PCDE Practice Test 28 — 15 Questions

Question 1

A team is designing a CI/CD pipeline for a microservice that requires canary deployments with metrics-based rollback. They want to use Cloud Deploy and Cloud Run. Which three features must they configure? (Choose 3)

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

Accepted Answer

Canary deployment strategy with canary percentage and metric thresholds. Option A is correct because Cloud Deploy implements canary rollouts by specifying a canary deployment strategy with a canary percentage and analysis metrics/thresholds that trigger automatic rollback when the metrics breach the defined limits. Option B is correct because a Cloud Deploy delivery pipeline must be defined with promotion targets (e.g., dev, staging, prod) so the canary release can progress through environments in the CI/CD workflow. Option C is correct because Cloud Run must be configured as the deployment target (runtime) in the delivery pipeline so Cloud Deploy can create and shift traffic between Cloud Run revisions during the canary. Option D is not required: Binary Authorization is an optional security control for attesting container images, not a prerequisite for metrics-based canary rollback. Option E is not required: manual approval gates are optional promotion controls and are not needed for automated metrics-based canary analysis and rollback.

Answer

Binary Authorization policy

Answer

Manual approval gate on the prod target

Question 2

A company is using Bigtable for real-time analytics and notices that some queries are experiencing high latency. They suspect a hot spot due to a row key design that uses a monotonically increasing value. Which two actions should they take to diagnose and mitigate the hot spottedness? (Choose TWO.)

Accepted Answer

Redesign the row key to include a hash prefix or a field that distributes writes evenly. Key Visualiser helps identify hot spots by showing row key distribution. Prefixing the row key with a field that distributes writes (like a hash prefix) is a common mitigation strategy.

Answer

Increase the number of nodes to spread the load

Answer

Create a Bigtable table with a different column family

Answer

Switch from HDD to SSD storage type

Question 3

You are deploying a containerized application to Cloud Run using gcloud run deploy. You need to ensure that revisions are tagged with a custom identifier for testing purposes, without allocating any traffic to them. Which flag should you use?

Accepted Answer

--tag=test. The `--tag` flag in `gcloud run deploy` assigns a custom tag (e.g., `test`) to a specific revision, allowing it to be accessed via a dedicated URL without receiving any live traffic. This is the correct way to create a tagged revision for testing or staging purposes while keeping the primary revision serving user requests.

Answer

--no-traffic

Answer

--traffic=test=0

Answer

--revision-suffix=test

Question 4

A Cloud SQL for PostgreSQL read replica is experiencing replication lag of several minutes. You need to reduce the lag. What is the most effective solution?

Accepted Answer

Increase the CPU and memory of the read replica to speed up applying changes.. Replication lag in Cloud SQL for PostgreSQL read replicas is often caused by the replica being unable to keep up with the rate of write-ahead log (WAL) apply from the primary. Increasing the CPU and memory of the read replica directly improves its ability to replay WAL records faster, reducing the lag. This is the most effective solution as it addresses the bottleneck at the replica side without impacting the primary instance.

Answer

Disable automated backups on the primary to free up resources.

Answer

Promote the replica to a standalone instance and recreate the replica.

Answer

Increase the CPU and memory of the primary instance.

Question 5

You are managing a Cloud SQL for MySQL instance that supports a web application. Recently, users have reported that the application is responding slowly during peak hours. You examine the Query Insights dashboard and see that a specific query is running frequently and has a high execution time. The query involves JOINs on three tables, each with tens of thousands of rows. The query plan shows a full table scan on two tables. What should you do first to improve performance?

Accepted Answer

Add indexes on the columns used in JOIN conditions.. Adding indexes on the columns used in JOIN conditions will improve query performance by allowing the database to quickly locate matching rows instead of scanning entire tables. The query plan shows full table scans on two tables, indicating missing indexes. Indexes reduce the amount of data read and speed up JOIN operations.

Answer

Enable the query cache flag in Cloud SQL database flags.

Answer

Increase the instance size to provide more memory and CPU.

Answer

Rewrite the query to use subqueries instead of JOINs.

Question 6

A financial services company uses Cloud Spanner for transaction processing. They need to capture real-time changes from the database to stream to a downstream analytics system. Which THREE services or features can achieve this?

Accepted Answer

Cloud Pub/Sub. Spanner change streams are correct because they capture row-level mutations in real time directly from Cloud Spanner. Cloud Pub/Sub is correct as it provides a fully managed messaging service that ingests and delivers change events from Spanner change streams to downstream systems with at-least-once delivery and low latency. Cloud Dataflow is correct because it can process and transform the change stream events in real time, enabling streaming analytics or integration with other services. Together, these three services form a complete pipeline: Spanner change streams capture changes, Pub/Sub transports them, and Dataflow processes them for the analytics system.

Answer

Cloud SQL for PostgreSQL

Answer

Bigtable replication

Question 7

An engineer is migrating a 20 TB PostgreSQL database to AlloyDB using DMS continuous migration. The full dump phase is taking longer than expected. Which THREE factors could affect the duration of the full dump phase? (Choose THREE.)

Accepted Answer

The number of tables and indexes on the source.. Option B is correct because the full dump phase must read and export every table and index, so a higher object count (many tables and indexes) increases metadata handling and parallel extraction overhead, directly lengthening the dump. Option C is correct because the dump is driven by the source server's ability to read data, so limited CPU and disk I/O on the source throttles how fast rows can be scanned and transmitted. Option E is correct because the extracted data must be streamed from the source to the DMS instance, so insufficient network bandwidth becomes a bottleneck that extends the full dump duration. Option A does not belong because the PostgreSQL major/minor version affects feature and replication-slot compatibility, not the raw duration of the full dump. Option D does not belong because SSL versus non-SSL adds only minor encryption overhead and is not a primary determinant of full dump duration.

Answer

The version of the source PostgreSQL database.

Answer

The choice of SSL or non-SSL connection.

Question 8

An organization wants to enforce that all Cloud Run services are not publicly accessible. Which organization policy should they use?

Accepted Answer

`run.allowedIngress`. The `run.allowedIngress` organization policy constraint is specifically designed to control ingress settings for Cloud Run services, allowing administrators to enforce that all services restrict traffic to internal sources only (e.g., `internal` or `internal-and-cloud-load-balancing`). This directly prevents public accessibility by blocking external HTTP/S requests at the platform level, overriding any per-service configuration.

Answer

`compute.vmExternalIpAccess`

Answer

`iam.allowedPolicyMemberDomains`

Answer

`cloudrun.allowedIngress`

Question 9

A company is migrating a 10 TB Teradata data warehouse to BigQuery. They need to convert Teradata DDL and BTEQ scripts to BigQuery 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 handles Teradata-specific syntax, data types, and procedural constructs, producing a translation report and assessment. This is the only option that performs code conversion rather than data movement.

Answer

BigQuery Data Transfer Service

Answer

Database Migration Service (DMS)

Answer

gcloud bigquery load

Question 10

A company wants to implement Binary Authorization for containers deployed to GKE. They need to ensure that only images signed by their internal CI system are allowed to run. Which three components are required?

Accepted Answer

An attestor in Binary Authorization. Option A is correct because an attestor is the Binary Authorization resource that defines the trusted authority (identified by a key pair or PKIX/Note) whose signature the policy will verify before admitting an image. Option B is correct because the CI system must cryptographically sign the container image's digest using a private key, producing an attestation that the attestor can validate. Option D is correct because the Binary Authorization policy must be configured with a rule (e.g., requireAttestationsBy) that references the attestor, otherwise no attestation enforcement occurs. Option C is incorrect because Cloud Build privilege escalation mode is unrelated to Binary Authorization signing or attestation. Option E is incorrect because Container Registry vulnerability scanning detects CVEs and does not provide the signing or attestation enforcement required by Binary Authorization.

Answer

Cloud Build with privilege escalation mode

Answer

Container Registry with vulnerability scanning enabled

Question 11

A team wants to implement a GitOps workflow for deploying applications to GKE. They want to use a tool that continuously reconciles the cluster state with a Git repository. Which TWO tools can they use? (Select TWO)

Accepted Answer

Argo CD. Argo CD is a declarative GitOps tool that continuously monitors a Git repository and automatically reconciles the cluster state to match the desired state defined in the repository. It directly supports the GitOps workflow requirement by polling or using webhooks to detect changes and applying them to GKE clusters.

Answer

Cloud Deploy

Answer

Cloud Build

Answer

Skaffold

Question 12

A DevOps team wants to alert when a Compute Engine instance is unreachable for 5 minutes. Which alerting condition type should be used?

Accepted Answer

Absent condition. An absent condition fires when a metric stops reporting for a specified duration, which is exactly the signal for an unreachable instance. If the instance is down or the agent stops sending the uptime metric, no data points arrive, and the absent condition triggers after the 5-minute window. Metric threshold conditions require data to evaluate and will not fire when data is missing.

Answer

Metric threshold condition

Answer

Logs-based alerting

Answer

Forecast condition

Question 13

Refer to the exhibit. A developer creates these tables and notices that queries joining Users and Orders on UserId are slow. What is the most likely cause?

Accepted Answer

Tables are not interleaved, so parent and child rows may be in different splits.. In Google Cloud Spanner, interleaving tables physically co-locates parent and child rows in the same tablet split, reducing cross-node lookups. Without interleaving, rows from Users and Orders may reside on different servers, causing distributed queries that are slower due to network round trips. Option C correctly identifies this as the most likely cause of slow joins.

Answer

The primary key of Orders should include UserId as a prefix for co-location.

Answer

The foreign key constraint is missing, causing full table scans.

Answer

The foreign key reference should be on the parent table.

Question 14

A company wants to centralize audit logs and billing data from multiple projects in a single project for analysis. What is the best approach?

Accepted Answer

Create a dedicated logging project, set up aggregated log sinks from all projects to that project, and export billing data to BigQuery in the same project. Centralizing audit logs and billing data from multiple projects into one project for analysis is best achieved by creating a dedicated logging project, configuring aggregated log sinks from all source projects to that project, and exporting billing data to BigQuery in the same project (C). This uses native log aggregation (sinks at the organization or folder level) and billing export to a single analytical destination, enabling unified querying and cost attribution without duplicating infrastructure per project.

Answer

Use Cloud Monitoring to view logs from all projects in one dashboard

Answer

Create a shared VPC project and enable VPC flow logs

Answer

Enable billing export to BigQuery in each project and query across projects

Question 15

Your Firestore database in Native mode contains a collection with millions of documents. You need to query documents where the 'tags' field (an array) contains the string 'urgent'. What must you ensure in your index configuration?

Accepted Answer

No additional index configuration is required; Firestore automatically creates the necessary index for array fields.. Firestore automatically creates a single-field index for array fields. However, to query array-contains, you need an index on the field with the array-contains filter. Firestore automatically creates a single-field index for the 'tags' field, so no additional index is needed. If the query includes additional equality clauses, a composite index may be required, but for a simple array-contains, it's automatic.

Answer

Ensure the 'tags' field is not indexed, and then create a composite index with the array-contains filter.

Answer

Create an index exemption for the 'tags' field to enable array queries.

Answer

Create a composite index on 'tags' and '__name__' for the collection.