Google PCA Analyze and optimize technical and business processes — 10 Questions

Question 1

A startup uses Cloud Functions with a Pub/Sub trigger to process incoming orders. They notice that the function sometimes fails to process messages, and those messages are lost. What is the most likely cause?

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

Accepted Answer

The Cloud Function is configured with retry on failure set to false.. When a Cloud Function fails to process a Pub/Sub message and retry on failure is set to false, the message is not redelivered. Pub/Sub relies on the subscriber (the Cloud Function) to acknowledge messages; without retries, a failed execution causes the message to be dropped after the ack deadline expires, leading to message loss.

Answer

The subscription has an ackDeadlineSeconds of 600.

Answer

The Cloud Function has a timeout of 540 seconds.

Answer

The Pub/Sub topic has a retention duration of 10 minutes.

Question 2

A company wants to reduce costs for a Cloud Storage bucket that stores infrequently accessed archival data. The data is accessed roughly once a quarter. Which storage class should they use?

Accepted Answer

Coldline storage class.. The Coldline storage class is designed for data accessed less than once a quarter, making it the most cost-effective choice for data accessed roughly once a quarter. It offers lower storage costs than Standard or Nearline, with retrieval fees and a 90-day minimum storage duration that suits quarterly access patterns.

Answer

Archive storage class.

Answer

Nearline storage class.

Answer

Standard storage class.

Question 3

A company is designing a disaster recovery plan for a critical application running on Compute Engine with a regional persistent disk. They want to minimize recovery time objective (RTO) and recovery point objective (RPO). Which TWO strategies should they implement? (Choose two.)

Accepted Answer

Use snapshot replication to a secondary region.. Option A is correct because replicating snapshots to a secondary region ensures that a recent, consistent copy of the regional persistent disk data exists outside the primary region, enabling fast recovery with a low RPO and RTO if the primary region fails. Option E is correct because creating a custom image of the boot disk and copying it to another region allows rapid instance recreation in the secondary region, reducing RTO by avoiding OS and application reinstallation. Option B is wrong because manual snapshots taken only after a failure cannot meet low RPO, since data written since the last snapshot would be lost. Option C is wrong because an instance template in the same region does not provide cross-region resilience and would be unavailable if the region fails. Option D is wrong because Cloud Storage backups with a lifecycle policy are typically for archival or long-term retention and do not by themselves deliver the low RTO/RPO required for a critical regional persistent disk workload.

Answer

Take manual snapshots after a failure occurs.

Answer

Create an instance template in the same region.

Answer

Store backups in Cloud Storage with a lifecycle policy.

Question 4

A company is using Cloud Bigtable for time-series data from IoT devices. They are experiencing high latency for queries that scan a large range of rows. Which THREE actions can improve query performance? (Choose three.)

Accepted Answer

Reduce the size of row keys.. Option A is correct because Bigtable sorts data lexicographically by row key, so shorter row keys reduce the amount of data read and compared per row, lowering scan latency across a large range. Option B is correct because adding nodes increases the cluster's read throughput and CPU capacity, which directly reduces latency for large scans that are throughput-bound. Option E is correct because when a table is replicated across clusters, application profiles with single-cluster routing prevent the client from reading across multiple clusters, avoiding cross-cluster latency and keeping reads local to one fast cluster. Option C is not a performance-improving action by itself; Key Visualizer is a diagnostic tool that identifies hot spots and access patterns but does not directly reduce query latency. Option D is incorrect because HDD storage has higher latency than SSD, so switching from SSD to HDD would worsen query performance rather than improve it.

Answer

Use Key Visualizer to analyze access patterns.

Answer

Switch from SSD storage to HDD storage.

Question 5

A developer ran the command `gcloud compute instances describe instance-1 --zone us-central1-a` and received the above output. They want to create another instance with the same configuration, except with a different external IP. Which action should they take?

Accepted Answer

Create a new instance without specifying a static IP, so it receives an ephemeral IP.. The `gcloud compute instances describe` output shows the instance has an external IP that is ephemeral (not reserved). To create a new instance with the same configuration but a different external IP, the simplest approach is to create a new instance without specifying a static IP, which will automatically assign a new ephemeral IP. This avoids the overhead of reserving and managing a static IP when only a temporary, different address is needed.

Answer

Reserve a new static external IP address and assign it to the new instance.

Answer

Use the same static IP address by releasing and reassigning it.

Answer

None of the above.

Question 6

A developer is deploying a containerized application to Cloud Run. The deployment fails with the error above. What is the most likely cause?

Accepted Answer

The container is listening on port 3000 instead of 8080.. Cloud Run requires containers to listen on the port defined by the `PORT` environment variable, which defaults to 8080. If the container is hardcoded to listen on port 3000, Cloud Run's health checks and routing will fail because the runtime cannot reach the application on the expected port, causing the deployment to fail.

Answer

The container health check is misconfigured.

Answer

The container startup script fails.

Answer

The container does not have a web server.

Question 7

A company wants to optimize their cloud spending on Google Cloud. They have a mix of workloads including batch processing, real-time analytics, and web serving. Which TWO strategies should they implement to reduce costs without significant architectural changes? (Choose two.)

Accepted Answer

Use preemptible VMs for batch processing jobs that are fault-tolerant.. Option B is correct because preemptible VMs (now also Spot VMs) offer up to 60-91% discounts versus standard on-demand pricing and are ideal for fault-tolerant batch processing workloads that can tolerate sudden termination, matching the scenario's batch processing requirement without architectural changes. Option C is correct because committed use discounts (CUDs) provide substantial discounts (up to 57% for 1-year and 70% for 3-year commitments) in exchange for committing to a minimum level of resource usage, which suits stable, predictable workloads like the company's ongoing web serving and analytics. Option A is incorrect because sustained use discounts are automatically applied to instances running for a significant portion of the billing month, not to short-lived instances, so the premise is technically wrong. Option D, while a valid cost optimization practice, is not one of the two marked correct answers here and involves ongoing operational effort rather than the specific discount mechanisms the question targets. Option E is incorrect because migrating web serving to Cloud Functions would require significant architectural changes, contradicting the 'without significant architectural changes' constraint.

Answer

Use sustained use discounts for short-lived instances.

Answer

Right-size all Compute Engine instances by analyzing utilization metrics.

Answer

Migrate all web serving workloads to Cloud Functions to benefit from pay-per-use pricing.

Question 8

You are a cloud architect for an e-commerce company. Their application runs on Google Kubernetes Engine (GKE) with a Regional cluster. The application consists of a frontend service, a backend service, and a Redis cache. Traffic is routed via an external HTTP(S) Load Balancer to the frontend. Recently, customers have reported intermittent 502 Bad Gateway errors during peak hours. The frontend logs show 'upstream connect error or disconnect/reset before headers. retried and limit reset' errors. The backend service is deployed with 3 replicas, each with resource requests of 1 CPU and 2 GB memory. The cluster autoscaler is enabled with a minimum of 3 nodes and a maximum of 10 nodes, using e2-standard-4 instances. The backend service's HPA is configured with CPU utilization target of 80%. During peak hours, CPU utilization on the backend pods reaches 90%, but the HPA does not scale up. The cluster has sufficient node capacity. What should you do to resolve the issue?

Accepted Answer

Lower the HPA CPU target to 60% and increase the number of replicas min to 5.. The HPA is configured with a CPU utilization target of 80%, but during peak hours, CPU utilization reaches 90% without triggering scale-up. This indicates that the HPA's target utilization is too high relative to the actual load, causing the HPA to not scale because the average CPU utilization across pods may still be below the target when considering the metric calculation. Lowering the HPA CPU target to 60% ensures that the HPA triggers scaling earlier, and increasing the minimum replicas to 5 provides a baseline capacity to absorb traffic spikes, preventing the upstream connect errors from the backend being overwhelmed.

Answer

Change the HPA to use memory utilization instead of CPU.

Answer

Increase the backend service's max connections per pod in the backendConfig.

Answer

Increase the maximum number of nodes in the cluster autoscaler to 20.

Question 9

A company is using Cloud NAT to allow instances in a private subnet to access the internet for updates. The security team wants to audit outbound connections. Which TWO steps should be taken to enable flow logs for Cloud NAT?

Accepted Answer

Configure a log sink to export Cloud NAT logs to BigQuery. Cloud NAT flow logs provide detailed records of outbound connections and are enabled directly on the Cloud NAT gateway itself. Option B is correct because configuring a log sink to export Cloud NAT logs to BigQuery is a valid step to audit outbound connections, but the primary step to enable logging is to update the existing Cloud NAT gateway to enable flow logs (Option E). Together, these two steps (B and E) allow you to capture and analyze outbound traffic for auditing.

Answer

Enable private Google access on the subnet

Answer

Enable VPC Flow Logs on the subnet

Answer

Create a new Cloud NAT gateway with logging enabled

Question 10

A team deployed the Terraform configuration shown in the exhibit. They observe that Cloud NAT is not translating traffic from the private subnet as expected. What is the most likely cause?

Accepted Answer

The Cloud Router is not in the same VPC network as the private subnet. Cloud NAT requires a Cloud Router to be in the same VPC network as the subnet whose traffic needs translation. If the Cloud Router is in a different VPC network, the NAT gateway cannot establish the necessary BGP sessions or route traffic from the private subnet, causing NAT to fail silently.

Answer

The log filter is set to ERRORS_ONLY, which suppresses all logs

Answer

The NAT IP allocation is manual and no IPs were specified

Answer

The subnet is not included in the source_subnetwork_ip_ranges_to_nat list