Google PCA Practice Test 47 — 15 Questions

Question 1

A logistics company is planning to migrate a batch ETL pipeline from on-premises Hadoop to Google Cloud. The pipeline processes several terabytes nightly, and the team wants to minimize infrastructure management while keeping the ability to tune the cluster for cost and performance. The data currently resides in an on-premises HDFS cluster. Which combination of services should the architect recommend?

Choose an answer to begin — your selection is scored in the full session.

Accepted Answer

Cloud Storage for durable object storage and Dataproc clusters created per job for processing.. Separating storage from compute with Cloud Storage and using ephemeral Dataproc clusters lets the team process nightly data without paying for idle infrastructure, while still selecting machine types and cluster sizes per job. Persistent clusters, self-managed Hadoop, and a full BigQuery rewrite each fail at least one requirement around management overhead or preserving existing Spark logic.

Answer

BigQuery for storage and analysis, replacing the Spark jobs entirely with SQL.

Answer

Persistent Dataproc clusters with local HDFS storage that run continuously and process jobs on a schedule.

Answer

Compute Engine VMs running a self-managed Hadoop distribution with Cloud Storage FUSE for input and output.

Question 2

A company uses Cloud Storage to store user-uploaded content. They want to ensure that the data is highly durable and protected against accidental deletion. Which two features should they enable? (Choose two.)

Accepted Answer

Object versioning.. Object versioning (C) is correct because it keeps prior versions of objects when they are overwritten or deleted, so an accidentally deleted or replaced object can be recovered rather than permanently lost. Bucket retention policy (D) is correct because it enforces a retention period during which objects cannot be deleted or overwritten, directly protecting data against accidental or premature deletion. Together these features address the durability and deletion-protection requirement for user-uploaded content in Cloud Storage. Requester pays (A) only shifts data-access and egress costs to the requester and provides no deletion protection. Lifecycle management (B) automates actions such as deleting or transitioning objects and can actually cause deletion, so it does not protect against accidental loss. Uniform bucket-level access (E) simplifies permission management by applying IAM uniformly at the bucket level, but it does not prevent accidental object deletion.

Answer

Requester pays.

Answer

Lifecycle management.

Answer

Uniform bucket-level access.

Question 3

You are responsible for ensuring the reliability of a high-traffic web application running on Google Kubernetes Engine (GKE). You need to implement a monitoring strategy that alerts you when the application's error rate exceeds 1% over a 5-minute window. You want to minimize false positives and ensure alerts are actionable. What should you do?

Accepted Answer

Create a Cloud Monitoring alerting policy based on the HTTP load balancer's 5xx error rate metric, with a threshold of 1% and a duration of 5 minutes.. Using the HTTP(S) load balancer's 5xx error rate metric provides a direct measure of errors as seen by clients. An alerting policy with a 1% threshold over 5 minutes aligns with the requirement. This approach is managed, reliable, and minimizes false positives because it uses a consistent metric from the load balancer, not application logs or internal metrics.

Answer

Configure a log-based metric in Cloud Logging that counts log entries with severity ERROR, and create an alerting policy if the count exceeds a threshold.

Answer

Use Prometheus to scrape application metrics and configure an alert in Prometheus Alertmanager for error rate > 1% over 5 minutes.

Answer

Create an uptime check in Cloud Monitoring that checks the application's health endpoint and alerts if it fails for 5 minutes.

Question 4

Your team is deploying a new version of a microservices application on Google Kubernetes Engine (GKE). You want to gradually shift traffic to the new version while monitoring key performance indicators (KPIs) such as error rate and latency. If KPIs degrade, you need to automatically roll back. Which approach should you use?

Accepted Answer

Implement a canary deployment using Istio with Flagger, which automates traffic shifting and rollback based on Prometheus metrics.. Flagger with Istio automates canary deployments by incrementally shifting traffic, analyzing Prometheus metrics, and rolling back automatically if KPIs degrade. This provides safe, gradual rollout with minimal manual intervention. Other options either lack automation, do not support gradual traffic shifting, or require manual monitoring.

Answer

Use GKE rolling updates with maxSurge and maxUnavailable set to 25%, and monitor KPIs manually.

Answer

Configure a GKE Ingress with two backends and use traffic splitting based on weights, then manually adjust weights based on monitoring.

Answer

Use Blue/Green deployment by creating a second deployment and switching the Service selector to the new version after manual testing.

Question 5

A retail company uses a Cloud SQL for MySQL instance with a single zone. The database is critical for order processing, and the company wants to minimize downtime if the zone hosting the instance fails. They also want to ensure that the application can continue to write data during a zonal failure without manual intervention. What should they do?

Accepted Answer

Enable high availability by configuring the instance as regional.. Configuring Cloud SQL as regional provides a synchronous standby in another zone and automatic failover. This ensures that writes can continue with minimal downtime during a zonal failure, satisfying the business requirement. Other options either require manual intervention, result in data loss, or do not provide automatic failover.

Answer

Migrate the database to a Compute Engine instance with a regional persistent disk.

Answer

Create a read replica in another zone and promote it if the primary fails.

Answer

Take regular automated backups and restore to a new instance in another zone.

Question 6

A financial services company runs a critical application on a managed instance group (MIG) of Compute Engine instances. The application must be highly available and able to survive a zone failure without manual intervention. The company wants to ensure that the MIG automatically recovers from zone failures and maintains capacity. They also want to minimize latency for users across the United States. Which configuration should they use?

Accepted Answer

Regional MIG with autoscaling enabled and a global external HTTP(S) load balancer. A regional managed instance group distributes instances across multiple zones, ensuring that a zone failure does not take down the application. Autoscaling maintains capacity. A global external HTTP(S) load balancer uses a single anycast IP and routes traffic to the nearest healthy backend, reducing latency for users across the United States. This combination provides both high availability and low latency.

Answer

Regional MIG with autoscaling enabled and a load balancer with a single backend service

Answer

Regional MIG with autoscaling enabled and an internal TCP/UDP load balancer

Answer

Zonal MIG with autoscaling enabled and a global external HTTP(S) load balancer

Question 7

A startup is deploying a new web application on Google Cloud. They want to use a fully managed, serverless platform that automatically scales and requires no infrastructure management. The application is containerized and listens on HTTP. Which Google Cloud service should they use?

Accepted Answer

Cloud Run. Cloud Run is a fully managed serverless platform that runs containers and automatically scales, including to zero. It requires no infrastructure management, making it ideal for a startup wanting to deploy a containerized web application. Compute Engine and GKE require more management, and App Engine flexible environment is not fully serverless.

Answer

Google Kubernetes Engine (GKE)

Answer

Compute Engine

Answer

App Engine flexible environment

Question 8

A team runs periodic BigQuery queries on a large dataset. They notice high costs due to full table scans. They want to reduce costs and improve query performance. Which two actions should they take? (Choose two options that best fit the scenario.)

Accepted Answer

Partition the table by a date/timestamp column. The correct actions are B (partition the table by a date/timestamp column) and D (cluster the table on frequently filtered columns). Partitioning restricts scans to only the relevant date partitions, and clustering physically sorts data by the filtered columns so BigQuery prunes blocks it doesn't need, both directly cutting bytes scanned and cost. Option A (avoiding SELECT *) is a general best practice but doesn't address full table scans on a large dataset, and option C (materialized views) helps only for recurring aggregate patterns, not the broad scan-cost problem described.

Answer

Use SELECT * only when necessary

Answer

Use materialized views to pre-aggregate data

Question 9

Your company uses Cloud Monitoring to track the performance of a microservices application. The SRE team wants to define an SLO for the latency of a critical API. They need to measure the proportion of requests that complete within 200 ms over a rolling 30-day window. Which approach should they use to implement this SLO?

Accepted Answer

Use Cloud Monitoring's SLO monitoring feature to define a latency SLO with a distribution cut based on a histogram metric.. Cloud Monitoring's SLO monitoring is designed for defining and tracking SLOs. Using a distribution cut on a histogram metric allows precise measurement of the proportion of requests within the latency threshold over a rolling period. It also provides error budget and alerting, which are essential for SRE practices.

Answer

Configure a log-based metric that counts requests with latency under 200 ms, then create an alert if the count drops.

Answer

Set up an uptime check that measures the API response time and alerts if it exceeds 200 ms.

Answer

Create a custom metric that logs each request latency, then use a dashboard to manually calculate the percentage within 200 ms.

Question 10

A healthcare company is designing a new patient-records API on Google Cloud. The API must serve read-heavy traffic globally with low latency, tolerate the failure of an entire region, and keep operational overhead low. The data is stored in Cloud Spanner. Which design should the architect recommend?

Accepted Answer

Deploy a multi-region Cloud Spanner instance and run the API on a global external Application Load Balancer with serverless NEGs pointing to Cloud Run services in multiple regions.. Global external Application Load Balancers route HTTP traffic to the nearest healthy backend across regions and support serverless NEGs for Cloud Run, while multi-region Cloud Spanner provides strongly consistent, automatically replicated data with regional failover. Together they meet the global latency, regional resilience, and low-overhead goals. Regional load balancers, proxy network load balancers, and DNS-based routing each fall short on at least one requirement.

Answer

Deploy a regional Cloud Spanner instance and run the API on Compute Engine managed instance groups in two zones behind a regional external Application Load Balancer.

Answer

Deploy a multi-region Cloud Spanner instance and use Cloud DNS with a geoproximity routing policy that resolves clients to a regional external Application Load Balancer in the closest region.

Answer

Deploy a multi-region Cloud Spanner instance and run the API on Compute Engine VMs in two regions, using a global external proxy Network Load Balancer with a single global backend service.

Question 11

A company wants to ensure that their development teams follow best practices for cost optimization. They want to implement a process that reviews architecture decisions before deployment and provides recommendations. Which Google Cloud tool should they use to get automated cost recommendations for their existing resources?

Accepted Answer

Active Assist. Active Assist is a suite of tools that provides automated recommendations for cost, security, and performance. It analyzes resource usage and suggests optimizations such as right-sizing or deleting idle resources. This directly supports the goal of implementing a process for cost optimization recommendations.

Answer

Cloud Billing reports

Answer

Cloud Asset Inventory

Answer

Cloud Monitoring

Question 12

A company is migrating a legacy application to Google Cloud. The application requires a shared file system that can be accessed by multiple Compute Engine instances simultaneously. The file system must be POSIX-compliant, highly available, and scalable. The company wants to minimize management overhead. Which solution should they use?

Accepted Answer

Filestore. Filestore is a managed NFS file system that provides POSIX-compliant shared storage for Compute Engine instances. It is highly available, scalable, and requires minimal management. Cloud Storage FUSE is not fully POSIX-compliant, Persistent Disk multi-writer is not for shared file systems, and Local SSD is not shared.

Answer

Cloud Storage with a Cloud Storage FUSE mount

Answer

Persistent Disk with multi-writer mode

Answer

Local SSD

Question 13

A company is designing a VPC architecture for a multi-tenant SaaS platform. Each tenant has isolated workloads that must not communicate with each other. They also need centralized network security and logging. Which VPC design meets these requirements?

Accepted Answer

Use a Shared VPC with separate subnets for each tenant and firewall rules to enforce isolation. Option B is correct because a Shared VPC in Google Cloud lets a host project centrally own and manage the VPC network, subnets, firewall rules, and logging while each tenant's service project gets its own subnet; firewall rules scoped to those subnets or service accounts enforce isolation so tenant workloads cannot communicate with each other. This design also satisfies the centralized network security and logging requirement, since the host project retains control of firewall policies and VPC Flow Logs across all tenant subnets. Option A does not provide tenant isolation or centralized logging, as Cloud VPN only establishes encrypted tunnels to on-premises or remote networks. Option C is unsuitable because a single VPC with network tags and IAP tunnels does not create hard tenant boundaries and IAP is for identity-based TCP access, not tenant segmentation. Option D is wrong because VPC peering connects networks rather than isolating tenants, and Cloud NAT only provides outbound internet access, not centralized security or logging.

Answer

Dedicated Cloud VPN connections per tenant

Answer

Single VPC with network tags and IAP tunnels

Answer

Peered VPCs for each tenant with Cloud NAT

Question 14

A financial services company stores regulated data in BigQuery datasets. Auditors require that all data access be logged with the identity of the user, the query text, and the timestamp, and that logs be retained for 365 days and be immutable. The security team wants to use Google Cloud-native tools with minimal operational overhead. What should they implement?

Accepted Answer

Enable BigQuery Data Access audit logs in Cloud Audit Logs, then create a log sink to a Cloud Storage bucket with a 365-day retention policy and a Bucket Lock.. BigQuery Data Access audit logs provide the required identity, query text, and timestamp for every data access. Routing them through a log sink to a Cloud Storage bucket with a retention policy and Bucket Lock ensures immutability for 365 days. This combination uses native Google Cloud services and requires no custom code or third-party tooling, minimizing operational overhead.

Answer

Enable BigQuery Data Access audit logs and configure a log sink to a BigQuery dataset with a 365-day partition expiration and table-level IAM restrictions.

Answer

Use BigQuery's INFORMATION_SCHEMA.JOBS_BY_PROJECT view to query historical job metadata, and export results to Cloud Storage on a daily schedule via a Cloud Scheduler job.

Answer

Enable VPC Service Controls for BigQuery and configure access levels that log all API calls to Cloud Logging with a 365-day retention period.

Question 15

A company is deploying a microservices application on Google Kubernetes Engine (GKE). The architect needs to ensure that the cluster can automatically scale nodes based on pod resource requests and that pods are scheduled efficiently across nodes. The company also wants to minimize costs by scaling down when demand is low. Which two configurations should the architect implement? (Choose two.)

Accepted Answer

Enable Cluster Autoscaler on the node pool with a minimum and maximum node count.. Cluster Autoscaler scales the number of nodes in a node pool based on pending pod resource requests, and setting pod resource requests ensures that the scheduler and autoscaler have accurate information to make scaling decisions. Together, they enable automatic node scaling and efficient scheduling while allowing scale-down to reduce costs. The other options either address pod scaling, add unnecessary complexity, or improve availability without meeting the core requirements.

Answer

Configure Horizontal Pod Autoscaler (HPA) based on CPU utilization.

Answer

Use a regional cluster with multiple zones.

Answer

Enable node auto-provisioning for the cluster.