PCDOE Practice Test 5 — 10 Questions

Question 1

Which THREE steps are typically part of a formal incident postmortem according to Google SRE best practices?

Accepted Answer

Assign action items with deadlines.. Option B is correct because a formal postmortem must produce concrete, owned action items with deadlines so that follow-up work is tracked and completed rather than left as vague intentions. Option C is correct because reconstructing a precise incident timeline — detection, escalation, mitigation, and resolution times — is a foundational step that lets the team reason about what happened and where response gaps existed. Option E is correct because Google SRE postmortems focus on identifying contributing factors and root causes in a blameless manner, examining the technical and organizational conditions that allowed the failure. Option A does not belong because postmortems are explicitly blameless and do not seek to name or blame an individual. Option D does not belong because immediate remediation is part of incident response and mitigation, not the postmortem, which occurs after the incident is resolved to analyze and learn from it.

Answer

Identify the person responsible for the incident.

Answer

Implement a solution immediately.

Question 2

A DevOps engineer notices that a Cloud Build trigger is not firing when commits are pushed to a Cloud Source Repositories repository. The trigger is configured with an invert regex for the branch filter. What could be the issue?

Accepted Answer

The branch name matches the exclude pattern; the trigger ignores matching branches.. When a Cloud Build trigger is configured with an invert regex for the branch filter, it means the trigger will fire only for branches that do NOT match the specified regex pattern. If the branch name matches the exclude pattern, the trigger ignores commits on that branch, which is why the trigger is not firing. This is the intended behavior of the invert_regex flag in Cloud Build triggers.

Answer

The repository is in a different region.

Answer

The commit was made by a service account.

Answer

The trigger's service account lacks read access to the repository.

Question 3

A DevOps team wants to implement a CI/CD pipeline for a microservices application deployed on Google Kubernetes Engine (GKE). They need to ensure that each service is built, tested, and deployed independently with minimal manual intervention. Which TWO practices should they implement?

Accepted Answer

Use Cloud Deploy to manage progressive delivery (e.g., canary, blue/green) to GKE clusters.. Option A is correct because Cloud Deploy is Google Cloud's managed continuous delivery service that natively supports progressive delivery strategies such as canary and blue/green deployments to GKE clusters, enabling each microservice to be released independently with automated rollout and rollback controls. Option D is correct because Cloud Build triggers can be configured (e.g., via branch or tag patterns, or included/excluded files) to fire on pull requests and run per-service build and test steps, giving each microservice its own independent CI workflow with minimal manual intervention. Option B is not required for this scenario: Cloud Source Repositories is a Git hosting option, but the question focuses on build/test/deploy independence, and Cloud Build triggers work with GitHub, Bitbucket, or GitLab as well, so it is not one of the two best practices. Option C is wrong because a monolithic repository with simultaneous deployment of all services directly contradicts the requirement for independent build, test, and deployment of each microservice. Option E is wrong because a single shared Cloud Build configuration with conditional steps couples all services into one pipeline, reducing independence and increasing the blast radius of changes rather than giving each service its own build and test flow.

Answer

Use Cloud Source Repositories integrated with Cloud Build for version control and triggering builds.

Answer

Use a monolithic repository and deploy all services simultaneously to ensure consistency.

Answer

Use a single Cloud Build configuration file for all services with conditional steps to handle different services.

Question 4

During a Cloud Build execution, a step fails due to timeout. What is the first thing to check?

Accepted Answer

Check the build logs for errors. When a Cloud Build step fails due to a timeout, the build logs are the first and most authoritative source of diagnostic information. They contain the exact error messages, exit codes, and step output that reveal why the step exceeded its timeout — for example, a hanging command, a missing dependency, or a resource contention issue. Checking logs before making any configuration changes ensures you address the root cause rather than treating symptoms.

Answer

Check network connectivity

Answer

Increase machine type for the build

Answer

Increase the timeout in cloudbuild.yaml

Question 5

Which service is commonly used for time-series data and real-time analytics?

Accepted Answer

Bigtable. Bigtable is a fully managed, scalable NoSQL database optimized for large analytical and operational workloads, including time-series data and real-time analytics. It provides sub-10ms latency for high-throughput reads and writes, making it ideal for IoT, monitoring, and financial data streams. Its column-oriented storage and automatic sharding support efficient time-based queries and aggregation.

Answer

Cloud SQL

Answer

Firestore

Answer

Cloud Spanner

Question 6

Your team wants to create a dashboard that shows request latency broken down by API version. Which approach is most efficient?

Accepted Answer

Use Cloud Monitoring Metrics Explorer to query the latency metric, group by API version, and save the chart as a dashboard. Cloud Monitoring Metrics Explorer allows you to directly query the latency metric (e.g., `request_latencies`) and group by the `version` label, then save the resulting chart as a dashboard widget. This is the most efficient approach because it requires no data export, no custom code, and no additional services — the metric is already available in Cloud Monitoring if your API is instrumented with the appropriate label.

Answer

Write a custom application to output metrics to a file and send to Cloud Monitoring

Answer

Export Cloud Logging logs to BigQuery and create a dashboard in Data Studio

Answer

Enable Cloud Trace and create a dashboard based on trace data

Question 7

You want to send alerts to a Slack channel when a critical error occurs. What should you do?

Accepted Answer

Configure a Slack webhook notification channel in Cloud Monitoring and associate it with an alerting policy. Cloud Monitoring alerting policies can directly send notifications to Slack via a configured webhook notification channel. When a critical error triggers the alerting policy, Cloud Monitoring sends an HTTP POST request to the Slack webhook URL, delivering the alert message to the specified Slack channel. This is the native, event-driven approach without requiring custom code or intermediate services.

Answer

Set up a webhook in Cloud Logging and point it to Slack

Answer

Use Cloud Tasks to schedule a job that queries logs and sends Slack messages

Answer

Create a Cloud Logging export to Pub/Sub and subscribe using a Cloud Function that sends to Slack

Question 8

An e-commerce platform uses Cloud Load Balancing with backend services running on Compute Engine managed instance groups. During Black Friday sales, the application experiences high latency and some 503 errors. The team uses autoscaling based on average CPU utilization, but scaling is too slow—Cloud Monitoring shows CPU rises to 90% before new instances are added. The team needs to reduce latency and eliminate 503 errors. What should they do?

Accepted Answer

Change the autoscaling metric to 'requests per second' and set a lower target value. Switching the autoscaling metric from average CPU utilization to 'requests per second' (RPS) with a lower target value allows the autoscaler to react more quickly to traffic spikes. CPU utilization is a lagging indicator that rises only after requests have already been queued and processed, whereas RPS directly reflects incoming load. By setting a lower target RPS, the autoscaler can add instances before the backend becomes saturated, reducing latency and eliminating 503 errors.

Answer

Use HTTP load balancing with a larger backend timeout

Answer

Enable Cloud CDN for all dynamic content

Answer

Increase the cooldown period for the autoscaling policy

Question 9

An engineer receives an alert that a service's error rate has exceeded the threshold. To investigate, which log-based metric should the engineer query in Cloud Logging to identify the root cause?

Accepted Answer

Error log count grouped by service name.. Error log count grouped by service name directly surfaces which specific service is generating the elevated error rate. In Cloud Logging, log-based metrics are user-defined counters extracted from log entries; querying the error log count per service isolates the offending component, enabling root cause identification without mixing in unrelated performance data.

Answer

Request latency histogram.

Answer

CPU utilization of the service instances.

Answer

Network bytes sent per instance.

Question 10

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