PCD Practice Exam 55 — 20 Questions

Question 1

A developer wants to automatically capture CPU and memory profiles from a production application running on Compute Engine to identify performance bottlenecks. Which Google Cloud tool should they use?

Accepted Answer

Cloud Profiler. Cloud Profiler is the correct tool because it continuously gathers CPU and memory usage data from production applications with minimal overhead, using statistical sampling to identify which functions or methods consume the most resources. This allows developers to pinpoint performance bottlenecks without adding significant latency or requiring code changes.

Answer

Cloud Logging

Answer

Cloud Monitoring

Answer

Cloud Trace

Question 2

A financial trading application uses Cloud Spanner for order processing. To reduce latency for read-heavy operations, the team wants to allow stale reads with a bounded staleness of 10 seconds. Which Spanner API or method should they use to achieve this?

Accepted Answer

Use the `timestamp_bound` parameter with `max_staleness` set to 10 seconds. Spanner supports stale reads (bounded staleness) by setting a read timestamp. The read timestamp can be set to a past time within the maximum staleness. The `max_staleness` option in the client libraries or the `read_timestamp` parameter in gRPC API allow bounded staleness.

Answer

Set the session to read-only mode

Answer

Configure an index with the `STORING` clause to avoid index joins

Answer

Use mutations API instead of DML for writes

Question 3

An application running on Compute Engine uses Cloud Storage for storing user-uploaded images. During load testing, the application experiences high latency when reading images. The developer suspects that the application is making too many small read requests. Which approach should the developer take to optimize performance?

Accepted Answer

Increase the read size to reduce the number of API requests.. The high latency is caused by many small read requests, each incurring API overhead. By increasing the read size (e.g., reading larger chunks or using range requests), the application reduces the number of API calls, which lowers cumulative latency and improves throughput. This directly addresses the root cause of excessive small reads.

Answer

Enable Cloud CDN to cache the images at edge locations.

Answer

Rewrite the objects to use a different storage class.

Answer

Mount the Cloud Storage bucket using Cloud Storage FUSE and read files from the local filesystem.

Question 4

A company is deploying a containerized application on Google Kubernetes Engine (GKE). The development team has built a Docker image and pushed it to Artifact Registry. They want to automate the deployment process so that whenever a new image is pushed to the registry, the application is automatically updated in the GKE cluster. Which combination of services should they use to achieve this?

Accepted Answer

Set up a Cloud Build trigger that monitors the Artifact Registry and runs a build step to update the GKE deployment using kubectl.. Cloud Build can be configured with a trigger that monitors Artifact Registry for new image pushes. When a new image is pushed, the trigger executes a build step that uses kubectl to update the GKE deployment, enabling continuous deployment without manual intervention.

Answer

Use Cloud Deploy to create a delivery pipeline that watches the Artifact Registry and promotes the image to GKE.

Answer

Schedule a Cloud Scheduler job that periodically checks for new images in Artifact Registry and updates the GKE deployment.

Answer

Configure a Cloud Run service that is automatically deployed when a new image is pushed to Artifact Registry.

Question 5

A development team needs a serverless NoSQL document database for a new mobile application that requires offline synchronization for users. The database should scale automatically and integrate with Firebase Authentication. Which Google Cloud database meets these requirements?

Accepted Answer

Firestore. Firestore provides serverless NoSQL document storage, automatic scaling, offline sync, and integration with Firebase Authentication.

Answer

Memorystore for Redis

Answer

Cloud SQL

Answer

Cloud Bigtable

Question 6

A team is building a mobile backend on Google Cloud using Cloud Endpoints with Firebase Authentication. They want to protect their API from abuse by implementing rate limiting per user. What approach should they take?

Accepted Answer

Use Apigee API Management as a proxy to enforce rate limiting per developer app.. Apigee API Management is the correct choice because it provides built-in rate limiting policies that can be enforced per developer app, which maps directly to per-user rate limiting when Firebase Authentication is used. Cloud Endpoints does not natively support per-user rate limiting; it relies on the backend to implement such logic, which is not a managed solution. Apigee acts as a proxy that can inspect the Firebase-issued JWT token to identify the user and apply rate limits accordingly, offloading this concern from the backend code.

Answer

Implement rate limiting in the backend code and enforce it via Cloud Endpoints.

Answer

Configure Cloud Armor with a rule to block requests from users exceeding a threshold.

Answer

Use Cloud CDN with a cache key based on the user ID.

Question 7

A developer needs to connect a Cloud SQL MySQL instance from an application running on Compute Engine without whitelisting IP addresses. Which method should they use?

Accepted Answer

Configure the application to use Cloud SQL Auth Proxy.. Cloud SQL Auth Proxy provides secure access using IAM permissions, avoiding the need to whitelist IP addresses. SSL without proxy still requires IP allowlisting. Private IP requires VPC peering and is not automatically connected. Cloud Shell is not for application connectivity.

Answer

Connect via Cloud Shell using the mysql client.

Answer

Set up a Cloud SQL private IP connection.

Answer

Use SSL/TLS connection with the public IP address.

Question 8

A company has a multi-region deployment of their application on GKE. They need to monitor service-level indicators (SLIs) like availability and latency across regions. They want a single pane of glass to view SLO compliance. What should they use?

Accepted Answer

Cloud Monitoring SLO monitoring. Cloud Monitoring SLO monitoring is the correct choice because it provides a unified dashboard (single pane of glass) to define, track, and visualize service-level indicators (SLIs) such as availability and latency across multiple GKE regions. It allows you to set SLO targets, monitor compliance over time, and receive alerts when the error budget is depleted, all within a single monitoring view.

Answer

Cloud Logging with log-based metrics

Answer

Cloud Profiler cross-region profiles

Answer

Cloud Trace multi-region traces

Question 9

A developer needs to connect a Cloud Run application to a Cloud SQL for MySQL database securely without managing IP allowlists or SSL certificates. Which method should they use?

Accepted Answer

Deploy the Cloud SQL Auth Proxy as a sidecar container in Cloud Run.. The Cloud SQL Auth Proxy provides secure authentication and encryption without requiring authorized networks or SSL certificate management. It uses IAM for authentication and encrypts connections.

Answer

Create a Compute Engine instance with a VPN to Cloud SQL and connect from Cloud Run via VPC peering.

Answer

Use the public IP of the Cloud SQL instance and add the Cloud Run service's IP range to the authorized networks.

Answer

Enable the 'require_ssl' flag and distribute the server certificate to the Cloud Run service.

Question 10

A company uses Cloud Bigtable for real-time user sessions. They need to back up Bigtable data to another region for disaster recovery, with the ability to restore to a specific point in time within the last week. Which backup strategy should they choose?

Accepted Answer

Enable Bigtable managed backups with a retention policy of 7 days and a restore to another cluster.. Bigtable's managed backups (also called backups) allow you to create backups with a retention policy (up to 7 days for point-in-time recovery). These backups can be restored to a different cluster, even in a different region, enabling cross-region disaster recovery. This meets the requirement for point-in-time recovery within the last week. Option A correctly describes this strategy. Options B, C, and D either introduce unnecessary steps or do not provide point-in-time recovery.

Answer

Use Bigtable managed backups with a 7-day retention, and restore to a cluster in the same region; then replicate to the DR region.

Answer

Use Bigtable replication across two instances in different regions, with a scheduled script to take snapshots.

Answer

Export Bigtable data to GCS using a Dataflow template daily, and store backups with object lifecycle management.

Question 11

Which two strategies should be implemented to ensure high availability for a Compute Engine instance group running a stateless web application?

Accepted Answer

Use regional managed instance group. Regional managed instance groups (MIGs) distribute instances across multiple zones within a region, providing automatic healing and high availability by recovering from zone failures. Combined with a global load balancer, they ensure traffic is routed only to healthy instances, making them ideal for stateless web applications that require resilience against zonal outages.

Answer

Use preemptible VMs

Answer

Use global load balancing

Answer

Use instance templates

Question 12

Your company runs a global e-commerce platform that requires strong consistency for transactions and the ability to scale writes horizontally. You are evaluating database options. Which TWO Google Cloud databases meet these requirements? (Choose 2)

Accepted Answer

Firestore. Cloud Spanner provides strong consistency and horizontal scaling globally, making it ideal for a global e-commerce platform. Firestore is a NoSQL database that also offers strong consistency and automatic horizontal scaling for writes, meeting the requirement for write scalability. AlloyDB, while providing strong consistency, does not scale writes horizontally; it relies on a single primary for writes. Cloud SQL and Bigtable do not meet both requirements: Cloud SQL lacks horizontal write scaling, and Bigtable does not provide strong consistency.

Answer

Cloud SQL

Answer

AlloyDB

Answer

Bigtable

Question 13

A company uses Cloud Spanner for a financial application. They need to ensure strong global consistency but also minimize latency for writes. What schema design should they use?

Accepted Answer

Use parent-child table relationships with interleaved tables. Interleaved tables in Cloud Spanner physically co-locate parent and child rows on the same split, reducing cross-node coordination for strongly consistent reads and writes. This minimizes write latency by ensuring that related data is stored together, avoiding distributed transaction overhead for operations that span parent-child relationships.

Answer

Use secondary indexes

Answer

Use commit timestamps

Answer

Use a single table with interleaved indexes

Question 14

A company is migrating a MySQL 5.7 database to Cloud SQL for MySQL 8.0. They have many queries using GROUP BY that return different results in 8.0. What is the most likely cause?

Accepted Answer

The sql_mode is different between MySQL 5.7 and 8.0.. MySQL 8.0 defaults to strict SQL mode, which disables the MySQL 5.7 non-standard GROUP BY behavior (GROUP BY can select nonaggregated columns not in GROUP BY). In 8.0, this causes errors or different results unless the sql_mode includes ONLY_FULL_GROUP_BY.

Answer

The character set changed from utf8 to utf8mb4.

Answer

The authentication plugin changed from mysql_native_password to caching_sha2_password.

Answer

The storage engine changed from MyISAM to InnoDB.

Question 15

A developer is using Cloud Logging and wants to export logs from a specific project to BigQuery for long-term analysis. They have created a log sink and given the appropriate permissions, but logs are not appearing in BigQuery. What is the most likely cause?

Accepted Answer

The service account used for the sink does not have the 'bigquery.dataEditor' role.. The log sink uses a service account to write logs to BigQuery. Even if the sink is configured correctly, the service account must have the 'bigquery.dataEditor' role on the destination dataset to insert log entries. Without this role, the sink will fail silently, and logs will not appear in BigQuery.

Answer

The sink's filter is too restrictive and no logs match.

Answer

The sink's destination BigQuery dataset is in a different region than the logs.

Answer

The log entries are not in JSON format.

Question 16

Which of the following is NOT a valid use case for Cloud Bigtable?

Accepted Answer

Serving as a transaction processing database for an e-commerce website. Cloud Bigtable is a NoSQL, wide-column database optimized for high-throughput, low-latency analytical and operational workloads, but it does not support multi-row transactions or ACID guarantees. Therefore, it is not suitable as a transaction processing database for an e-commerce website, which requires strong consistency and transactional integrity for order management and inventory updates.

Answer

Analyzing ad-tech clickstream data

Answer

Storing time-series data from IoT sensors

Answer

Powering a financial market data feed with millisecond latency

Question 17

A developer is debugging a Cloud Function that fails with a timeout. The function makes multiple synchronous external API calls. What is the best way to improve performance and avoid timeouts?

Accepted Answer

Use Cloud Tasks to offload the API calls asynchronously.. Cloud Tasks is the best choice because it allows you to offload synchronous external API calls to be executed asynchronously, decoupling the Cloud Function from the slow external services. This prevents the function from timing out while waiting for responses, and Cloud Tasks handles retries and scheduling automatically, improving overall reliability and performance.

Answer

Increase the timeout of the Cloud Function to the maximum of 9 minutes.

Answer

Use Firestore transactions to batch API calls.

Answer

Use Pub/Sub to trigger another function for each API call.

Question 18

Your Bigtable cluster is experiencing high latency for a table that stores IoT sensor data. The row key format is deviceID#timestamp. You discover that most reads query the last hour of data for a few devices. How can you optimize row key design to improve read performance?

Accepted Answer

Reverse the timestamp in the row key (e.g., deviceID#MAXTIME - timestamp). Reversing the timestamp (e.g., deviceID#MAXTIME - timestamp) ensures that for a given deviceID, the most recent data appears first in the lexicographic order of row keys. This allows reads querying the last hour of data to perform a contiguous range scan on a small set of rows, reducing read latency. It does not improve write distribution (all rows for a device still hash to the same tablet), but the read performance benefit is significant for this workload.

Answer

Separate frequently accessed data into a different column family

Answer

Use a single table with a composite key including device type

Answer

Add a salt prefix to the row key

Question 19

A financial services firm needs a database for real-time fraud detection. The workload requires sub-millisecond read latency on transactions and the ability to run complex SQL analytics on the same data. Which database should they choose?

Accepted Answer

AlloyDB. AlloyDB is correct because it combines PostgreSQL-compatible SQL analytics with sub-millisecond read latency for transactional workloads, using a columnar engine for analytical queries and a memory-optimized row store for real-time transactions. This dual-engine architecture allows the same data to serve both OLTP and OLAP requirements without data movement or latency trade-offs.

Answer

BigQuery

Answer

Cloud Bigtable

Answer

Cloud Spanner

Question 20

A company is migrating from MySQL 5.7 to Cloud SQL for MySQL 8.0. They have stored procedures that use GROUP BY with non-aggregated columns. In MySQL 5.7, this is allowed. What change might they need to make?

Accepted Answer

Use ANY_VALUE() for non-aggregated columns in SELECT. MySQL 8.0 enables strict SQL mode by default and the ONLY_FULL_GROUP_BY mode, which disallows SELECTing non-aggregated columns not in GROUP BY. The procedures must be updated to comply or SQL mode changed.

Answer

Switch to Cloud Spanner

Answer

Downgrade to MySQL 5.7 on Cloud SQL

Answer

No changes needed; MySQL 8.0 is backward compatible