Google PCA Deployment Practice Question
A company is designing a microservices architecture on Google Kubernetes Engine (GKE) for a global user base. They require high availability across multiple zones, automatic scaling, and rolling updates without downtime. Which Kubernetes workload resource should they use for each service?
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
✓
Deployment with pod anti-affinity rules spread across zones
The correct option is B: a Deployment with pod anti-affinity rules spread across zones. Deployments are the standard GKE workload for stateless microservices, providing declarative rolling updates (via RollingUpdate strategy with maxSurge/maxUnavailable) and integration with the Horizontal Pod Autoscaler for automatic scaling, while pod anti-affinity (or topologySpreadConstraints) spreads replicas across multiple zones for high availability. StatefulSet (A) is designed for stateful workloads needing stable network identities and per-pod PersistentVolumes, not for stateless services requiring rolling updates and autoscaling. Job (C) runs finite batch tasks to completion rather than long-running services, and DaemonSet (D) schedules one pod per node for node-level agents, not scalable service replicas.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
StatefulSet with volumeClaimTemplates for persistent storage
Why it's wrong here
StatefulSet gives each pod a stable identity and its own PersistentVolumeClaim, which suits stateful databases rather than stateless services needing horizontal scaling and rolling updates. It is tempting because StatefulSets are the right choice when pods require durable per-instance storage and ordered, stable network identities, such as replicated databases or message brokers.
- ✓
Deployment with pod anti-affinity rules spread across zones
Why this is correct
A Deployment manages stateless replicas and performs rolling updates, satisfying the no-downtime requirement. Pod anti-affinity rules spread those replicas across zones, delivering the multi-zone high availability the stem demands, while the Horizontal Pod Autoscaler handles automatic scaling.
- ✗
Job for batch processing
Why it's wrong here
A Job runs pods to completion for finite batch tasks, then stops; it provides no long-running replica set, so it cannot serve continuous microservice traffic or perform rolling updates. It is tempting because Jobs correctly handle one-off or scheduled batch workloads, such as data processing or report generation, where termination on completion is the desired behaviour.
- ✗
DaemonSet to ensure one pod per node
Why it's wrong here
A DaemonSet schedules exactly one pod per node for node-level agents, so it cannot scale replicas independently of cluster size or perform the rolling updates a service needs. It is tempting because DaemonSets are correct for cluster-wide functions like log shippers, monitoring agents, or CNI plugins that must run on every node.
Go deeper
Related to this question
Learn chapter
Google Cloud Resource Hierarchy and Organization
Key term
Anthos
Anthos is a Google Cloud platform that lets you run applications consistently across different computing environments, like on-premises data centers and multiple public clouds.
Key term
Google Kubernetes Engine
Google Kubernetes Engine (GKE) is a managed Kubernetes service on Google Cloud that lets you deploy, scale, and manage containerized applications without having to operate the underlying cluster control plane.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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