PCDE Practice Test 3 — 30 Questions

Question 1

You are running a Cloud Bigtable instance for time-series data ingestion. Write throughput has dropped significantly, and you see an increase in 'resource exhausted' errors. The table has one column family and one rowkey format: `#orgId#deviceId#timestamp`. After analyzing cluster metrics, you see that one node is handling most of the traffic. What is the most likely cause?

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

Accepted Answer

The rowkey design is causing hotspotting on one tablet node due to a prefix (orgId) being written heavily.. The rowkey design `#orgId#deviceId#timestamp` causes hotspotting because all writes for a given `orgId` are directed to a single tablet node. Cloud Bigtable partitions data by rowkey range, and sequential or heavily skewed prefixes (like `orgId`) concentrate write traffic on one node, leading to 'resource exhausted' errors and throughput degradation.

Answer

The column family design is creating too many columns.

Answer

The cluster does not have enough nodes.

Answer

The timestamp is too granular, causing many rows with the same timestamp.

Question 2

An SRE team wants to alert when the error budget burn rate exceeds 14x the allowed rate over a 1-hour window. Which Cloud Monitoring alert policy configuration is appropriate?

Accepted Answer

Alert on error budget burn rate > 14 over a 1-hour window. For fast burn alert, use a 1-hour window with a burn rate threshold of 14. The burn rate is calculated as the ratio of actual failures to the allowed error budget per time unit.

Answer

Alert on error budget burn rate > 14 over a 6-hour window

Answer

Alert on error budget burn rate > 5 over a 1-hour window

Answer

Alert on error budget burn rate > 8 over a 2-hour window

Question 3

A company wants to enforce that only container images signed by their CI/CD pipeline can be deployed to GKE. Which two services should they use together?

Accepted Answer

Binary Authorization and Container Analysis. Binary Authorization enforces that only container images signed by trusted authorities (like a CI/CD pipeline) can be deployed to GKE. Container Analysis (now part of Artifact Analysis) scans images for vulnerabilities and stores attestations, which Binary Authorization uses to verify signatures before allowing deployment. Together, they provide a complete enforcement chain: signing during CI/CD and verification at deploy time.

Answer

Cloud Build and Artifact Registry

Answer

Security Command Center and Artifact Registry

Answer

Cloud Deploy and Cloud Run

Question 4

A company uses Cloud Build to deploy to Cloud Run. They need to test a new revision with a specific tag without serving any live traffic. After validation, they want to shift 10% of traffic to the new revision. Which two gcloud commands should they use?

Accepted Answer

gcloud run deploy --image ... --no-traffic --tag=test; gcloud run services update-traffic ... --to-revisions=test=10. The `--no-traffic` flag deploys the new revision without routing any live traffic to it, while `--tag=test` assigns a specific tag (e.g., 'test') that allows direct URL-based validation. The second command `gcloud run services update-traffic --to-revisions=test=10` then shifts exactly 10% of traffic to that tagged revision, enabling a gradual rollout. This two-step approach ensures the revision is validated before receiving production traffic.

Answer

gcloud run deploy --image ... --no-traffic; gcloud run services update-traffic ... --to-latest=10

Answer

gcloud run deploy --image ... --traffic=10%; gcloud run revisions delete

Answer

gcloud run deploy --image ... --tag=test; gcloud run services update-traffic ... --to-revisions=test=100

Question 5

Refer to the exhibit. A company wants to perform point-in-time recovery (PITR) for their Cloud SQL MySQL instance. Is PITR enabled?

Accepted Answer

Yes, because binaryLogEnabled is true.. Cloud SQL MySQL uses binary logging to enable point-in-time recovery (PITR). When `binaryLogEnabled` is set to `true`, the instance logs all changes, allowing restoration to any specific point within the configured transaction log retention period. The `pointInTimeRecoveryEnabled` field is not a valid Cloud SQL configuration parameter; instead, PITR is implicitly enabled when binary logging is active.

Answer

No, because PITR requires the backupConfiguration to have 'pointInTimeRecoveryEnabled: true'.

Answer

No, because transactionLogRetentionDays is set to 7.

Answer

Yes, because enabled is true.

Question 6

A team wants to implement an on-call rotation using Cloud Monitoring and third-party tools. Which three components are essential for setting up on-call alerting? (Choose THREE.)

Accepted Answer

An escalation policy. Essential components: alerting policy to trigger notifications, notification channel to reach on-call engineers, and escalation policy to handle unacknowledged alerts. A dashboard and runbook are helpful but not essential for the on-call rotation itself.

Answer

A Cloud Monitoring dashboard

Answer

A runbook for incident response

Question 7

During a cutover from MySQL to Cloud SQL, the team must minimize downtime. Which THREE steps are essential for a successful cutover with minimal data loss?

Accepted Answer

Verify that DMS replication lag is zero.. Quiesce writes to stop changes, verify replication lag is zero to ensure all changes are applied, then promote the destination to make it writable. Updating connection strings and testing are also needed but the three essential steps for data integrity are quiescing, verifying lag, and promoting.

Answer

Enable point-in-time recovery on the destination.

Answer

Take a full backup of the source after quiescing.

Question 8

A company notices that their Cloud SQL for PostgreSQL instance, as shown in the exhibit, frequently runs out of storage, causing downtime. They have set up automated backups with point-in-time recovery. What is the most likely cause of the storage issue?

Accepted Answer

Transaction logs for point-in-time recovery are consuming disk space.. Cloud SQL for PostgreSQL uses transaction logs (WAL files) to enable point-in-time recovery (PITR). These logs accumulate on the disk until they are automatically removed, but if the rate of log generation exceeds the cleanup rate or if the backup retention period is long, the logs can fill the disk, causing storage exhaustion and downtime.

Answer

The activation policy is set to ALWAYS, causing continuous writes.

Answer

The instance tier (db-custom-4-15360) is too low for the workload.

Answer

The data disk type (PD_SSD) is not suitable for PostgreSQL.

Question 9

A company is running a MySQL database on Cloud SQL and needs to optimize for high random read/write performance. Which storage type should they choose?

Accepted Answer

SSD persistent disk. SSD persistent disk provides consistent low-latency performance for random read/write operations, which is critical for MySQL databases on Cloud SQL. It offers higher IOPS and throughput compared to HDD or balanced persistent disks, making it the optimal choice for high random read/write workloads.

Answer

Local SSD

Answer

Balanced persistent disk

Answer

HDD persistent disk

Question 10

A company uses Cloud Bigtable for a real-time analytics pipeline. They have configured replication with a primary cluster in us-central1 and a secondary cluster in us-west1. They want to minimize data loss during a failover to the secondary cluster. What is the best approach to achieve the lowest possible RPO?

Accepted Answer

Use multi-cluster routing with read-failover enabled and direct all writes to the primary cluster.. Bigtable replication is asynchronous, so RPO is determined by replication lag. To minimize data loss, you should route writes to the primary cluster and use read-failover routing to consume from the secondary only when primary is unhealthy. During failover, switch writes to secondary manually.

Answer

Use single-cluster routing with failover priority set to the secondary cluster.

Answer

Use any-replica routing and let Cloud Bigtable automatically direct reads and writes to the healthiest cluster.

Answer

Use single-cluster routing and regularly back up the Bigtable data.

Question 11

A team is designing a relational schema for a new application on Cloud SQL. The schema includes a table 'Orders' and a table 'Customers'. Each order belongs to one customer. The team anticipates high write throughput and needs to enforce referential integrity. Which schema design is most appropriate?

Accepted Answer

Use a foreign key constraint from Orders.customer_id to Customers.customer_id. Using a foreign key constraint from Orders.customer_id to Customers.customer_id enforces referential integrity at the database level, which is essential for maintaining data consistency in a relational schema. Cloud SQL (e.g., MySQL or PostgreSQL) natively supports foreign key constraints, ensuring that every order references an existing customer without relying on application logic. This approach is efficient for high write throughput as the database handles the check atomically, avoiding race conditions.

Answer

Use Cloud Spanner interleaved tables with Orders as a child of Customers

Answer

Implement referential integrity checks in the application code and omit database constraints

Answer

Store order data as a JSON array in a column of the Customers table

Question 12

An organization wants to implement a blameless postmortem culture after incidents. Which of the following is a key practice in blameless postmortems?

Accepted Answer

Identifying contributing factors using techniques like the 5 Whys. Blameless postmortems focus on identifying contributing factors and systemic issues, not individual blame. The 5 Whys technique helps uncover root causes.

Answer

Firing the responsible engineer to prevent recurrence

Answer

Assigning blame to the engineer who made the mistake

Answer

Immediately implementing a fix without documentation

Question 13

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. Binary Authorization requires images to be signed (e.g., using Cloud Key Management Service or Signify), an attestor that verifies signatures, and an admission controller (Binary Authorization) that enforces the policy on the cluster.

Answer

Cloud Build with privilege escalation mode

Answer

Container Registry with vulnerability scanning enabled

Question 14

An organization wants to restrict the creation of Cloud SQL instances outside of specific regions. Which organization policy constraint should they use?

Accepted Answer

`resourceLocations`. The `resourceLocations` constraint is the correct organization policy to restrict Cloud SQL instance creation to specific regions. This policy defines a list of allowed locations (e.g., `us-central1`, `europe-west1`) where all resources, including Cloud SQL instances, can be created. By setting this constraint at the organization, folder, or project level, any attempt to create a Cloud SQL instance outside the permitted regions will be denied.

Answer

`compute.requireShieldedVm`

Answer

`iam.disableServiceAccountKeyCreation`

Answer

`sql.restrictPublicIp`

Question 15

A team uses Skaffold for local development and wants to integrate it into their CI/CD pipeline on Cloud Build for continuous deployment to GKE. What is the recommended approach?

Accepted Answer

Use 'skaffold run' in a Cloud Build step. Skaffold can be run as a step in cloudbuild.yaml. It handles building, tagging, and deploying based on skaffold.yaml configuration. Using 'skaffold run' in a Cloud Build step is the standard integration.

Answer

Use Cloud Build's built-in kubectl deployer

Answer

Run 'skaffold dev' in the Cloud Build step

Answer

Convert skaffold.yaml to a Helm chart

Question 16

A company is designing a disaster recovery strategy for their Cloud Spanner database. They need an RPO of less than 30 seconds and an RTO of less than 1 minute. Which two configurations would meet these requirements? (Choose TWO)

Accepted Answer

Multi-region configuration with read-write replicas (e.g., nam3). The correct answers are B and D. A multi-region configuration with read-write replicas (e.g., nam3) provides automatic failover across regions with an RPO of approximately 15 seconds and an RTO of less than 1 minute, meeting the requirements for region-level failures. A regional instance in Cloud Spanner provides synchronous replication within the region, achieving an RPO of zero and an RTO of seconds, which meets the requirements for zone-level failures within a region. Option A (cross-region backup and restore) typically has an RPO of hours and RTO of hours, so it does not meet the strict RPO/RTO. Option C (point-in-time recovery) provides RPO of seconds to minutes but depends on backups and may not achieve RTO <1 minute for restore operations. Option E (multi-region with read-only replicas) does not support automatic failover because read-only replicas cannot become the new leader, so failover is not automatic and RTO would be longer.

Answer

Cross-region backup and restore

Answer

Point-in-time recovery (PITR)

Answer

Multi-region configuration with read-only replicas

Question 17

You are designing a Firestore database for a chat application. Documents will store messages with fields: senderId, messageText, timestamp, conversationId. To efficiently retrieve the most recent 50 messages in a conversation, which index should you create?

Accepted Answer

A composite index on (conversationId, timestamp, __name__) descending. To efficiently retrieve the most recent 50 messages for a specific conversation, you need a composite index on (conversationId, timestamp, __name__) with descending order. This allows Firestore to perform a range query on conversationId and then order by timestamp descending, using the index to skip scanning irrelevant documents. The __name__ field is included to ensure the index is covering and to handle document name ordering ties, which is required for consistent pagination with descending order.

Answer

A single-field index on timestamp

Answer

An index on conversationId only

Answer

A composite index on (senderId, timestamp)

Question 18

A company is using DMS to migrate a MySQL database to Cloud SQL with continuous replication. During the CDC phase, the replication lag is increasing and not catching up. The source database is heavily used for OLTP workloads. Which action would most likely reduce the replication lag?

Accepted Answer

Reduce the number of concurrent write operations on the source database.. Increasing the source database's binary log retention period does not reduce lag; it retains more logs. Reducing concurrent writes on source directly slows the rate of change, allowing DMS to catch up.

Answer

Increase the size of the Cloud SQL destination instance.

Answer

Increase the binary log retention period on the source.

Answer

Enable parallel replication on DMS.

Question 19

Which TWO data types are supported in Cloud Spanner schemas?

Accepted Answer

ARRAY. ARRAY is a supported data type in Cloud Spanner, allowing you to store ordered lists of elements of the same primitive type (e.g., ARRAY, ARRAY). This is essential for modeling one-to-many relationships without requiring separate tables, and it integrates seamlessly with Cloud Spanner's query engine for array operations.

Answer

GEOMETRY

Answer

TEXT

Answer

TINYINT

Question 20

A financial services company uses BigQuery to run complex analytical queries on trading data. They notice that a particular query joining a large fact table (10 TB) with a small dimension table (100 MB) is slow. The fact table is partitioned by date and clustered by symbol. The dimension table is not partitioned. The query filters on a specific date range and a few symbols. Which optimization is MOST likely to improve query performance?

Accepted Answer

Enable automatic query rewriting to use clustering keys for pruning on the dimension table join.. BigQuery's automatic query rewriting can leverage clustering keys from the fact table to prune the join, even though the dimension table is not clustered. When the query filters on a specific date range and symbols, BigQuery can use the fact table's clustering on symbol to skip irrelevant blocks during the join, reducing data scanned and improving performance. This optimization is automatic and does not require manual denormalization or repartitioning.

Answer

Denormalize the dimension table into the fact table.

Answer

Partition the dimension table by its primary key.

Answer

Cluster the dimension table on its primary key.