PCDE Practice Test 41 — 15 Questions

Question 1

A media streaming company uses Cloud Bigtable to store user session data with a single cluster in us-east1. They want to add disaster recovery capability with an RPO of no more than 5 minutes and an RTO of under 10 minutes. Which action should they take?

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

Accepted Answer

Add a second cluster in a different region with replication, and configure a Cloud DNS health check to redirect traffic. Bigtable replication allows adding a second cluster in a different region with asynchronous replication. The replication lag can be within seconds, typically under 5 minutes. For RTO under 10 minutes, manual failover via the Cloud Console or CLI is sufficient; automatic failover is not built-in but can be achieved with external orchestration.

Answer

Use Cloud SQL cross-region read replicas

Answer

Deploy a new Bigtable instance in another region and set up dataflow pipelines to replicate data

Answer

Create an on-demand backup and restore to another region

Question 2

A company is migrating a 5 TB Oracle database to Cloud SQL for PostgreSQL using DMS with continuous migration. They need to minimize downtime and have a rollback plan. Which TWO actions should they include in their migration plan? (Choose TWO.)

Accepted Answer

Test the application against the destination Cloud SQL instance before cutover.. Option B is correct because validating the application against the destination Cloud SQL for PostgreSQL instance before cutover verifies query compatibility, performance, and connection behavior after the Database Migration Service (DMS) schema and data conversion, so issues are caught while the source is still authoritative and downtime is minimized. Option E is correct because keeping the source Oracle database running in read-only mode after cutover preserves a rollback path: if the promoted Cloud SQL destination fails validation, the team can revert the application to the still-consistent source without data loss. Option A is wrong because a one-time migration job cannot capture ongoing changes, which would force a lengthy outage for a 5 TB database instead of the required continuous migration with minimal downtime. Option C is wrong because deleting the source immediately eliminates any rollback capability and risks permanent data loss if the destination has problems. Option D is wrong because skipping schema conversion and using raw Oracle SQL is incompatible with PostgreSQL, so the converted schema and SQL dialect must be handled by DMS and the application.

Answer

Use a one-time migration job instead of continuous.

Answer

Delete the source database immediately after promoting the destination.

Answer

Skip schema conversion and use raw Oracle SQL.

Question 3

Which TWO BigQuery features are specifically designed to accelerate BI dashboard query performance? (Choose TWO.)

Accepted Answer

Clustering. Clustering (B) physically co-locates rows with similar values in the same storage blocks, allowing BigQuery to skip entire blocks when processing queries with filters on clustered columns. This dramatically reduces the amount of data scanned, directly accelerating BI dashboard queries that often filter by date, region, or customer ID. Cached results (D) store the output of recent queries for up to 24 hours, so repeated dashboard refreshes or concurrent user requests can be served instantly without re-scanning any data.

Answer

Wildcard tables

Answer

User-defined functions (UDFs)

Answer

Column-level security

Question 4

A startup is building a ride-sharing application that requires globally distributed, strongly consistent transactions for ride matching and payments. The database must scale horizontally and provide low-latency reads and writes. Which Google Cloud database should they use?

Accepted Answer

Cloud Spanner. Cloud Spanner is Google's globally distributed, horizontally scalable relational database that provides external consistency (strong consistency) across regions using TrueTime and Paxos. It supports ANSI SQL, ACID transactions, and low-latency reads/writes at global scale, making it the only option that satisfies all three requirements: global distribution, strong consistency, and horizontal scaling.

Answer

Cloud Bigtable

Answer

Cloud SQL

Answer

Firestore

Question 5

A Database Engineer is deploying a Cloud SQL for PostgreSQL instance for a financial services application that requires high availability and automatic failover. The engineer also needs to ensure that backups are taken daily and retained for 30 days. Which TWO actions should the engineer take? (Choose two.)

Accepted Answer

Enable automated backups and set backup retention to 30 days.. Cloud SQL automated backups can be configured with a retention period of up to 365 days, and setting it to 30 days meets the requirement for daily backups with 30-day retention. Option C is correct because enabling high availability (HA) on a Cloud SQL instance with a regional persistent disk provides automatic failover to a standby instance in a different zone within the same region, ensuring high availability for the financial services application.

Answer

Create a cross-region replica and configure automatic failover.

Answer

Schedule a Cloud Scheduler job to export the database to Cloud Storage daily.

Answer

Enable point-in-time recovery (PITR) with a 7-day retention.

Question 6

A mobile app backend uses Firestore for user profiles. The schema has a single collection 'users' where each document contains: user_id (used as document ID), name, email, and friends (an array of user IDs). The friends array can grow large (thousands of IDs). When a user adds a friend, the application updates the array, causing the document to grow and leading to write contention and size limit warnings. The team needs to redesign the schema to scale better. What is the best approach?

Accepted Answer

Create a new 'friendships' collection with documents containing user_id_1 and user_id_2 fields.. It normalizes the friendship relationship into a separate 'friendships' collection, where each document represents a single bidirectional link between two users. This avoids unbounded document growth and write contention on user documents, as adding a friend only requires a small write to a new friendship document rather than updating a potentially large array. Firestore's 1 MiB document size limit and 1 write per second per document limit are no longer risk factors.

Answer

Move the friends list to a subcollection under each user document.

Answer

Migrate user profiles and friendships to Cloud SQL for relational capabilities.

Answer

Limit the maximum size of the friends array to 1000 at the application level.

Question 7

An e-commerce platform wants to implement chaos engineering on its Google Kubernetes Engine cluster to test resilience against network latency. Which tool is specifically designed for this purpose on GKE?

Accepted Answer

Chaos Mesh. Chaos Mesh is an open-source chaos engineering platform for Kubernetes. It can inject various faults including network latency, and is available on GKE. Traffic Director fault injection is for service mesh, not directly for GKE pods. Cloud Functions is not for Kubernetes.

Answer

Traffic Director fault injection

Answer

Cloud Functions

Answer

Cloud Build

Question 8

An engineer wants to use Skaffold for local development and for CI/CD on Google Cloud. Which feature allows Skaffold to run on Cloud Build and deploy to GKE?

Accepted Answer

Skaffold run command. The `skaffold run` command is the correct answer because it performs a one-shot build and deploy, which is the exact behavior needed for CI/CD pipelines. When integrated with Cloud Build, `skaffold run` executes the entire workflow (build, test, deploy) in a non-interactive, headless mode, making it suitable for automated deployments to GKE without requiring a continuous dev loop.

Answer

Skaffold dev loop

Answer

Skaffold init command

Answer

Skaffold delete command

Question 9

A DevOps team has a GKE workload that experiences fluctuating traffic. They want to automatically adjust the number of pods based on CPU utilization. Which resource should they configure?

Accepted Answer

Horizontal Pod Autoscaler. Horizontal Pod Autoscaler (HPA) automatically scales the number of pod replicas based on observed CPU utilization or other metrics, which is exactly what the team needs.

Answer

Pod Disruption Budget

Answer

Vertical Pod Autoscaler

Answer

Cluster Autoscaler

Question 10

A team needs to migrate a large Teradata data warehouse to BigQuery. They want to automatically convert Teradata DDL and BTEQ scripts to BigQuery-compatible SQL. Which Google Cloud service should they use?

Accepted Answer

Schema Conversion Tool (SCTS). BigQuery Schema Conversion Tool (SCTS), part of the BigQuery Migration Service, is purpose-built to translate Teradata DDL, DML, and BTEQ scripts into BigQuery-compatible SQL. It performs automated syntax and semantic conversion, flags unsupported constructs, and produces a conversion report. This is the recommended Google Cloud service for Teradata-to-BigQuery SQL translation.

Answer

BigQuery Data Transfer Service

Answer

Database Migration Service (DMS)

Answer

Cloud Dataflow

Question 11

An organization wants to centralize cost management across multiple projects. They need to analyze spending trends and set budget alerts. Which combination of services should they use?

Accepted Answer

Export billing data to BigQuery and set up budgets with alert thresholds.. Exporting billing data to BigQuery enables SQL-based analysis of spending trends, and Cloud Billing budgets with alert thresholds provide proactive notifications. This combination is the standard Google Cloud approach for centralized cost management and analysis.

Answer

Use the Cloud Billing API to retrieve cost data and store in Firestore for querying.

Answer

Export billing data to Cloud Storage and use Cloud Logging for analysis.

Answer

Enable Cloud Billing reports and configure Slack notifications via webhooks.

Question 12

A company wants to enforce that only approved images from Artifact Registry can be deployed to their GKE clusters. They also want to ensure that images are scanned for vulnerabilities. Which TWO services should they use together?

Accepted Answer

Binary Authorization. Binary Authorization (B) is the GKE-integrated admission controller that enforces deploy-time policies, allowing only container images that meet defined attestations (such as being built by approved pipelines or signed by trusted authorities) to be admitted to the cluster, which directly satisfies the requirement to restrict deployments to approved Artifact Registry images. Container Analysis (D) provides the vulnerability scanning and metadata/attestation storage that Binary Authorization relies on, automatically scanning images pushed to Artifact Registry and generating the vulnerability and build attestations used by the policy. Together they form the standard GKE supply-chain security pair: Container Analysis produces the scan results and attestations, and Binary Authorization enforces them at admission time. Cloud IAM (A) handles authentication and authorization of identities but cannot enforce image provenance or scan requirements. Cloud Build (C) is a CI/CD build service that can create attestations but is not the enforcement or scanning mechanism itself. Artifact Registry (E) stores and manages the container images but does not by itself enforce admission policies or perform the vulnerability analysis needed for this scenario.

Answer

Cloud IAM

Answer

Cloud Build

Answer

Artifact Registry

Question 13

An engineer needs to build a Docker image using Cloud Build and ensure the image is cached across builds to speed up subsequent runs. The build uses Kaniko. What should the engineer add to the cloudbuild.yaml to enable layer caching?

Accepted Answer

Use the 'kaniko' builder and set '--cache=true' and '--cache-repo'. Kaniko is a container image builder designed to run inside containers without a Docker daemon, and it supports layer caching via the '--cache=true' flag combined with '--cache-repo' to specify a repository where cached layers are stored and retrieved. Adding these flags to the Kaniko builder step in cloudbuild.yaml enables reuse of unchanged layers across builds, significantly speeding up subsequent runs.

Answer

Configure a build pool with a persistent disk for caching

Answer

Add step using 'docker build' with '--cache-from'

Answer

Set the 'images' field in cloudbuild.yaml to enable automatic caching

Question 14

A team is converting an Oracle stored procedure that uses PL/SQL with cursors to PostgreSQL PL/pgSQL. The procedure declares a cursor with parameters. Which conversion is correct for a parameterized cursor in PL/pgSQL?

Accepted Answer

Declare the cursor as CURSOR (param INT) FOR SELECT * FROM table WHERE id = param;. The correct conversion for a parameterized cursor in PL/pgSQL is to declare the cursor using the syntax 'CURSOR (param INT) FOR SELECT ...'. This is the direct equivalent of Oracle's parameterized cursor. While REFCURSOR can also be used, it is not the most direct conversion and does not declare the cursor with parameters in the same way.

Answer

Use a REFCURSOR variable and OPEN it with a query using the parameter.

Answer

Replace the cursor with a FOR loop that returns a set of rows.

Answer

Use a temporary table to store the query results.

Question 15

A company is designing a schema for Cloud Bigtable to store user sessions. Access patterns: (1) read all sessions for a given user ID, and (2) read a specific session by session ID. The row key should support both patterns efficiently. Which row key design is MOST appropriate?

Accepted Answer

Use user_id#session_id as the row key. Using user_id#session_id as the row key allows efficient range scans for all sessions of a given user (prefix scan on user_id) and direct point reads for a specific session (exact row key lookup). This design leverages Bigtable's lexicographic sorting, where rows with the same user_id prefix are stored contiguously, enabling fast retrieval of all sessions for a user.

Answer

Use session_id as the row key and store user_id as a column

Answer

Use a hash of user_id as row key prefix and session_id as suffix

Answer

Use user_id as the row key and store multiple session columns