents resource starvation, ensuring predictable application performance.
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.
✗
Store sensitive configuration data in environment variables.
Why it's wrong here
Use Secrets or Secret Manager instead.
✗
Skip liveness and readiness probes for stateless applications.
Why it's wrong here
Health probes are important for all applications.
✓
Use pod anti-affinity to spread pods across nodes.
Why this is correct
Improves availability by distributing replicas.
Clue confirmation
The clue word "best" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✓
Define resource requests and limits for all containers.
Why this is correct
Ensures proper scheduling and avoids resource starvation.
Clue confirmation
The clue word "best" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✗
Use the default Compute Engine service account for pods.
Why it's wrong here
Least privilege principle: create dedicated service accounts.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Google Cloud often tests the misconception that liveness and readiness probes are optional for stateless workloads, but in GKE they are critical for self-healing and traffic management, even for stateless applications.
Detailed technical explanation
How to think about this question
Pod anti-affinity uses the 'requiredDuringSchedulingIgnoredDuringExecution' or 'preferredDuringSchedulingIgnoredDuringExecution' policy with topologyKey 'kubernetes.io/hostname' to enforce node-level spreading. Under the hood, the kube-scheduler evaluates affinity rules during pod binding, and if constraints cannot be met, the pod remains pending. In a real-world scenario, a multi-replica web service without anti-affinity could have all replicas on one node, causing total outage during node maintenance or failure.
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
An e-commerce site experiences heavy traffic on Black Friday and near-zero traffic during off-peak weeks. Rather than provisioning permanent large VMs, the team uses auto-scaling groups that add capacity automatically under load and reduce it overnight. Questions like this test whether you understand elasticity, availability zones, and cloud compute scaling patterns.
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.
Deploying applications — This question tests Deploying applications — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Use pod anti-affinity to spread pods across nodes. — Option C is correct because pod anti-affinity ensures pods are scheduled across different nodes, improving fault tolerance and high availability. This is a best practice for stateless applications to avoid a single point of failure during node failures. Option D is correct because defining resource requests and limits allows the Kubernetes scheduler to make informed placement decisions and prevents resource starvation, ensuring predictable application performance.
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.
Are there clue words in this question I should notice?
Yes — watch for: "best". Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Question Discussion
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