Google Professional Cloud Database Engineer Exam Practice Test Instant Access

Question 1

Your team uses thousands of connected IoT devices to collect device maintenance data for your oil and gas customers in real time. You want to design inspection routines, device repair, and replacement schedules based on insights gathered from the data produced by these devices. You need a managed solution that is highly scalable, supports a multi-cloud strategy, and offers low latency for these IoT devices. What should you do?

AUse Firestore with Looker.

BUse Cloud Spanner with Data Studio.

CUse MongoD8 Atlas with Charts.

DUse Bigtable with Looker.

Answer : C

This scenario has BigTable written all over it - large amounts of data from many devices to be analysed in realtime. I would even argue it could qualify as a multicloud solution, given the links to HBASE. BUT it does not support SQL queries and is not therefore compatible (on its own) with Looker. Firestore + Looker has the same problem. Spanner + Data Studio is at least a compatible pairing, but I agree with others that it doesn't fit this use-case - not least because it's Google-native. By contrast, MongoDB Atlas is a managed solution (just not by Google) which is compatible with the proposed reporting tool (Mongo's own Charts), it's specifically designed for this type of solution and of course it can run on any cloud.

Question 2

Your customer has a global chat application that uses a multi-regional Cloud Spanner instance. The application has recently experienced degraded performance after a new version of the application was launched. Your customer asked you for assistance. During initial troubleshooting, you observed high read latency. What should you do?

AUse query parameters to speed up frequently executed queries.

BChange the Cloud Spanner configuration from multi-region to single region.

CUse SQL statements to analyze SPANNER_SYS.READ_STATS* tables.

DUse SQL statements to analyze SPANNER_SYS.QUERY_STATS* tables.

Answer : C

To troubleshoot high read latency, you can use SQL statements to analyze the SPANNER_SYS.READ_STATS* tables. These tables contain statistics about read operations in Cloud Spanner, including the number of reads, read latency, and the number of read errors. By analyzing these tables, you can identify the cause of the high read latency and take appropriate action to resolve the issue. Other options, such as using query parameters to speed up frequently executed queries or changing the Cloud Spanner configuration from multi-region to single region, may not be directly related to the issue of high read latency. Similarly, analyzing the SPANNER_SYS.QUERY_STATS* tables, which contain statistics about query operations, may not be relevant to the issue of high read latency.

Question 3

Your application follows a microservices architecture and uses a single large Cloud SQL instance, which is starting to have performance issues as your application grows. in the Cloud Monitoring dashboard, the CPU utilization looks normal You want to follow Google-recommended practices to resolve and prevent these performance issues while avoiding any major refactoring. What should you do?

AUse Cloud Spanner instead of Cloud SQL.

BIncrease the number of CPUs for your instance.

CIncrease the storage size for the instance.

DUse many smaller Cloud SQL instances.

Answer : D

https://cloud.google.com/sql/docs/mysql/best-practices#data-arch

Question 4

You are working on a new centralized inventory management system to track items available in 200 stores, which each have 500 GB of dat

a. You are planning a gradual rollout of the system to a few stores each week. You need to design an SQL database architecture that minimizes costs and user disruption during each regional rollout and can scale up or down on nights and holidays. What should you do?

AUse Oracle Real Application Cluster (RAC) databases on Bare Metal Solution for Oracle.

BUse sharded Cloud SQL instances with one or more stores per database instance.

CUse a Biglable cluster with autoscaling.

DUse Cloud Spanner with a custom autoscaling solution.

Answer : D

https://cloud.google.com/spanner/docs/autoscaling-overview

1. CloudSQL max out at 64TB, so unable to told 100TB of data. https://cloud.google.com/sql/docs/quotas#metrics_collection_limit 2. Scale is done manually on SQL Cloud

Question 5

Your company wants you to migrate their Oracle, MySQL, Microsoft SQL Server, and PostgreSQL relational databases to Google Cloud. You need a fully managed, flexible database solution when possible. What should you do?

AMigrate all the databases to Cloud SQL.

BMigrate the Oracle, MySQL, and Microsoft SQL Server databases to Cloud SQL, and migrate the PostgreSQL databases to Compute Engine.

CMigrate the MySQL, Microsoft SQL Server, and PostgreSQL databases to Compute Engine, and migrate the Oracle databases to Bare Metal Solution for Oracle.

DMigrate the MySQL, Microsoft SQL Server, and PostgreSQL databases to Cloud SQL, and migrate the Oracle databases to Bare Metal Solution for Oracle.

Answer : D

Question 6

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?

A1. 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.

B1. 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.

C1. 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.

D1. 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.

Answer : D

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

Question 7

You are migrating critical production database from Amazon RDS for MySQL to Cloud SQL for MYSQL by using Google Cloud's Migration Service.

You want to keep disruption to your production database to minimum and, at the same time, optimize migration performance. What should you do?

ACreate and start multiple Database Migration Service jobs to migrate your database to the target Cloud SQL for MySQL instance.

BUpgrade the Amazon RDS for MySQL primary instance to an instance with more vCPUs and memory, and then run Google Cloud's Database Migration Service.

CCreate a single Database Migration Service migration job with initial load parallelism configured to maximum on the source Amazon RDS for MySQL read replica.

DCreate a single Database Migration Service migration job with initial Load Parallelism configured to Maximum on the Amazon RDS for MySQL primary instance.

Answer : C