Google PROFESSIONAL-CLOUD-DATABASE-ENGINEER Online Practice Questions and Exam Preparation

Google PROFESSIONAL-CLOUD-DATABASE-ENGINEER Online Questions & Answers

• Question 11:

  You support a consumer inventory application that runs on a multi-region instance of Cloud Spanner. A customer opened a support ticket to complain about slow response times. You notice a Cloud Monitoring alert about high CPU utilization. You want to follow Google-recommended practices to address the CPU performance issue. What should you do first?

  A. Increase the number of processing units.
  B. Modify the database schema, and add additional indexes.
  C. Shard data required by the application into multiple instances.
  D. Decrease the number of processing units.
  A. Increase the number of processing units.

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  Explanation/Reference:

  In case of high CPU utilization like, mentioned in question, refer: https://cloud.google.com/spanner/docs/identify-latency-point#:~:text=Check%20the%20CPU%20utilization%20of%20the%20instance.%20If%20th e%20CPU%20utilization%20of%20the%20instance%20is%20above%20the%20recommen ded%20level%2C%20you%20should%20manually%20add%20more%20nodes%2C%20or %20set%20up%20auto%20scaling. "Check the CPU utilization of the instance. If the CPU utilization of the instance is above the recommended level, you should manually add more nodes, or set up auto scaling." Indexes and schema are reviewed post identifying query with slow performance. Refer : https://cloud.google.com/spanner/docs/troubleshooting-performance-regressions#reviewschema

• Question 12:

  Your ecommerce application connecting to your Cloud SQL for SQL Server is expected to have additional traffic due to the holiday weekend. You want to follow Google-recommended practices to set up alerts for CPU and memory metrics so you can be notified by text message at the first sign of potential issues. What should you do?

  A. Use a Cloud Function to pull CPU and memory metrics from your Cloud SQL instance and to call a custom service to send alerts.
  B. Use Error Reporting to monitor CPU and memory metrics and to configure SMS notification channels.
  C. Use Cloud Logging to set up a log sink for CPU and memory metrics and to configure a sink destination to send a message to Pub/Sub.
  D. Use Cloud Monitoring to set up an alerting policy for CPU and memory metrics and to configure SMS notification channels.
  D. Use Cloud Monitoring to set up an alerting policy for CPU and memory metrics and to configure SMS notification channels.

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  Explanation/Reference:

  Cloud Monitoring collects metrics, events, and metadata from Google Cloud, Amazon Web Services (AWS), hosted uptime probes, and application instrumentation. Using the BindPlane service, you can also collect this data from over 150 common application components, on-premise systems, and hybrid cloud systems.

• Question 13:

  You use Python scripts to generate weekly SQL reports to assess the state of your databases and determine whether you need to reorganize tables or run statistics. You want to automate this report but need to minimize operational costs and overhead. What should you do?

  A. Create a VM in Compute Engine, and run a cron job.
  B. Create a Cloud Composer instance, and create a directed acyclic graph (DAG).
  C. Create a Cloud Function, and call the Cloud Function using Cloud Scheduler.
  D. Create a Cloud Function, and call the Cloud Function from a Cloud Tasks queue.
  C. Create a Cloud Function, and call the Cloud Function using Cloud Scheduler.

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  Explanation/Reference:

  Cloud Scheduler triggers actions at regular fixed intervals, whereas Cloud Tasks triggers actions based on how the individual task object is configured. Reference: https://cloud.google.com/tasks/docs/comp-tasks-sched

• Question 14:

  Your application uses Cloud SQL for MySQL. Your users run reports on data that relies on near-real time; however, the additional analytics caused excessive load on the primary database. You created a read replica for the analytics workloads, but now your users are complaining about the lag in data changes and that their reports are still slow. You need to improve the report performance and shorten the lag in data replication without making changes to the current reports. Which two approaches should you implement? (Choose two.)

  A. Create secondary indexes on the replica.
  B. Create additional read replicas, and partition your analytics users to use different read replicas.
  C. Disable replication on the read replica, and set the flag for parallel replication on the read replica. Re-enable replication and optimize performance by setting flags on the primary instance.
  D. Disable replication on the primary instance, and set the flag for parallel replication on the primary instance. Re-enable replication and optimize performance by setting flags on the read replica.
  E. Move your analytics workloads to BigQuery, and set up a streaming pipeline to move data and update BigQuery.
  B. Create additional read replicas, and partition your analytics users to use different read replicas.
  C. Disable replication on the read replica, and set the flag for parallel replication on the read replica. Re-enable replication and optimize performance by setting flags on the primary instance.

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  Explanation/Reference:

  Replication lag and slow report performance. E is eliminated because using BigQuery would mean changes to the current reports. Report slowness could be the result of poor indexing or just too much read load (or both!). Since excessive load is mentioned in the question, creating additional read replicas and spreading the analytics workload around makes B correct and eliminates A as a way to speed up reporting. That leaves the replication problem. Cloud SQL enables single threaded replication by default, so it stands to reason enabling parallel replication would help the lag. To do that you disable replication on the replica (not the primary), set flags on the replica and optionally set flags on the primary instance to optimize performance for parallel replication. That makes C correct and D incorrect. https://cloud.google.com/sql/docs/mysql/replication/manage-replicas#configuring-parallel-replication

• Question 15:

  Your company wants to migrate an Oracle-based application to Google Cloud. The application team currently uses Oracle Recovery Manager (RMAN) to back up the database to tape for long-term retention (LTR). You need a cost-effective backup and restore solution that meets a 2-hour recovery time objective (RTO) and a 15-minute recovery point objective (RPO). What should you do?

  A. Migrate the Oracle databases to Bare Metal Solution for Oracle, and store backups on tapes on-premises.
  B. Migrate the Oracle databases to Bare Metal Solution for Oracle, and use Actifio to store backup files on Cloud Storage using the Nearline Storage class.
  C. Migrate the Oracle databases to Bare Metal Solution for Oracle, and back up the Oracle databases to Cloud Storage using the Standard Storage class.
  D. Migrate the Oracle databases to Compute Engine, and store backups on tapes on-premises.
  B. Migrate the Oracle databases to Bare Metal Solution for Oracle, and use Actifio to store backup files on Cloud Storage using the Nearline Storage class.

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  Explanation/Reference:

  https://www.actifio.com/solutions/cloud/google/

• Question 16:

  Your company has PostgreSQL databases on-premises and on Amazon Web Services (AWS). You are planning multiple database migrations to Cloud SQL in an effort to reduce costs and downtime. You want to follow Google-recommended practices and use Google native data migration tools. You also want to closely monitor the migrations as part of the cutover strategy. What should you do?

  A. Use Database Migration Service to migrate all databases to Cloud SQL.
  B. Use Database Migration Service for one-time migrations, and use third-party or partner tools for change data capture (CDC) style migrations.
  C. Use data replication tools and CDC tools to enable migration.
  D. Use a combination of Database Migration Service and partner tools to support the data migration strategy.
  A. Use Database Migration Service to migrate all databases to Cloud SQL.

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  Explanation/Reference:

  https://cloud.google.com/blog/products/databases/tips-for-migrating-across-compatible-database-engines

• Question 17:

  You are managing a small Cloud SQL instance for developers to do testing. The instance is not critical and has a recovery point objective (RPO) of several days. You want to minimize ongoing costs for this instance. What should you do?

  A. Take no backups, and turn off transaction log retention.
  B. Take one manual backup per day, and turn off transaction log retention.
  C. Turn on automated backup, and turn off transaction log retention.
  D. Turn on automated backup, and turn on transaction log retention.
  C. Turn on automated backup, and turn off transaction log retention.

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  Explanation/Reference:

  https://cloud.google.com/sql/docs/mysql/backup-recovery/backups

• Question 18:

  You are writing an application that will run on Cloud Run and require a database running in the Cloud SQL managed service. You want to secure this instance so that it only receives connections from applications running in your VPC environment in Google Cloud. What should you do?

  A. 1. Create your instance with a specified external (public) IP address. 2. Choose the VPC and create firewall rules to allow only connections from Cloud Run into your instance. 3. Use Cloud SQL Auth proxy to connect to the instance.
  B. 1. Create your instance with a specified external (public) IP address. 2. Choose the VPC and create firewall rules to allow only connections from Cloud Run into your instance. 3. Connect to the instance using a connection pool to best manage connections to the instance.
  C. 1. Create your instance with a specified internal (private) IP address. 2. Choose the VPC with private service connection configured. 3. Configure the Serverless VPC Access connector in the same VPC network as your Cloud SQL instance. 4. Use Cloud SQL Auth proxy to connect to the instance.
  D. 1. Create your instance with a specified internal (private) IP address. 2. Choose the VPC with private service connection configured. 3. Configure the Serverless VPC Access connector in the same VPC network as your Cloud SQL instance. 4. Connect to the instance using a connection pool to best manage connections to the instance.
  D. 1. Create your instance with a specified internal (private) IP address. 2. Choose the VPC with private service connection configured. 3. Configure the Serverless VPC Access connector in the same VPC network as your Cloud SQL instance. 4. Connect to the instance using a connection pool to best manage connections to the instance.

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  Explanation/Reference:

  https://cloud.google.com/sql/docs/mysql/connect-run#configure https://cloud.google.com/sql/docs/mysql/connect-run#connection-pools

• Question 19:

  You are running a transactional application on Cloud SQL for PostgreSQL in Google Cloud. The database is running in a high availability configuration within one region. You have encountered issues with data and want to restore to the last known pristine version of the database. What should you do?

  A. Create a clone database from a read replica database, and restore the clone in the same region.
  B. Create a clone database from a read replica database, and restore the clone into a different zone.
  C. Use the Cloud SQL point-in-time recovery (PITR) feature. Restore the copy from two hours ago to a new database instance.
  D. Use the Cloud SQL database import feature. Import last week's dump file from Cloud Storage.
  C. Use the Cloud SQL point-in-time recovery (PITR) feature. Restore the copy from two hours ago to a new database instance.

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  Explanation/Reference:

  Using import/export from last week is slow for large scale databases and will restore database from last week.

• Question 20:

  You are running a large, highly transactional application on Oracle Real Application Cluster (RAC) that is multi-tenant and uses shared storage. You need a solution that ensures high-performance throughput and a low-latency connection between applications and databases. The solution must also support existing Oracle features and provide ease of migration to Google Cloud. What should you do?

  A. Migrate to Compute Engine.
  B. Migrate to Bare Metal Solution for Oracle.
  C. Migrate to Google Kubernetes Engine (GKE)
  D. Migrate to Google Cloud VMware Engine
  B. Migrate to Bare Metal Solution for Oracle.

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  Explanation/Reference:

  Oracle is neither licensed nor supported in GCE. The only platform which supports RAC and all existing Oracle features is BMS.