PCDOE Practice Test 35 — 15 Questions

Question 1

A company uses Cloud SQL for their transactional database. They are experiencing slow read performance. Which THREE actions can improve read throughput? (Choose three.)

Accepted Answer

Add a read replica. Adding a read replica offloads read queries from the primary Cloud SQL instance, distributing the read workload and improving read throughput. This is a common pattern for scaling read-heavy workloads in Cloud SQL, as replicas serve read traffic asynchronously without impacting the primary instance's write performance.

Answer

Enable query caching

Answer

Use Cloud SQL Proxy for connections

Question 2

A team is using Cloud Build to build a Docker image and push to Artifact Registry. After each build, they want to automatically trigger a deployment to Cloud Run. What is the best way to achieve this?

Accepted Answer

Configure a Cloud Run trigger on Artifact Registry push.. Cloud Run natively supports continuous deployment from Artifact Registry: when a new image is pushed to the registry, Cloud Run can automatically deploy the latest image without requiring an external pipeline or scheduler. This is the simplest and most direct approach, as it eliminates the need for additional CI/CD orchestration while ensuring deployments happen immediately after each successful build.

Answer

Use Cloud Build builder to deploy to Cloud Run in the same pipeline.

Answer

Use Cloud Deploy to manage the rollout.

Answer

Use Cloud Scheduler to periodically check for new images and deploy.

Question 3

Refer to the exhibit. A DevOps engineer tries to create a project but gets this error. What is the most likely cause?

Accepted Answer

The organization has an organizational policy that restricts project creation.. The error message indicates that project creation is blocked by an organizational policy. In Google Cloud, organization policies (e.g., constraints/compute.restrictNonCcmlProjects) can be set at the organization or folder level to restrict project creation. This is a common control for governance and cost management, and it overrides individual user permissions.

Answer

The project ID already exists.

Answer

The user's billing account is not linked.

Answer

The user does not have the Project Creator role.

Question 4

An organization wants to enforce that all Compute Engine VMs use only specific machine families (e.g., N2, C2). Which mechanism should they use?

Accepted Answer

Organization policy with compute.restrictComputeEngineMachineTypes. Organization policies in Google Cloud allow administrators to enforce constraints on resources across the entire hierarchy. The `compute.restrictComputeEngineMachineTypes` constraint specifically limits which machine families (e.g., N2, C2) can be used when creating Compute Engine VMs, making it the correct mechanism for this requirement.

Answer

IAM deny policies

Answer

Quota management

Answer

Folders with different owners

Question 5

Your company runs a web application on Compute Engine behind a global HTTP(S) Load Balancer. You want to improve performance for users in Europe. You have already enabled Cloud CDN. What is the next best action to reduce latency?

Accepted Answer

Add Compute Engine instances in a European region (e.g., europe-west1) and add them to the load balancer's backend.. Adding Compute Engine instances in a European region (e.g., europe-west1) and adding them to the load balancer's backend reduces latency by bringing the origin server physically closer to European users. Even with Cloud CDN enabled, cache misses still require a round trip to the backend; having a backend in Europe minimizes that distance. The global HTTP(S) Load Balancer automatically routes requests to the closest healthy backend, so this directly improves performance for users in Europe.

Answer

Switch to a regional load balancer to route traffic more efficiently.

Answer

Configure a multi-regional Cloud CDN and enable cache warming for popular content.

Answer

Increase the machine type of existing instances to improve processing speed.

Question 6

Your organization runs a critical e-commerce platform on Google Kubernetes Engine (GKE). The platform uses Cloud Service Mesh (Anthos Service Mesh) for traffic management and Cloud Monitoring for observability. Recently, after a new release, you observe that the p99 latency of the checkout service has increased from 200ms to 2s. The service's CPU and memory metrics appear normal, and there are no error logs. The release included a change to the Istio VirtualService configuration that added a retry policy: 3 retries with a 500ms timeout per retry. You suspect that the retries are contributing to the latency increase. You want to use Cloud Monitoring to confirm this hypothesis. Which approach should you take?

Accepted Answer

Use Metrics Explorer to query the istio.io/service/server/request_count metric, filtered by response_code_class and destination_service, and include the istio.io/service/server/request_retries metric to see retry counts alongside latency. It directly correlates retry attempts with latency by querying the `istio.io/service/server/request_retries` metric alongside the `istio.io/service/server/request_count` metric in Metrics Explorer. This allows you to visualize the retry count per destination service (checkout) and compare it with the p99 latency increase, confirming whether the retry policy is causing the observed latency spike. The retry policy (3 retries with 500ms timeout) can add up to 1.5s of additional latency per request, which aligns with the increase from 200ms to 2s.

Answer

Use Cloud Trace to analyze distributed traces for the checkout service and look for retry spans

Answer

Check the 'Services' dashboard in Cloud Monitoring, which shows a pre-built latency chart for all services

Answer

Use Logs Explorer to search for logs containing 'retry' in the checkout service namespace

Question 7

A backend service receives bursts of requests that cause timeouts. The team wants to smooth out the load while ensuring all requests are processed eventually. Which strategy should they use?

Accepted Answer

Use Cloud Tasks to queue incoming requests and process at a controlled rate. Cloud Tasks is designed to decouple request processing by queuing incoming requests and then dispatching them to a target handler at a controlled rate. This allows the backend to process requests smoothly, preventing timeouts during bursts, while ensuring every request is eventually processed through retry and dead-letter mechanisms.

Answer

Implement client-side rate limiting

Answer

Use Cloud Load Balancing with connection draining

Answer

Increase the number of backend instances

Question 8

Refer to the exhibit. The output shows three folders created directly under the organization node. Which gcloud command was most likely executed to produce this output?

Accepted Answer

gcloud resource-manager folders list --organization=123456789012. The `gcloud resource-manager folders list --organization=123456789012` command lists all folders directly under the specified organization node. The output shows three folders (e.g., folder1, folder2, folder3) at the top level, which matches the behavior of listing folders with the organization ID as the parent. This command is specifically designed to retrieve immediate child folders of an organization, not nested folders.

Answer

gcloud organizations list

Answer

gcloud projects list --filter='parent.id:123456789012'

Answer

gcloud resource-manager folders list --folder=123456789012

Question 9

Refer to the exhibit. You see this log entry from a Cloud Run service. The stack trace shows the error occurs in handler.js at line 50. You want to see the state of variables at that point in the production environment without adding logging or redeploying. What should you do?

Accepted Answer

Use Cloud Debugger to set a snapshot location at line 50 in handler.js.. Cloud Debugger allows you to inspect the state of an application, including local variables and call stack, at a specific line of code in a production environment without modifying or redeploying the application. By setting a snapshot at line 50 in handler.js, you can capture the variable values at the exact point where the error occurs, which directly addresses the need to debug without adding logging or redeploying.

Answer

Use Error Reporting to view similar errors.

Answer

Use Cloud Profiler to capture a heap snapshot.

Answer

Use Cloud Trace to trace the request.

Question 10

A team defines an SLO of 99.9% availability over a 30-day window. They use a multi-window, multi-burn-rate alerting approach. Which alerting condition should trigger a page based on fast burn rate?

Accepted Answer

2% error budget consumed in 10 minutes.. A multi-window, multi-burn-rate alerting approach uses a short window (e.g., 10 minutes) to detect fast burn rates that could rapidly exhaust the error budget. Consuming 2% of the error budget in 10 minutes corresponds to an annualized burn rate of over 1000x, which is dangerously fast and requires immediate paging to prevent a breach of the 99.9% SLO over the 30-day window.

Answer

1% error budget consumed in 1 hour.

Answer

10% error budget consumed in 1 hour.

Answer

5% error budget consumed in 6 hours.

Question 11

Which storage class provides the lowest cost for data accessed less than once a year?

Accepted Answer

Archive. Archive storage class is the correct answer because it is specifically designed for long-term data retention where access is extremely infrequent, such as less than once a year. It offers the lowest storage cost among Google Cloud Storage classes, but with higher retrieval costs and a minimum storage duration of 365 days, making it ideal for data that is rarely accessed.

Answer

Nearline

Answer

Standard

Answer

Coldline

Question 12

A team is running a stateful application on Compute Engine VMs. They notice that the application performance degrades over time as the disk fills up. They want to proactively alert before performance degrades. Which metric should they monitor?

Accepted Answer

Disk usage percentage. Disk usage percentage is the correct metric because the application performance degrades as the disk fills up, which is a capacity issue. Monitoring disk usage percentage allows the team to set an alert threshold (e.g., 80% or 90%) to proactively take action (e.g., clean up logs or resize disks) before the disk becomes full and causes performance degradation. This directly addresses the root cause described in the scenario.

Answer

Disk read/write latency

Answer

Network sent bytes

Answer

CPU utilization

Question 13

A team notices that the 'cpu-high' alert fires frequently even for short bursts. The 'disk-full' alert never sends notifications. Based on the exhibit, what is the issue with each?

Accepted Answer

The cpu-high alert duration is too short; the disk-full alert has no notification channel.. The 'cpu-high' alert fires frequently for short bursts due to its duration being set too short, causing it to trigger on transient spikes. The 'disk-full' alert never sends notifications because it lacks a configured notification channel, so even when the condition is met, no alert is dispatched.

Answer

The cpu-high uses email which is unreliable; the disk-full condition is too low.

Answer

Both alerts have misconfigured durations.

Answer

The cpu-high threshold is too high; the disk-full duration is too long.

Question 14

Which TWO are benefits of using Cloud Build private pools?

Accepted Answer

Dedicated VMs for builds. Cloud Build private pools provide dedicated VMs that are not shared with other Google Cloud projects. This isolation ensures consistent performance and eliminates the 'noisy neighbor' effect that can occur in public pools, where build resources are shared across multiple tenants.

Answer

Lower cost

Answer

No internet access

Answer

Faster builds compared to public pools

Question 15

After a recent deployment, the mean latency of a user-facing service increased from 200ms to 500ms. The engineer uses Cloud Trace to analyze traces. Which trace characteristic should the engineer focus on to identify the bottleneck?

Accepted Answer

Distribution of span latencies across services.. The engineer should focus on the distribution of span latencies across services (Option B) because Cloud Trace captures the latency of each span in a distributed trace. By examining the histogram or distribution of span latencies, the engineer can identify which specific service or component is contributing the most to the overall increase from 200ms to 500ms, pinpointing the bottleneck. This approach aligns with the principle of distributed tracing, where the critical path is determined by the slowest span in the trace.

Answer

Timestamps of the trace ID.

Answer

Error count per span.

Answer

Total number of spans in the trace.