PCD Quick Quiz — 10 Questions

Question 1

Refer to the exhibit. A team is using Cloud Monitoring with MQL to alert on CPU utilization per zone. They notice that the alert fires even when no single instance in a zone has CPU>80%, because the average across instances in the zone exceeds 80%. What change should they make to the MQL query to alert only when any individual instance exceeds 80%?

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

Accepted Answer

Change the group_by to group_by [instance_id] and remove zone grouping.. The current MQL query uses `group_by [zone]` to compute the mean CPU utilization per zone, which averages all instances in a zone together. By changing the grouping to `group_by [instance_id]` and removing the zone grouping, the alert will evaluate each instance individually, firing only when a single instance's CPU exceeds 80%, rather than when the zone-wide average exceeds the threshold.

Answer

Remove the group_by and use a filter instead.

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Add a filter for each instance individually.

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Use a ratio instead of mean.

Question 2

A company is deploying a three-node Bigtable cluster for production. They anticipate growth in read throughput and want to plan for scaling. Which two actions can they take to increase read throughput? (Choose TWO.)

Accepted Answer

Add more nodes to the existing cluster. Option A is correct because adding more nodes to a Bigtable cluster increases the cluster's compute capacity, and Bigtable distributes tablet serving across nodes, so additional nodes directly raise the aggregate read throughput available to the cluster. Option E is correct because adding a second cluster in a different zone (a multi-cluster routing setup) lets the application serve reads from multiple clusters, increasing overall read throughput and resilience; with multi-cluster routing, reads can be served from the nearest or all clusters depending on the app profile. Option B is wrong because a development instance is a single-node, non-production, non-HA instance with much lower performance and cannot be scaled for production read throughput. Option C is wrong because HDD storage in Bigtable is cheaper but has higher latency and lower throughput than SSD, so it would not increase read throughput. Option D is wrong because Key Visualizer is a monitoring/diagnostic tool that visualizes access patterns and row-key hot spots; it does not itself increase performance, though it can inform schema or key design changes.

Answer

Switch to a development instance type

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Change storage to HDD

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Use Key Visualizer to increase performance

Question 3

A database administrator is using Liquibase for schema versioning during a migration to Cloud SQL. What is the primary benefit of using Liquibase?

Accepted Answer

Version control and rollback of schema changes. Liquibase provides version control of database schema changes, allowing rollbacks and tracking in a declarative manner (changelogs).

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Real-time replication of data

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Automated performance tuning

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Automatic data type conversion

Question 4

A developer deploys a containerized application on Cloud Run. The application needs to access a Cloud SQL instance securely without exposing it to the internet. What is the best practice?

Accepted Answer

Use Cloud Run's VPC connector and configure private IP for Cloud SQL.. Cloud Run services cannot directly connect to Cloud SQL using private IP without a VPC connector. The VPC connector allows Cloud Run to send traffic to a VPC network, where the Cloud SQL instance with a private IP resides, ensuring traffic never traverses the public internet. This is the recommended pattern for secure, low-latency access to Cloud SQL from serverless environments.

Answer

Whitelist the Cloud Run IP range in Cloud SQL authorized networks.

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Use a Cloud SQL proxy sidecar container in the same pod.

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Use Cloud NAT to route traffic.

Question 5

You are designing a CI/CD pipeline using Cloud Build. You want to automatically trigger a build when code is pushed to a specific branch in Cloud Source Repositories. What is the correct configuration?

Accepted Answer

Create a build trigger in Cloud Build with a regex pattern for the branch name.. Cloud Build natively supports build triggers that can be configured to automatically start a build when code is pushed to a specific branch in Cloud Source Repositories. The trigger uses a regex pattern to match the branch name, and Cloud Build listens for repository push events directly without requiring additional services.

Answer

Create a Cloud Function that invokes Cloud Build via API when a push event occurs.

Answer

Add a build step in cloudbuild.yaml that polls the repository.

Answer

Configure a Cloud Pub/Sub topic to notify Cloud Build on push events.

Question 6

An engineer needs to create a Cloud SQL instance with SSD storage. Which storage type should they select for best performance?

Accepted Answer

SSD (solid-state drive). SSD (solid-state drive) is the recommended storage type for Cloud SQL instances when best performance is required. SSD provides lower latency and higher IOPS compared to HDD, making it suitable for transactional workloads and real-time applications. Cloud SQL supports both SSD and HDD, but SSD is the default and optimal choice for production databases.

Answer

HDD (hard disk drive)

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Local SSD

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Persistent disk standard

Question 7

A team notices that a Cloud Run service occasionally returns HTTP 500 errors. They have enabled Cloud Error Reporting. What is the best way to rapidly diagnose the root cause of these errors?

Accepted Answer

Examine the error group details in Cloud Error Reporting.. Cloud Error Reporting automatically groups similar errors (like HTTP 500s) into error groups, providing stack traces, request details, and occurrence timelines. Examining the error group details is the fastest path to root cause because it surfaces the exact exception and context without requiring manual log filtering or metric setup.

Answer

Search Cloud Logging manually for '500' events.

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View the Cloud Trace dashboard for error traces.

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Create a Cloud Monitoring dashboard for 5xx metrics.

Question 8

A team is investigating increased latency in a web application deployed on Google Kubernetes Engine (GKE). They want to identify which specific service calls are slow. Which Google Cloud tool should they use?

Accepted Answer

Cloud Trace. Cloud Trace is the correct tool because it provides end-to-end latency tracking for requests in distributed systems, including GKE. It captures detailed spans for each service call, allowing the team to pinpoint which specific microservice or API call is causing the increased latency. This aligns directly with the need to identify slow service calls in a web application.

Answer

Cloud Monitoring dashboards

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Cloud Profiler

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Cloud Logging

Question 9

A DevOps engineer is designing a row key for a Bigtable table storing user activity logs. The pattern is: user_id (UUID) + timestamp. On a cluster with 10 nodes, they observe severe hotspotting on a single node during peak writes. Which row key design change would likely resolve this issue?

Accepted Answer

Use a hash of the user_id as the prefix. The correct approach to mitigate hotspotting in Bigtable. Using a hash of the user_id as the row key prefix ensures uniform distribution of writes across tablets because the hash function randomizes the prefix, eliminating sequential patterns. Option D (timestamp + user_id) can still cause hotspotting if timestamps are strictly monotonically increasing, as all writes would target the same tablet at any given moment. While timestamps from multiple distributed sources may vary, this design is less robust than hashing and not a guaranteed solution. Therefore, only Option A reliably resolves the hotspotting issue.

Answer

Use a single table with no row key change

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Increase the number of nodes to 20

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Use a composite key: timestamp + user_id

Question 10

A company is running a critical application on Google Kubernetes Engine (GKE) that stores state in a Cloud SQL PostgreSQL instance. The application's latency-sensitive frontend needs to read data from Cloud SQL with minimal latency. The team wants to reduce read latency and offload read traffic from the primary database. What should they do?

Accepted Answer

Create a read replica of the Cloud SQL instance and direct read traffic to the replica.. Creating a read replica of the Cloud SQL PostgreSQL instance allows read-heavy, latency-sensitive traffic to be offloaded from the primary database. The replica handles SELECT queries independently, reducing load on the primary and lowering read latency for the frontend, as replicas are typically in the same region and can serve data with minimal additional delay.

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Migrate the database to Cloud Spanner for better read scalability.

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Use Memorystore for Redis as a cache layer between the application and Cloud SQL.

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Use Cloud CDN to cache database responses.