Google PCA Ensure solution and operations reliability Practice Test 6 — 15 Questions

Question 1

A team is using Cloud Functions and wants to ensure retries on failure. What is the best practice?

Accepted Answer

Configure maximum retries and set dead-letter topic.. Cloud Functions (2nd gen) and Cloud Run allow configuring maximum retry attempts and a dead-letter topic to handle messages that repeatedly fail processing. This ensures that transient failures are retried automatically, while persistent failures are captured in a dead-letter queue for later analysis, preventing message loss and enabling reliable event-driven processing.

Answer

Increase function timeout.

Answer

Use background functions with Pub/Sub.

Answer

Use synchronous invocation.

Question 2

A company uses Cloud Storage for backup data. They want to protect against accidental deletion. Which option is best?

Accepted Answer

Enable object versioning.. Object versioning in Cloud Storage preserves every version of an object, including overwrites and deletions. When versioning is enabled, a delete operation creates a delete marker instead of permanently removing the object, allowing easy recovery. This directly protects against accidental deletion by retaining all previous object versions.

Answer

Use a lifecycle policy.

Answer

Set a retention policy.

Answer

Use object holds.

Question 3

A company is designing a highly available application on GCE. Which TWO steps should they take to ensure reliability?

Accepted Answer

Use a managed instance group with autohealing.. A managed instance group (MIG) with autohealing automatically replaces unhealthy VM instances based on health check results, ensuring the application remains available even if individual instances fail. This is a core reliability pattern for stateless applications on Compute Engine, as it provides self-healing infrastructure without manual intervention.

Answer

Use a global external HTTP(S) load balancer.

Answer

Use persistent disks without snapshots.

Answer

Deploy instances in a single zone to avoid latency.

Question 4

A company runs a stateful application on GKE using StatefulSets. Which THREE practices improve reliability?

Accepted Answer

Use headless services.. A headless service (clusterIP: None) allows direct pod-to-pod communication without load balancing, which is essential for stateful applications like databases that require stable network identities. Each pod in a StatefulSet gets a unique DNS name (e.g., pod-0.service.namespace.svc.cluster.local), enabling reliable discovery and ordering for replication, leader election, and failover. This ensures that clients always reach the correct pod instance, improving overall reliability.

Answer

Use horizontal autoscaling based on disk usage.

Answer

Use persistent volumes with reclaim policy Delete.

Question 5

A company is migrating a critical database to Cloud SQL for MySQL. Which TWO actions ensure high availability?

Accepted Answer

Enable automatic backups.. Enabling automatic backups in Cloud SQL for MySQL ensures that point-in-time recovery (PITR) and daily backups are automatically taken, which is a fundamental requirement for high availability. While backups alone do not provide instant failover, they are essential for data durability and recovery in case of a disaster, and the question asks for actions that 'ensure high availability'—backups are a core component of a high-availability strategy by enabling recovery from data loss or corruption.

Answer

Use read replicas in multiple zones.

Answer

Configure a failover replica with a different IP.

Answer

Enable multi-region failover.

Question 6

A user reports that an application running on instance-1 is unreliable and often restarts. What is the most likely cause?

Accepted Answer

The instance is preemptible and can be terminated at any time.. Preemptible instances (now called 'spot instances' in Google Cloud) can be terminated by Google Compute Engine at any time due to resource demands, with only 30 seconds of warning. This makes them unsuitable for applications that require reliability and continuous uptime, as the instance can be stopped abruptly, causing the application to restart or become unavailable.

Answer

The instance is in a single zone without redundancy.

Answer

The machine type is too small.

Answer

The instance is using an outdated image.

Question 7

Company A runs a containerized application on Google Kubernetes Engine (GKE) with 3 node pools: one for frontend, one for backend, and one for stateful databases. The backend services experience periodic latency spikes. After investigation, they found that the spikes correlate with the node pool autoscaler scaling down nodes. The backend services are deployed as Deployments with resource requests and limits set to 100m CPU and 200Mi memory each. The node pool uses n1-standard-2 machine types. The cluster autoscaler is enabled. What should they do to prevent the latency spikes?

Accepted Answer

Configure a PodDisruptionBudget for the backend Deployment with minAvailable set to a high value.. The latency spikes occur because the cluster autoscaler is terminating nodes that host backend Pods, causing those Pods to be rescheduled and disrupting traffic. A PodDisruptionBudget (PDB) with a high minAvailable value ensures that a minimum number of backend Pods remain available during voluntary disruptions like node scale-down, preventing the sudden loss of capacity that leads to latency spikes. This directly addresses the root cause without disabling autoscaling or misconfiguring scheduling.

Answer

Disable cluster autoscaler for the backend node pool.

Answer

Use node taints and tolerations to isolate the backend services.

Answer

Increase the resource requests for the backend services to ensure they are scheduled on dedicated nodes.

Question 8

Company B uses Cloud Endpoints to expose their API. Recently, they started seeing 503 errors during periods of high traffic. They have enabled Cloud Endpoints with a moderate quota. The backend is running on Cloud Run. The Cloud Run service is configured with min instances = 0 and max instances = 100. The container concurrency is set to 80. The average request latency is 200ms. What is the most likely cause and what should they do?

Accepted Answer

Cloud Run is scaling too slowly; set min instances to a higher value.. The 503 errors during high traffic are most likely caused by Cloud Run's scaling latency. With min instances = 0, new requests must wait for a container to start (cold start), and during traffic spikes, the scaling algorithm may not provision instances quickly enough, leading to request timeouts and 503s. Setting a higher min instances value ensures a warm pool of containers is always ready to handle traffic bursts, reducing cold start delays.

Answer

The container concurrency is too low; increase it to 200.

Answer

The backend is experiencing cold starts; set a higher CPU limit.

Answer

The Cloud Endpoints quota is being exhausted; increase the quota.

Question 9

A company runs a critical application on Compute Engine instances in a managed instance group (MIG) with autoscaling. Users report intermittent 503 errors during traffic spikes. Which action should the company take to improve reliability?

Accepted Answer

Configure a health check with a sufficient initial delay (grace period) in the MIG. Intermittent 503 errors during traffic spikes often indicate that new VM instances are being started but are not yet ready to serve traffic, causing the load balancer to forward requests to them prematurely. Configuring a health check with a sufficient initial delay (grace period) in the MIG ensures that newly created instances are given time to fully initialize and pass health checks before they receive traffic, preventing 503 errors. This directly addresses the root cause by allowing the application to become healthy before being added to the load balancer's backend.

Answer

Change the load balancer from regional to global

Answer

Increase the autoscaling cool-down period from 60s to 120s

Answer

Increase the maximum number of instances in the MIG

Question 10

A company uses Cloud Spanner for a global financial application. They need to ensure that a regional outage does not cause data loss. The application requires strong consistency and low latency reads and writes across multiple regions. Which configuration meets the reliability requirements?

Accepted Answer

Use a multi-region Spanner instance with a primary region and two witness regions. A multi-region Spanner instance with a primary region and two witness regions uses Google's synchronous replication across three regions, ensuring strong consistency and no data loss during a regional outage. Witness regions participate in the Paxos quorum without serving read traffic, guaranteeing that writes are committed in at least two regions before acknowledgment, which meets the requirement for zero data loss and low latency reads and writes.

Answer

Use a multi-region Spanner instance with read replicas in two other regions

Answer

Use a single-region Spanner instance and schedule backups to Cloud Storage

Answer

Use a single-region Spanner instance with point-in-time recovery (PITR) enabled

Question 11

A company runs a microservices-based application on Google Kubernetes Engine (GKE) with a Regional cluster. They want to improve reliability by implementing best practices for pod scheduling and resilience. Which TWO actions should they take? (Choose two.)

Accepted Answer

Define a PodDisruptionBudget for each deployment to limit the number of concurrent disruptions. A PodDisruptionBudget (PDB) limits the number of Pods of a replicated application that can be down simultaneously from voluntary disruptions, such as node maintenance or cluster upgrades. This ensures that a minimum number of replicas remain available, improving application reliability during planned events.

Answer

Set terminationGracePeriodSeconds to 0 for faster pod termination during scale-down

Answer

Enable cluster autoscaler to automatically add nodes when pods are pending

Answer

Set resource requests equal to limits to ensure guaranteed QoS class

Question 12

A company runs a stateful workload on Compute Engine with regional persistent disks (PD). They need to implement a disaster recovery (DR) plan with a Recovery Point Objective (RPO) of less than 1 hour and Recovery Time Objective (RTO) of less than 4 hours. Which THREE steps should they include in their DR plan? (Choose three.)

Accepted Answer

Take snapshots of the persistent disk every 30 minutes and copy them to a Cloud Storage bucket in another region. Taking snapshots every 30 minutes meets the RPO of less than 1 hour. By copying these snapshots to a Cloud Storage bucket in another region, you ensure data is available in a DR region for recovery, which is essential for cross-region disaster recovery.

Answer

Create a snapshot schedule for the persistent disk every 4 hours

Answer

Use regional persistent disks to automatically replicate data to a second zone

Question 13

You are the lead cloud architect for a startup that runs a web application on Google Kubernetes Engine (GKE) with a standard (zonal) cluster. The application is deployed with 3 replicas of a stateless frontend service. During a recent incident, a zone outage caused all GKE nodes to become unavailable, leading to application downtime of 45 minutes. You need to redesign the cluster to tolerate a single zone failure with no more than 5 minutes of downtime. Your budget allows for at most a 20% increase in compute costs. Which approach should you take?

Accepted Answer

Migrate the cluster to a regional GKE cluster with nodes in 3 zones and distribute replicas across zones. D is correct because a regional GKE cluster distributes nodes across three zones, ensuring that if one zone fails, the remaining two zones continue serving traffic. By spreading the 3 replicas across zones (e.g., one per zone), the application tolerates a single zone outage with near-zero downtime, and the 20% cost increase covers the additional node pool overhead without exceeding the budget.

Answer

Increase the number of replicas from 3 to 9 and keep the zonal cluster

Answer

Change the frontend deployment to use regional persistent disks

Answer

Deploy second GKE cluster in another region and use global load balancer for failover

Question 14

You manage a batch data processing workload on Compute Engine that runs daily on a single VM. The VM uses a standard persistent disk (pd-standard) for input data and output results. Recently, the VM crashed due to a hardware failure, and the job failed. You need to implement a solution that automatically recovers from VM failures with minimal data loss. The job is idempotent and can restart from the beginning if necessary. Which solution should you choose?

Accepted Answer

Create a managed instance group (MIG) with an instance template that includes a startup script to run the job, and enable autohealing. A managed instance group (MIG) with autohealing automatically recreates a VM instance when it fails, and the startup script ensures the idempotent job reruns from the beginning on the new VM. This minimizes data loss by using the same persistent disk (or a fresh one) and leverages Compute Engine's health check mechanism to detect failure and trigger recovery without manual intervention.

Answer

Take a snapshot of the persistent disk every hour and create a new VM from the latest snapshot on failure

Answer

Use Cloud Scheduler to restart the VM every hour until the job completes

Answer

Add a startup script to the existing VM to rerun the job on boot, and enable automatic restart

Question 15

Your company runs a customer-facing API on Cloud Run with a concurrency setting of 80. The API calls a backend Cloud Function that performs a heavy computation (2–5 seconds). During peak hours, the API experiences increased latency and some requests time out after 60 seconds. Monitoring shows that the Cloud Run max instances is set to 100, and the Cloud Function max instances is set to 10. The timeout for Cloud Run is set to 300 seconds. The Cloud Function's timeout is set to 540 seconds. You need to reduce end-to-end latency and prevent timeouts while minimizing cost. Which action is most effective?

Accepted Answer

Increase Cloud Function max instances from 10 to 100. The bottleneck is the Cloud Function's low max instances (10), causing queuing. Increasing Cloud Function max instances allows more concurrent requests to be processed, reducing latency and timeouts. Option A is wrong because concurrency on Cloud Run is separate from backend; reducing concurrency would require more Cloud Run containers and increase cost. Option B is wrong because increasing Cloud Run max instances alone doesn't help if Cloud Function capacity is the limit. Option D is wrong because increasing Cloud Run timeout doesn't reduce latency; it just keeps the connection alive longer.

Answer

Increase Cloud Run max instances from 100 to 500

Answer

Increase Cloud Run request timeout from 300 to 600 seconds

Answer

Reduce Cloud Run concurrency from 80 to 10