Google PCA Analyze and optimize technical and business processes Practice Test 5 — 15 Questions

Question 1

A financial services company needs a disaster recovery plan for a critical application running on GKE. The application uses Cloud SQL for MySQL. The RPO is 5 minutes and RTO is 15 minutes. Which design meets these requirements cost-effectively?

Accepted Answer

Use Cloud SQL cross-region replication (MySQL) with a failover replica in another region, and deploy GKE cluster in that region with the same configuration.. Cloud SQL cross-region replication provides an asynchronous replica in another region with a typical replication lag of a few seconds, meeting the 5-minute RPO. The failover replica can be promoted in minutes, and deploying a GKE cluster in the same region with identical configuration allows the application to connect to the promoted replica, achieving the 15-minute RTO. This approach is cost-effective because you only pay for the replica and the second GKE cluster when needed for failover testing or actual disaster recovery.

Answer

Use Cloud SQL for MySQL with multi-region database flag and route traffic to nearest region via Cloud Load Balancing.

Answer

Set up VPC peering between two regions and use Cloud DNS to direct traffic in failover.

Answer

Use Cloud SQL backups to Cloud Storage and restore in another region, with GKE cluster recreated via Deployment Manager.

Question 2

A company stores large amounts of data in Cloud Storage and wants to reduce costs. Which two actions should they take? (Choose two.)

Accepted Answer

Enable object versioning and configure lifecycle rules to delete noncurrent versions after 90 days.. Option B is correct because enabling object versioning and configuring lifecycle rules to delete noncurrent versions after 90 days directly reduces storage costs by automatically removing older object versions that are no longer needed. Option D is correct because transitioning objects to Nearline or Coldline storage classes after 30 days leverages lower-cost storage tiers for infrequently accessed data, aligning cost with access patterns.

Answer

Disable object versioning to prevent multiple versions.

Answer

Add bucket labels to track cost by department.

Answer

Change the default storage class to Standard for all buckets.

Question 3

A company runs a web application on App Engine Standard environment. The application experiences downtime during deployments due to traffic shifting. Which two strategies should they implement to improve reliability? (Choose two.)

Accepted Answer

Use traffic splitting to gradually migrate traffic to the new version.. Option C is correct because App Engine's traffic splitting feature allows you to gradually shift traffic from the old version to the new version, minimizing the impact of deployment-related errors or performance issues. This incremental migration reduces the risk of a full outage during deployment and enables quick rollback if problems arise.

Answer

Use Cloud Endpoints to manage API traffic and route deployments.

Answer

Increase the number of idle instances to handle traffic during deployment.

Answer

Set manual scaling to avoid autoscaling delays.

Question 4

A company uses Cloud Build to automate their CI/CD pipeline. They want to optimize the build process for a Java application. Which three practices should they adopt? (Choose three.)

Accepted Answer

Parallelize independent build steps by using Cloud Build's step parallelism or by splitting into multiple builds.. Option A is correct because Cloud Build allows you to define build steps that run sequentially by default, but you can parallelize independent steps by using the `waitFor` field to specify dependencies. This reduces total build time by running non-dependent steps concurrently, which is a key optimization for CI/CD pipelines. Splitting into multiple builds is also a valid approach for parallel execution.

Answer

Use a custom build step that downloads all tools from the internet each time.

Answer

Use a high-CPU machine type (e.g., n1-highcpu-64) for faster compilation.

Question 5

A company is running a web application on Compute Engine instances that average 20% CPU utilization. They want to reduce costs without impacting performance. What is the most effective action?

Accepted Answer

Rightsize instances to a smaller machine type based on usage metrics.. The instances are averaging only 20% CPU utilization, indicating they are over-provisioned. Rightsizing to a smaller machine type directly reduces the compute cost per instance while maintaining adequate performance for the current workload, as the smaller instance can handle the existing load without degradation.

Answer

Change instance type to e2-standard-4.

Answer

Purchase 3-year committed use discounts.

Answer

Use preemptible instances for all traffic.

Question 6

A team deployed a new version of a service on Cloud Run. After deployment, users report 502 errors. The logs show "Error: Server Error" with no stack trace. What is the first step the team should take to diagnose the issue?

Accepted Answer

Check the container image for missing dependencies or misconfiguration.. The 502 error with 'Error: Server Error' and no stack trace typically indicates that the container failed to start or crashed immediately after startup, often due to missing dependencies or misconfiguration in the container image. Cloud Run requires the container to listen on the port specified by the PORT environment variable (default 8080) and respond to health checks; if the container exits or fails to bind, Cloud Run returns a 502. Checking the container image is the first diagnostic step because it addresses the most common root cause before investigating runtime or scaling issues.

Answer

Enable Cloud Debugger to inspect the running instance.

Answer

Increase Cloud Run max instances limit.

Answer

Rollback to the previous version immediately.

Question 7

A company wants to implement a CI/CD pipeline for a microservices application on GKE. They require automated canary deployments with gradual traffic shifting and automatic rollback on metric failure. Which Google Cloud service is most suitable?

Accepted Answer

Cloud Deploy with Skaffold.. Cloud Deploy with Skaffold is the most suitable because it provides native support for progressive delivery on GKE, including automated canary deployments with gradual traffic shifting (using Service Mesh or Ingress) and automatic rollback based on Cloud Monitoring metrics. Skaffold handles the build and deploy configuration, while Cloud Deploy manages the rollout pipeline, approval gates, and metric-driven rollback logic without requiring manual intervention.

Answer

Cloud Build with Deployment Manager.

Answer

Spinnaker on GKE.

Answer

Istio with manual traffic management.

Question 8

A financial services company uses Cloud SQL for MySQL for a critical application. They need zero downtime during maintenance and automatic failover across zones. They configured a Cloud SQL instance with high availability (HA). During a recent regional outage, the application experienced 10 minutes of downtime. What should they add to improve availability?

Accepted Answer

Create a cross-region replica and promote on failure.. Option B is correct because a cross-region replica provides a read-replica in a different region that can be promoted to a primary instance during a regional outage, enabling recovery with minimal downtime. This addresses the scenario where a single-region HA configuration (which uses zonal redundancy within the same region) cannot survive a full regional outage, as occurred in the question. Promoting the replica is a manual or automated failover action that restores write capability in the secondary region, reducing downtime from 10 minutes to seconds or minutes depending on replication lag.

Answer

Configure a warm standby instance in another region using migration.

Answer

Use Cloud SQL Proxy with multiple endpoints.

Answer

Enable database flags for faster failover detection.

Question 9

A company is using BigQuery for data analytics. They want to optimize costs while maintaining query performance. Which TWO actions should they take? (Choose 2.)

Accepted Answer

Partition tables by date.. Partitioning tables by date (Option C) is correct because it allows BigQuery to prune partitions during query execution, scanning only the relevant date ranges instead of the entire table. This reduces the amount of data processed, directly lowering query costs under on-demand pricing while maintaining performance through reduced I/O.

Answer

Use reserved slots with flat-rate pricing.

Answer

Always use SELECT *.

Answer

Materialize frequently used queries as tables.

Question 10

A company is migrating a legacy monolithic application to Google Cloud. They want to adopt microservices and improve deployment frequency. Which THREE practices should they adopt? (Choose 3.)

Accepted Answer

Use Infrastructure as Code (IaC) with Terraform.. Option A is correct because Infrastructure as Code (IaC) with Terraform enables declarative, version-controlled provisioning of cloud resources. This supports the microservices migration by allowing teams to spin up consistent, repeatable environments for each service, which is essential for increasing deployment frequency without manual configuration errors.

Answer

Build a single deployment pipeline for all services.

Answer

Implement blue/green deployments.

Question 11

A company runs a batch processing workload on Compute Engine. They need to minimize cost and ensure jobs complete within a 24-hour window. Which THREE strategies should they implement? (Choose 3.)

Accepted Answer

Use preemptible VMs for fault-tolerant jobs.. Preemptible VMs are significantly cheaper than standard VMs and are ideal for batch processing workloads that are fault-tolerant. Since the job can handle interruptions and be restarted, using preemptible VMs directly reduces cost while still completing within the 24-hour window if the job is designed to checkpoint progress.

Answer

Use sole-tenant nodes for resource isolation.

Answer

Configure instance reservations for guaranteed capacity.

Question 12

A company runs a customer-facing web application on Google Kubernetes Engine (GKE) in us-central1. The application uses a Cloud SQL for PostgreSQL database for user data. Recently, they noticed that during peak hours, the application response times increase significantly, and some requests time out. The team has already scaled the GKE nodepool to the maximum size, but the issue persists. Database CPU utilization is at 80%, and connections are near the max limit. The application uses connection pooling via PgBouncer running as a sidecar. The team suspects the database is the bottleneck. They need to improve performance with minimal cost impact. What should they do?

Accepted Answer

Add read replicas and split read/write traffic.. Option D is correct because adding read replicas and splitting read/write traffic offloads read queries from the primary Cloud SQL instance, reducing CPU and connection pressure. PgBouncer as a sidecar can be configured to route read-only transactions to replicas, while writes go to the primary. This directly addresses the 80% CPU and max connections issue without increasing costs as much as scaling up the machine type.

Answer

Enable Cloud SQL automatic storage increase.

Answer

Increase the max connections parameter on Cloud SQL.

Answer

Increase the Cloud SQL machine type to the next tier.

Question 13

A company is using Cloud Functions (2nd gen) for event-driven processing of uploaded images in Cloud Storage. Each image is resized to multiple sizes and stored back in different buckets. Recently, the number of uploads has increased 10x, and the team notices that some images are not being processed, and logs show function execution timeouts after 60 seconds. The function's timeout is set to 60 seconds. The code processes images sequentially. The team needs to reliably process all images with minimal code changes. What should they do?

Accepted Answer

Use Cloud Tasks to queue the processing and run the function as a task handler.. Option D is correct because using Cloud Tasks decouples the processing, allowing retries and better scaling. Option A (increase timeout) delays the problem. Option B (split into multiple functions) requires significant code changes. Option C (increase memory) may speed up processing but may not handle all image sizes reliably.

Answer

Increase the memory allocation for the function.

Answer

Increase the Cloud Function timeout to 540 seconds.

Answer

Split the function into separate functions for each resize operation.

Question 14

A company is using Cloud Spanner to serve a global gaming application. They have a single instance in us-central1. Players in Asia experience high latency. The application reads and writes player profiles. The team wants to reduce latency for Asian players while keeping write latency low for global consistency. They need a solution that minimizes operational overhead and uses native Spanner capabilities. What should they do?

Accepted Answer

Configure a multi-region instance configuration that includes us-central1 and an Asian region.. A multi-region instance configuration in Cloud Spanner is the correct solution because it provides a single writable instance that spans multiple geographic regions, allowing reads and writes to be served locally in each region while maintaining strong global consistency. This minimizes latency for Asian players by enabling local reads and writes, and it uses native Spanner capabilities without additional operational overhead. Option A directly addresses the requirement for low write latency and global consistency by leveraging Spanner's built-in multi-region replication.

Answer

Add read replicas in Asia using Spanner's read-only replicas.

Answer

Use Cloud CDN to cache player profiles at the edge.

Answer

Create a new instance in asia-east1 and use Directed Read options to route reads from Asia.

Question 15

A large enterprise is migrating its on-premises data warehouse to BigQuery. The current warehouse is 100 TB and uses complex ETL jobs that run on SQL Server Integration Services (SSIS). The team wants to minimize migration effort and maintain the same SQL logic for transformations. They plan to use BigQuery's standard SQL. They also need to schedule transformations and load data from multiple on-premises sources. Which approach should they take?

Accepted Answer

Use Cloud Composer (Airflow) to orchestrate SQL statements in BigQuery, and use Data Transfer Service for scheduled loads.. Option A is correct: Cloud Composer (Airflow) can orchestrate BigQuery SQL statements, and Data Transfer Service handles scheduled loads from on-premises sources, minimizing code changes. Option B (Data Fusion) does not directly replicate SSIS. Option C (Dataflow) requires rewriting SSIS packages. Option D (SSIS on Compute Engine) still needs migration and doesn't leverage BigQuery's strengths.

Answer

Connect SSIS to BigQuery using ODBC and run SSIS packages in a VM on Compute Engine.

Answer

Rewrite SSIS packages as Dataflow pipelines using Apache Beam.

Answer

Use Data Fusion to replicate SSIS packages.