- A
Refactor the application to store session state in Cloud Memorystore for Redis and make the application stateless.
Redis provides a fast, scalable, shared session store that decouples session state from individual pods.
- B
Use a StatefulSet with a headless service to assign stable network identities to pods.
Why wrong: StatefulSet does not solve the session state problem; it is for stateful applications requiring stable identities.
- C
Use GKE Ingress with session affinity (sticky sessions) to route requests to the same pod.
Why wrong: Sticky sessions can lead to unbalanced load and do not fully solve statelessness.
- D
Store session state in Cloud SQL using a replicated database.
Why wrong: Cloud SQL adds latency and is not designed for high-throughput session caching.
Quick Answer
The correct answer is to refactor the application to store session state in Cloud Memorystore for Redis and make the application stateless. This approach is essential for horizontal scaling in GKE because it decouples session data from individual pods; by externalizing state to a managed, highly available Redis service, any pod can handle any request, enabling seamless autoscaling and resilience against pod failures. On the Google Professional Cloud Architect exam, this scenario tests your understanding of the stateless design principle for containerized workloads—a common trap is assuming that sticky sessions or StatefulSets can solve the problem, but these undermine true horizontal elasticity. A key memory tip is to associate "GKE session state management" with the phrase "stateless pods, stateful backing store," which reinforces that the application itself must remain stateless while relying on a service like Memorystore for persistent session data.
Google PCA Manage implementation of cloud architecture Practice Question
This PCA practice question tests your understanding of manage implementation of cloud architecture. 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.
A company is migrating a monolithic application to Google Kubernetes Engine (GKE). The application currently runs on a single Compute Engine instance and stores session state in local memory. The migration must support horizontal scaling and high availability. What should the company do to manage session state in the new architecture?
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
Refactor the application to store session state in Cloud Memorystore for Redis and make the application stateless.
Option A is correct because migrating to a stateless architecture with Cloud Memorystore for Redis allows the application to scale horizontally without session state being tied to any single pod. By externalizing session state to a managed, highly available Redis service, any pod can handle any request, which is essential for high availability and autoscaling in GKE.
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.
- ✓
Refactor the application to store session state in Cloud Memorystore for Redis and make the application stateless.
Why this is correct
Redis provides a fast, scalable, shared session store that decouples session state from individual pods.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Use a StatefulSet with a headless service to assign stable network identities to pods.
Why it's wrong here
StatefulSet does not solve the session state problem; it is for stateful applications requiring stable identities.
- ✗
Use GKE Ingress with session affinity (sticky sessions) to route requests to the same pod.
Why it's wrong here
Sticky sessions can lead to unbalanced load and do not fully solve statelessness.
- ✗
Store session state in Cloud SQL using a replicated database.
Why it's wrong here
Cloud SQL adds latency and is not designed for high-throughput session caching.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Google Cloud often tests the distinction between 'making the application stateless' versus 'using sticky sessions or StatefulSets'—the trap here is that candidates may think session affinity (Option C) is sufficient for high availability, but it actually creates a single point of failure at the pod level.
Detailed technical explanation
How to think about this question
Cloud Memorystore for Redis provides sub-millisecond latency for session reads and writes, which is critical for maintaining user experience during scaling events. Under the hood, Redis uses an in-memory data structure store with optional persistence, and Memorystore offers automatic failover and replication, ensuring session data survives pod restarts. In a real-world scenario, a flash sale or traffic spike would cause GKE to spin up new pods; with Redis, all pods share the same session data, avoiding the 'sticky session' failure mode where a pod crash loses all its sessions.
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
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FAQ
Questions learners often ask
What does this PCA question test?
Manage implementation of cloud architecture — This question tests Manage implementation of cloud architecture — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Refactor the application to store session state in Cloud Memorystore for Redis and make the application stateless. — Option A is correct because migrating to a stateless architecture with Cloud Memorystore for Redis allows the application to scale horizontally without session state being tied to any single pod. By externalizing session state to a managed, highly available Redis service, any pod can handle any request, which is essential for high availability and autoscaling in GKE.
What should I do if I get this PCA 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 30, 2026
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