PCD Timed Practice Test 2 — 10 Questions

Question 1

A company is using Cloud Monitoring to track custom metrics published from an on-premises application using the Monitoring API. The metrics are published every 30 seconds. The team wants to create an alert that fires if the metric goes below a threshold for more than 1 minute. Which alert condition type should they use?

10 minute time limit — choose an answer to begin.

Accepted Answer

Metric type: custom.googleapis.com, condition: metric threshold (below value), duration: 60s. The requirement is to fire an alert when the metric value goes below a threshold for more than 1 minute. The 'metric threshold (below value)' condition type directly monitors a metric against a lower bound and evaluates the condition over the specified duration (60s) before triggering. This aligns with the need to detect sustained low values, not just a single data point.

Answer

Metric type: custom.googleapis.com, condition: metric lower bound, duration: 60s

Answer

Metric type: custom.googleapis.com, condition: metric change, duration: 60s

Answer

Metric type: custom.googleapis.com, condition: metric absence, duration: 60s

Question 2

A Cloud Spanner query that uses a secondary index is taking longer than expected. The index includes a large payload column. How can the query performance be improved?

Accepted Answer

Add the payload column to the index using the STORING clause. In Cloud Spanner, a secondary index that includes a large payload column can cause the query to do a back-join to the base table to fetch that column, adding latency. Adding the payload column to the index using the STORING clause makes the index covering, so the query can be satisfied entirely from the index without touching the base table. This eliminates the back-join and improves performance.

Answer

Use a composite key instead of an index

Answer

Change the index to a global index

Answer

Remove the index and use a full table scan

Question 3

Your Cloud Run service is experiencing 5xx errors. You have enabled Cloud Logging and Cloud Error Reporting. How can you quickly identify the most common error type?

Accepted Answer

Open Cloud Error Reporting to see grouped error counts.. Cloud Error Reporting automatically groups similar errors (e.g., same stack trace or error message) and shows a count for each group, making it the fastest way to identify the most common 5xx error type without manual log inspection. It is purpose-built for this exact use case, aggregating errors from Cloud Logging and presenting them in a dashboard sorted by frequency.

Answer

Use Cloud Trace to analyze the traces of failing requests.

Answer

View the logs in Cloud Logging and manually count error messages.

Answer

Create a Cloud Monitoring alert on 5xx response codes.

Question 4

An engineer is deploying AlloyDB for PostgreSQL and needs to support read scaling with automatic scaling of read replicas based on load. They also want to ensure minimal operational overhead. What should they use?

Accepted Answer

Create a read pool instance with autoscaling enabled.. AlloyDB read pool instances are designed specifically for horizontal read scaling. When autoscaling is enabled, AlloyDB automatically adds or removes read replicas in the pool based on CPU utilization and other load metrics, eliminating manual capacity management. This directly satisfies both the read-scaling and minimal-operational-overhead requirements.

Answer

Manually create additional read replicas and set up a load balancer.

Answer

Create multiple cross-region replicas.

Answer

Use AlloyDB Omni to deploy replicas on-premises.

Question 5

A company runs a Java microservice on GKE that processes financial transactions. The service is critical and must meet a 99.9% availability SLO. They have set up Cloud Monitoring alerting policies based on request latency and error rate. Recently, the team noticed that the alerting policy for high latency fires too frequently with false positives, causing alert fatigue. They want to reduce false positives without compromising real issues. The latency metric is collected from the application's custom metric via Prometheus. Which approach should they take?

Accepted Answer

Increase the alert duration to require sustained latency over a longer period.. Increasing the alert duration requires the high latency to be sustained over a longer period, which filters out transient spikes that cause false positives. This approach preserves the ability to detect genuine, prolonged performance degradation that could impact the 99.9% availability SLO, without raising the threshold and risking missed real issues.

Answer

Change the metric to use median instead of average.

Answer

Increase the alert threshold to a higher latency value.

Answer

Disable the alert and rely on manual checks.

Question 6

A team is designing a disaster recovery plan for a critical application on Google Cloud. The application runs on Compute Engine with a regional persistent disk. They want to minimize data loss in case of a regional outage. Which strategy should they use?

Accepted Answer

Use persistent disk snapshot replication to another region. Persistent disk snapshot replication to another region is the correct strategy because snapshots are stored in Cloud Storage and can be replicated across regions. This allows you to restore the disk from a snapshot in a different region if the primary region experiences an outage, minimizing data loss by ensuring the backup is geographically separate. Regional persistent disks are synchronous within a region but do not provide cross-region replication, so snapshots are the recommended approach for cross-region disaster recovery.

Answer

Create a snapshot schedule and store snapshots in the same region

Answer

Use synchronous replication across regions

Answer

Configure a managed instance group with autohealing

Question 7

You need to migrate an on-premises MySQL 5.7 database (2 TB) to Cloud SQL for MySQL with minimal downtime. Database Migration Service (DMS) is chosen. What is the correct sequence of steps to ensure a successful continuous migration?

Accepted Answer

Set up a connection profile for the source, create a DMS migration job (full dump + CDC), monitor the initial dump, then promote the replica to complete migration.. DMS continuous migration first performs a full dump (initial snapshot), then switches to CDC to replicate ongoing changes. After the initial dump, you validate the replica and promote it to make it the primary. The correct order: create connection profile for source, create migration job with full dump + CDC, monitor initial dump, then promote when ready.

Answer

Use mysqldump to export the database, import to Cloud SQL, then set up DMS for CDC only.

Answer

Create a DMS continuous migration job directly without a connection profile.

Answer

First promote the Cloud SQL replica, then create the connection profile.

Question 8

A developer wants to automatically deploy a new version of an application to App Engine Standard every time code is pushed to the main branch of a Cloud Source Repositories repository. Which service should be used?

Accepted Answer

Cloud Build. Cloud Build is the correct service because it is a fully managed CI/CD platform that integrates natively with Cloud Source Repositories and App Engine Standard. You can configure a Cloud Build trigger to automatically build and deploy your application whenever code is pushed to the main branch, using a cloudbuild.yaml file that specifies the build steps and the `gcloud app deploy` command.

Answer

Cloud Run

Answer

Cloud Scheduler

Answer

Cloud Deploy

Question 9

An operations team has set up a Cloud Monitoring alerting policy that fires when the 99th percentile latency of a service exceeds 200ms for 1 minute. They notice that the alert fires frequently during normal traffic patterns. What is the most likely issue with the alert configuration?

Accepted Answer

The alerting policy uses a rolling window that is too short for the metric's natural variation.. The alert fires frequently during normal traffic because the 1-minute rolling window is too short to smooth out natural latency spikes. A short window captures transient variations as if they were sustained, causing false positives. Lengthening the window (e.g., to 5 minutes) would reduce noise and better reflect true performance trends.

Answer

The metric's alignment period is set to align by rate instead of mean.

Answer

The service is actually experiencing high latency, and the threshold should be lowered.

Answer

The alerting policy is using a forecast threshold instead of a metric threshold.

Question 10

A startup is developing a new web application that will be deployed on Google Cloud. They expect the application to have unpredictable traffic patterns, with periods of no traffic followed by sudden spikes. The development team wants to minimize operational overhead and only pay for resources when the application is handling requests. They also need the application to scale automatically to handle the spikes. Which Google Cloud service should they use for the application's frontend?

Accepted Answer

Cloud Run. Cloud Run is a fully managed serverless compute platform that automatically scales instances based on incoming requests, including scaling to zero when there is no traffic. This means the startup only pays for the resources consumed during request handling, aligning with cost efficiency. It also removes the need to manage servers or clusters, minimizing operational overhead. Thus, Cloud Run is the best fit for unpredictable traffic patterns.

Answer

Google Kubernetes Engine (GKE) Autopilot cluster

Answer

App Engine standard environment

Answer

Compute Engine managed instance group with autoscaling