PCDE Practice Test 3 — 30 Questions

Question 1

An organization wants to store Docker images in a private Google Cloud repository with vulnerability scanning enabled. Which service should they use?

Accepted Answer

Artifact Registry. Artifact Registry is Google Cloud's recommended service for storing container images and other artifacts (Maven, npm, Python packages). It natively supports vulnerability scanning via Container Analysis, integrates with IAM for fine-grained access control, and supports regional repositories. Container Registry (GCR) is deprecated in favor of Artifact Registry, making Artifact Registry the correct modern choice.

Answer

Container Registry

Answer

Cloud Build

Answer

Cloud Storage

Question 2

An organization needs to run both transactional (OLTP) and real-time analytical (OLAP) queries on the same dataset without data duplication. The dataset is moderately large (a few terabytes). Which Google Cloud database service is MOST appropriate for this HTAP workload?

Accepted Answer

AlloyDB. AlloyDB is Google Cloud's PostgreSQL-compatible, fully managed database designed for HTAP workloads. It uses a columnar engine that automatically accelerates analytical queries on the same data used for transactional processing, eliminating the need for ETL or data duplication. Its architecture separates compute and storage, allowing independent scaling for OLTP and OLAP, and it supports real-time analytics with minimal latency. For a few terabytes, AlloyDB provides the best balance of transactional throughput and analytical performance without duplicating data.

Answer

Bigtable

Answer

BigQuery

Answer

Cloud SQL for PostgreSQL

Question 3

An SRE team wants to track the amount of toil each week and ensure it does not exceed 50% of the team's time. Which approach is most aligned with SRE best practices?

Accepted Answer

Have each team member log their time and estimate toil percentage weekly. SRE best practices emphasize measuring toil to ensure it does not exceed 50% of the team's time. The most practical approach is to have each team member log their time and estimate toil percentage weekly. This provides a qualitative and quantitative measure, allowing the team to track and address toil.

Answer

Use Cloud Monitoring to automatically classify all tasks as toil

Answer

Use Cloud Tasks to queue up toil items and measure completion time

Answer

Set a Cloud Scheduler job to remind team members to automate toil

Question 4

You need to monitor the number of ERROR-level log entries in Cloud Logging and trigger an alert when the count exceeds 100 in 5 minutes. Which approach should you use?

Accepted Answer

Create a log-based counter metric with filter 'severity=ERROR' and then set an alert on that metric. A log-based counter metric counts matching log entries, and a filter of severity=ERROR scopes it to error logs. An alerting policy on that counter metric with a threshold of 100 over a 5-minute window triggers exactly as required. This is the standard Cloud Monitoring pattern for log-derived alerts.

Answer

Create a log-based distribution metric and set an alert on the count

Answer

Use a logs-based alerting policy directly from Cloud Logging

Answer

Export logs to BigQuery and run a scheduled query to trigger a custom alert

Question 5

A company is migrating a large on-premises MySQL database to Cloud SQL. The source database supports heavy reporting queries that scan millions of rows and join multiple tables. The team wants to minimize downtime and avoid performance degradation during migration. Which migration approach should they use?

Accepted Answer

Set up Database Migration Service (DMS) with continuous replication from the source to Cloud SQL, then cut over when replication lag is minimal. Database Migration Service (DMS) performs an initial full dump-and-load followed by continuous change data capture (CDC) replication from the source MySQL to Cloud SQL, allowing the source to remain fully operational during migration. Because replication is continuous, the cutover can be scheduled when replication lag is near zero, minimizing downtime and avoiding the performance hit of a cold dump/restore. This is the recommended approach for minimizing downtime on large, actively used MySQL databases.

Answer

Use gcloud sql import command to import a CSV export while the source database remains in use

Answer

Create a BigQuery transfer service to move data from MySQL to Cloud SQL

Answer

Use mysqldump to export the data and import it into Cloud SQL during a maintenance window

Question 6

You are designing a BigQuery schema for IoT sensor data. The sensor readings have varying fields depending on the sensor type. You want to minimize storage costs and avoid schema maintenance when new sensor types are added. What is the best schema design?

Accepted Answer

Store the sensor data in a JSON column. Storing sensor data in a JSON column leverages BigQuery's native support for semi-structured data (the `JSON` data type), allowing you to ingest records with varying fields without schema changes. This minimizes storage costs by avoiding the overhead of many NULL columns and eliminates the need for schema maintenance when new sensor types are added, as BigQuery can query JSON fields directly using functions like `JSON_EXTRACT` or dot notation.

Answer

Use a separate table per sensor type

Answer

Use a schema with a STRUCT containing all possible fields as optional

Answer

Use a wide table with many nullable columns

Question 7

A BI report requires a running total of sales over the last 30 days for each product. The data is in a BigQuery table with columns: sale_date, product_id, amount. Which SQL window function is most efficient?

Accepted Answer

Use SUM(amount) OVER (ORDER BY sale_date ROWS BETWEEN 30 PRECEDING AND CURRENT ROW). The most efficient among the given choices for a 30-day rolling sum, because it uses a window function with `ROWS BETWEEN 30 PRECEDING AND CURRENT ROW` to limit the sum to the last 30 rows. Although a true time-based window would require `RANGE BETWEEN INTERVAL 29 DAY PRECEDING AND CURRENT ROW` with `PARTITION BY product_id`, that is not offered. Option C gives a cumulative sum (unbounded) which is not a 30-day total. Options A and D are set-based or inefficient. Thus B is the best available.

Answer

Use GROUP BY with SUM(amount)

Answer

Use SUM(amount) OVER (ORDER BY sale_date ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW)

Answer

Use a correlated subquery to sum over previous dates

Question 8

An organization uses Cloud Build and wants to inject a secret API key into a build step without exposing it in the cloudbuild.yaml. Which approach should they use?

Accepted Answer

Use `secretEnv` to reference a Secret Manager secret. Cloud Build's `secretEnv` field allows you to reference a secret stored in Secret Manager and inject it as an environment variable into a build step. This approach ensures the secret value is never exposed in the `cloudbuild.yaml` file or build logs, as Cloud Build retrieves it securely at runtime using the Secret Manager API.

Answer

Store the key in a Cloud Build substitution variable

Answer

Pass the key via `args` with a substitution

Answer

Store the key in a Cloud Storage bucket and download it in the build

Question 9

You notice that your Cloud SQL for MySQL instance's storage is filling up quickly. You have enabled automatic storage increase, but you want to manually increase the storage size by 50 GB to avoid any risk of reaching the limit. The current disk size is 200 GB. What is the correct gcloud command to resize the disk?

Accepted Answer

gcloud sql instances patch my-instance --storage-size 250. The `gcloud sql instances patch` command is used to modify an existing Cloud SQL instance, and the `--storage-size` flag expects the value in GB as an integer (without the 'GB' suffix). Specifying `250` correctly increases the storage from 200 GB to 250 GB.

Answer

gcloud sql instances patch my-instance --storage-size 250GB

Answer

gcloud sql instances update my-instance --storage-size 250

Answer

gcloud sql instances resize my-instance 250

Question 10

A financial BI application stores monetary values such as revenue and tax amounts. Which BigQuery data type should be used to ensure accuracy in calculations?

Accepted Answer

Use NUMERIC or BIGNUMERIC. NUMERIC and BIGNUMERIC are exact numeric types with fixed precision and scale, designed to avoid floating-point rounding errors. In BigQuery, monetary calculations require exact decimal arithmetic, and these types provide up to 38 (NUMERIC) or 76 (BIGNUMERIC) digits of precision, ensuring accuracy for revenue and tax computations.

Answer

Use STRING and parse numbers as needed

Answer

Use INT64 and store amounts in cents

Answer

Use FLOAT64

Question 11

A DevOps engineer wants to automatically trigger a Cloud Build pipeline whenever a pull request is created against the main branch of a repository. Which type of build trigger should they use?

Accepted Answer

Pull request trigger. A pull request trigger in Cloud Build is specifically designed to initiate a build when a pull request is created or updated against a target branch, such as main. This trigger type evaluates the PR event and automatically runs the pipeline, enabling validation of proposed changes before merging.

Answer

Push to branch trigger

Answer

Scheduled trigger

Answer

Manual trigger

Question 12

A company uses Terraform with remote state stored in GCS. They want to prevent concurrent `terraform apply` runs for the same configuration to avoid state corruption. Which feature should they use?

Accepted Answer

State locking is automatically enabled when using a GCS backend; no additional configuration is needed.. The GCS backend for Terraform automatically supports state locking without any additional configuration. When Terraform performs operations that could modify state (like apply or destroy), it creates a lock object in the same GCS bucket to prevent concurrent modifications. This is built into the backend implementation, so no flags or bucket settings are required. Therefore, option D is correct.

Answer

Set the `-lock` flag to `true` in the Terraform CLI command.

Answer

Enable state locking in the GCS bucket by setting `force_destroy = false`.

Answer

Use Terraform workspaces to isolate runs.

Question 13

Refer to the exhibit. A company has a Cloud Spanner instance with the backup configuration shown. They need to improve disaster recovery. Which THREE strategies should they implement?

Accepted Answer

Enable point-in-time recovery (PITR). Option B is correct because enabling point-in-time recovery (PITR) on the Cloud Spanner instance lets the company restore the database to any timestamp within the configurable retention window (up to 7 days), which directly strengthens disaster recovery against accidental data corruption or deletion. Option C is correct because using a multi-region instance configuration replicates data synchronously across multiple regions with a 99.999% SLA, providing resilience if an entire region becomes unavailable. Option D is correct because configuring cross-region backups stores backup copies in a different region than the source instance, protecting recovery data even if the instance's home region is lost. Option A is not the best fit because exports to Cloud Storage are manual or scheduled logical dumps that are not automatically managed as Spanner backups and have slower, less granular restore capabilities. Option E is not correct because read replicas in another region improve read latency and read availability but do not by themselves provide a recovery mechanism for restoring lost or corrupted data.

Answer

Schedule regular exports to Cloud Storage

Answer

Use read replicas in another region

Question 14

Refer to the exhibit. The company wants to achieve a 99.99% SLA for this Cloud SQL instance. What should they do?

Accepted Answer

Change the availability type to REGIONAL.. A 99.99% SLA for Cloud SQL requires a regional (multi-zone) configuration to protect against a zonal failure. By changing the availability type to REGIONAL, the instance is provisioned with a synchronous standby in a different zone, enabling automatic failover and meeting the 99.99% uptime target. The default zonal availability only provides a 99.95% SLA.

Answer

Change to a different tier.

Answer

Enable automatic backups.

Answer

Increase the number of CPUs.

Question 15

A BI team is designing a BigQuery table for a sales dashboard that queries daily sales by product category and region. The dashboard often filters on a specific date range and a specific region. Which combination of partitioning and clustering should be used?

Accepted Answer

Partition by date, cluster by region. Partitioning by date (e.g., on a DATE or TIMESTAMP column) allows BigQuery to prune entire partitions when the dashboard filters on a specific date range, reducing the amount of data scanned. Clustering by region then sorts the data within each partition by region, enabling efficient block-level pruning when the dashboard filters on a specific region. This combination optimizes both the date range and region filters, which are the most common query patterns for this sales dashboard.

Answer

Partition by region, cluster by date

Answer

Use only clustering on date and region without partitioning

Answer

Partition by month, cluster by date

Question 16

A data engineering team ingests JSON logs into BigQuery using a streaming pipeline. Queries need to extract specific fields from nested arrays. Which SQL construct should be used to efficiently transform the nested data into a flat table for BI?

Accepted Answer

UNNEST with CROSS JOIN. `UNNEST` with `CROSS JOIN` is the standard SQL construct in BigQuery to flatten nested arrays (repeated fields) into a flat table. When JSON logs contain arrays of structs, `CROSS JOIN UNNEST(array_column)` expands each array element into its own row, allowing BI tools to access individual fields directly. This is the most efficient and idiomatic way to transform nested data into a relational format for querying.

Answer

ARRAY_AGG with STRUCT

Answer

STRUCT with nested field access

Answer

SELECT * EXCEPT with UNNEST

Question 17

A company is migrating an on-premises PostgreSQL database to Cloud SQL. The database is 2 TB and must have minimal downtime during migration. Which migration strategy should the Database Engineer recommend?

Accepted Answer

Use Database Migration Service to set up continuous replication from the on-premises database to Cloud SQL, then perform a minimal-downtime cutover.. The Database Migration Service (DMS) supports continuous replication from an on-premises PostgreSQL database to Cloud SQL using logical replication (pglogical or native PostgreSQL logical replication). This allows the source database to remain operational during the migration, and the cutover to Cloud SQL can be performed with minimal downtime, typically seconds to minutes, meeting the 2 TB size and low-downtime requirements.

Answer

Export the database using pg_dump and import into Cloud SQL using pg_restore during a maintenance window.

Answer

Set up PostgreSQL on Compute Engine and replicate data, then switch over to Cloud SQL.

Answer

Use Cloud SQL's built-in replication feature to connect directly to the on-premises database.

Question 18

An organization uses Artifact Registry to store Docker images. They want to enforce that only images that have passed vulnerability scanning and are signed can be deployed to GKE. Which two services should they use together?

Accepted Answer

Binary Authorization and Container Scanning API. Binary Authorization enforces that only signed and verified container images can be deployed to GKE, while the Container Scanning API (now part of Artifact Analysis) performs vulnerability scanning on images stored in Artifact Registry. Together, they ensure that only images that have passed vulnerability scanning and are cryptographically signed can be deployed, meeting the organization's requirements.

Answer

Cloud Deploy and Cloud Run

Answer

Cloud Build and Artifact Registry

Answer

Security Command Center and Cloud Asset Inventory

Question 19

A company is using Cloud SQL and wants to automatically increase storage when disk usage reaches a threshold. What should they configure?

Accepted Answer

Enable 'auto-storage increase' in the instance settings.. Cloud SQL provides a built-in 'auto-storage increase' setting that, when enabled, automatically increases the instance's storage capacity when disk usage reaches a predefined threshold (typically 90% or when free space drops below a certain amount). This eliminates the need for manual intervention or custom automation, ensuring high availability and preventing out-of-disk errors.

Answer

Use Active Assist recommendations to manually resize.

Answer

Set up a Cloud Monitoring alert to manually increase storage when usage exceeds 80%.

Answer

Configure a Cloud Function to resize the disk via API when threshold is reached.

Question 20

An organization wants to set up a landing zone with separate projects for development, staging, and production environments. They also need a shared VPC for networking and a centralized logging project. Which folder structure aligns with Google Cloud best practices?

Accepted Answer

Create folders: /environments/dev, /environments/staging, /environments/prod, and /common. Place networking and logging projects in /common.. It follows Google Cloud best practices by separating environments (dev, staging, prod) into their own folder under an /environments parent, and placing shared resources like networking and logging into a /common folder. This structure enables consistent IAM policy inheritance, resource isolation, and centralized management of shared services, which is critical for a landing zone in a DevOps pipeline.

Answer

Create a single folder /landing-zone and put all projects there.

Answer

Create folders: /dev, /staging, /prod. Place all projects directly under the root.

Answer

Create folders: /prod, /non-prod, /shared. Put dev and staging in /non-prod.