PCD Practice Test 35 — 15 Questions

Question 1

A company is migrating an on-premises PostgreSQL database to Cloud SQL. They need to ensure high availability and minimize downtime during maintenance. They also want to enable IAM database authentication for enhanced security. Which three actions should they take? (Choose three.)

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

Accepted Answer

Create a Cloud SQL for PostgreSQL instance with regional HA configuration. Creating a Cloud SQL for PostgreSQL instance with regional HA configuration uses synchronous replication across two zones within the same region, providing automatic failover with minimal downtime. This ensures high availability and meets the requirement to minimize downtime during maintenance, as the standby instance takes over with no data loss.

Answer

Use Cloud SQL Auth Proxy for all connections

Answer

Create a cross-region read replica for failover

Question 2

A developer is using Cloud Spanner for a global application. They need to design a schema to avoid hotspots. Which practice should they follow?

Accepted Answer

Use a hash prefix on the primary key. Cloud Spanner uses a distributed architecture that splits data across splits based on the primary key. A monotonically increasing or timestamp-based key causes all new writes to hit a single split, creating a hotspot. By using a hash prefix on the primary key, writes are distributed uniformly across all splits, avoiding hotspots and maximizing write throughput.

Answer

Use a UUID primary key

Answer

Use a monotonically increasing primary key

Answer

Use a composite primary key with a timestamp

Question 3

A company is migrating a PostgreSQL application to AlloyDB for improved OLTP performance and the ability to run analytical queries on the same data. Which feature of AlloyDB BEST supports this hybrid HTAP workload?

Accepted Answer

Columnar engine. AlloyDB's columnar engine is specifically designed to accelerate analytical queries by storing data in a column-oriented format, which allows for faster scans and aggregations on large datasets. This enables the same database to handle both OLTP (row-oriented) and OLAP (column-oriented) workloads without requiring a separate analytics system, directly supporting the hybrid HTAP requirement described in the question.

Answer

In-database ML inference

Answer

Cross-region replication

Answer

Automatic storage scaling

Question 4

An application uses Cloud SQL for read-heavy workloads. To scale reads, which configuration is best?

Accepted Answer

Add read replicas across zones. Read replicas in Cloud SQL allow you to offload read traffic from the primary instance to one or more replica instances, which are kept in sync using asynchronous replication. This configuration directly scales read capacity by distributing SELECT queries across replicas, making it the best choice for read-heavy workloads.

Answer

Use connection pooling

Answer

Enable high availability with standby

Answer

Enable automatic storage increase

Question 5

A company uses Firestore in Native mode for a mobile app. They need to enforce security rules to allow users to read and write only their own data. Which TWO steps are required? (Select TWO.)

Accepted Answer

Write a security rule that checks if request.auth.uid == resource.data.user_id. Firestore Security Rules use the request.auth object to identify the user. Use resource.data.user_id to match the document's owner field. The rules must check request.auth.uid against the document's field. Configuring IAM roles at the project level is not granular enough. Enabling Datastore mode changes the API.

Answer

Enable Datastore mode instead of Native mode

Answer

Assign the roles/datastore.user IAM role to each user

Answer

Create a composite index on user_id and timestamp

Question 6

A company deploys a containerized web application to Cloud Run. The application needs to access a Cloud SQL instance but fails with a connection timeout. The VPC connector is configured and attached to the Cloud Run service. What is the most likely cause?

Accepted Answer

The VPC connector is not configured to route to the Cloud SQL private IP range.. The VPC connector is attached to the Cloud Run service, but for it to route traffic to the Cloud SQL private IP address, the connector must be configured with a subnet that has a route to the Cloud SQL private IP range (e.g., 10.0.0.0/8 or a specific allocated range). Without this route, packets destined for the Cloud SQL instance's private IP are dropped, causing a connection timeout. The VPC connector itself does not automatically know how to reach Cloud SQL; the subnet must be peered or have appropriate routes.

Answer

Cloud SQL instance does not have a public IP address.

Answer

The application is not using the Cloud SQL Auth Proxy.

Answer

The VPC firewall rules block traffic to Cloud SQL.

Question 7

A data engineer needs to run a complex transformation pipeline between Cloud SQL and BigQuery, including joining data from both sources. The pipeline should run on a schedule and handle large volumes efficiently. Which service should they use?

Accepted Answer

Dataflow. Dataflow is the correct choice because it is a fully managed, serverless service for executing Apache Beam pipelines, which can handle complex transformations (e.g., joining data from Cloud SQL and BigQuery) at scale. It supports scheduled execution via Cloud Scheduler or built-in triggers, and its auto-scaling and exactly-once processing semantics ensure efficient handling of large volumes without manual infrastructure management.

Answer

Cloud Functions

Answer

Cloud Run

Answer

Datastream

Question 8

A company uses Cloud SQL for PostgreSQL and wants to set up point-in-time recovery (PITR) with a recovery window of 7 days. They have automated backups enabled. What additional configuration is required to achieve PITR?

Accepted Answer

Configure the backup retention period to 7 days and ensure automatic backup is enabled.. Point-in-time recovery (PITR) in Cloud SQL for PostgreSQL relies on write-ahead log (WAL) archiving, which is automatically enabled when automated backups are turned on. To retain the WAL logs needed to replay transactions to any point within the recovery window, you must set the backup retention period to at least 7 days. Option C correctly combines a 7-day backup retention with automated backups, which is the only additional configuration required beyond the default automated backup setting.

Answer

Create an on-demand backup every hour for the last 7 days.

Answer

Set up a cross-region backup copy with a retention of 7 days.

Answer

Enable binlog replication on the instance.

Question 9

A company uses Cloud Bigtable for AdTech clickstream data. They notice that some tables have many deleted rows and the storage cost is increasing. What should they configure to automatically remove deleted data and reduce storage?

Accepted Answer

Configure a garbage collection policy based on time or number of versions. Cloud Bigtable automatically compacts data in the background, but deleted rows are not immediately removed; they remain as tombstones until a garbage collection policy is applied. By configuring a garbage collection policy based on time or number of versions, you instruct Bigtable to permanently delete expired data and reclaim storage space, reducing costs.

Answer

Set up cluster replication to a secondary cluster

Answer

Enable compaction on the table

Answer

Use IAM conditions to restrict write access

Question 10

A startup is migrating an on-premises PostgreSQL 14 database to Cloud SQL. The database is 500 GB and handles OLTP workloads. They want to minimize downtime during migration. Which approach should they use?

Accepted Answer

Use Database Migration Service (DMS) with continuous replication. Database Migration Service (DMS) supports continuous replication from source PostgreSQL to Cloud SQL, allowing near-zero downtime. Export/import requires downtime. Replica promotion is not a migration method.

Answer

Export the database using pg_dump and import using psql

Answer

Create a Cloud SQL read replica from the on-premises database

Answer

Use gcloud sql import to directly import from a dump file

Question 11

A company is migrating an on-premises Oracle database to AlloyDB for PostgreSQL. They need to minimize downtime and ensure data consistency. They plan to use Database Migration Service (DMS). Which migration job type and configuration should they use?

Accepted Answer

Use a continuous migration job that performs an initial full dump followed by CDC replication.. Database Migration Service (DMS) continuous migration jobs perform an initial full dump to establish a baseline, then use Change Data Capture (CDC) to replicate ongoing changes from the source Oracle database to AlloyDB for PostgreSQL. This approach minimizes downtime by allowing the target to stay synchronized with the source until a cutover, ensuring data consistency without requiring a separate manual import step.

Answer

Use a continuous migration job with CDC only, skipping the initial dump.

Answer

Use a batch migration job that exports Oracle data to CSV files and loads them into AlloyDB.

Answer

Use a one-time full dump migration job and then manually import the dump into AlloyDB.

Question 12

A company is running a microservices application on Google Kubernetes Engine (GKE). They have implemented Cloud Monitoring and Cloud Logging, but recently they noticed that the Istio-proxy sidecar logs are missing from Cloud Logging. The application pods are running correctly and the sidecar containers are present. What is the most likely cause of the missing logs?

Accepted Answer

The cluster was not created with the Istio on GKE add-on enabled, so proxy logs are not automatically collected.. When using Istio on GKE, the Istio-proxy sidecar logs are automatically collected and sent to Cloud Logging only if the cluster was created with the 'Istio on GKE' add-on enabled. Without this add-on, the sidecar logs are not automatically forwarded, even though the sidecar containers are present and the application pods are running correctly. The add-on configures the necessary logging pipeline for Istio telemetry and logs.

Answer

The Istio-proxy logs are being sent to Stackdriver but are filtered by a log sink exclusion.

Answer

The Cloud Logging agent is not installed on the cluster nodes.

Answer

The sidecar container is not configured to output logs to stdout/stderr.

Question 13

A developer created a Cloud Function that makes an HTTP request to an external API. The above error occurs intermittently. The external API is working correctly. What is the most likely cause?

Accepted Answer

The request to the external API has incorrect headers or payload. The 'INVALID_ARGUMENT' error indicates the request payload or headers are malformed. Intermittent occurrence suggests a data-dependent issue rather than a permanent config problem.

Answer

The function is not handling network retries properly

Answer

The Cloud Function is not deployed in the same region as the API

Answer

The function is timing out due to long response time

Question 14

A developer is designing a data pipeline using Pub/Sub and Dataflow. They need to guarantee at-least-once delivery with no duplicates in the sink. Which Dataflow feature should they use?

Accepted Answer

Exactly-once processing. Dataflow's exactly-once processing (also known as 'exactly-once semantics' or 'EOS') ensures that each record is processed exactly once, even if the pipeline restarts or fails. This eliminates duplicates in the sink while still guaranteeing at-least-once delivery from Pub/Sub, because Dataflow uses a combination of source-side deduplication (via Pub/Sub message IDs) and sink-side idempotent writes (via the Dataflow sink's commit protocol). The result is that no duplicate records are written to the sink, meeting the requirement of no duplicates.

Answer

Checkpointing

Answer

Idempotent writes

Answer

Windowing

Question 15

A developer wants to profile their application's CPU and memory usage to identify performance bottlenecks. Which TWO Google Cloud services should they use?

Accepted Answer

Cloud Profiler. The two Google Cloud services that a developer should use to profile application CPU and memory usage and identify performance bottlenecks are Cloud Profiler and Cloud Trace. Cloud Profiler (Option C) continuously gathers and analyzes call stacks and resource consumption across your application, pinpointing functions that consume the most CPU and memory. Cloud Trace (Option D) provides distributed tracing to analyze request latency and identify performance bottlenecks in microservices architectures. Together, they offer a comprehensive view of application performance, with Profiler focusing on resource-intensive code paths and Trace focusing on request-level delays.

Answer

Cloud Logging

Answer

Cloud Debugger

Answer

Cloud Monitoring