Online Questions - Valid Practice To your Professional-Cloud-Database-Engineer Exam (Updated 220 Questions)
Practice To Professional-Cloud-Database-Engineer - Remarkable Practice On your Google Cloud Certified - Professional Cloud Database Engineer Exam
To be eligible for the Google Professional-Cloud-Database-Engineer certification exam, you must have at least three years of experience in managing databases on a cloud platform, including one year of experience in designing and implementing databases on Google Cloud. You should also have a good understanding of database concepts and technologies, such as SQL, NoSQL, and database management systems. Additionally, you should have hands-on experience with Google Cloud Platform services related to databases, such as Cloud SQL, Cloud Spanner, and Cloud Bigtable.
Google Professional-Cloud-Database-Engineer exam comprises of multiple choice and scenario-based questions, and it requires a thorough understanding of GCP database services. Professional-Cloud-Database-Engineer exam is designed to test the candidate’s ability to design, develop, and administer GCP databases in a real-world scenario. Professional-Cloud-Database-Engineer exam is conducted online, and the candidates are given a time limit of 2 hours to complete it. The passing score for the exam is 70%, and the certification is valid for two years.
NEW QUESTION # 25
Your company is developing a new global transactional application that must be ACID-compliant and have 99.999% availability. You are responsible for selecting the appropriate Google Cloud database to serve as a datastore for this new application. What should you do?
- A. Use Cloud Spanner.
- B. Use Cloud SQL.
- C. Use Bigtable.
- D. Use Firestore.
Answer: A
Explanation:
99,999% availability and global - it's either Spanner or Firestore, but 'transactional' eliminates Firestore
NEW QUESTION # 26
You are managing multiple applications connecting to a database on Cloud SQL for PostgreSQL. You need to be able to monitor database performance to easily identify applications with long-running and resource-intensive queries. What should you do?
- A. Use log messages produced by Cloud SQL.
- B. Use the Cloud Monitoring dashboard with available metrics from Cloud SQL.
- C. Use Query Insights for Cloud SQL.
- D. Use Cloud SQL instance monitoring in the Google Cloud Console.
Answer: C
Explanation:
https://cloud.google.com/sql/docs/mysql/using-query-insights#introduction
NEW QUESTION # 27
Your company is shutting down their on-premises data center and migrating their Oracle databases using Oracle Real Application Clusters (RAC) to Google Cloud. You want minimal to no changes to the applications during the database migration. What should you do?
- A. Migrate the Oracle databases to Cloud SQL.
- B. Migrate the Oracle databases to Bare Metal Solution for Oracle.
- C. Migrate the Oracle databases to Compute Engine.
- D. Migrate the Oracle databases to Cloud Spanner.
Answer: B
Explanation:
This answer is correct because Bare Metal Solution for Oracle is a service that provides dedicated physical servers and networking infrastructure for running Oracle databases on Google Cloud1. Bare Metal Solution for Oracle supports Oracle RAC, which is a cluster database that provides high availability, scalability, and performance for Oracle workloads2. By using Bare Metal Solution for Oracle, you can migrate your Oracle databases with minimal to no changes to the applications, and you can leverage the native Google Cloud services and interconnectivity1.
NEW QUESTION # 28
You need to redesign the architecture of an application that currently uses Cloud SQL for PostgreSQL. The users of the application complain about slow query response times. You want to enhance your application architecture to offer sub-millisecond query latency. What should you do?
- A. Configure Firestore, and modify your application to offload queries.
- B. Configure Bigtable, and modify your application to offload queries.
- C. Configure Memorystore, and modify your application to offload queries.
- D. Configure Cloud SQL for PostgreSQL read replicas to offload queries.
Answer: C
NEW QUESTION # 29
Your organization has a critical business app that is running with a Cloud SQL for MySQL backend database.
Your company wants to build the most fault-tolerant and highly available solution possible. You need to ensure that the application database can survive a zonal and regional failure with a primary region of us- central1 and the backup region of us-east1. What should you do?
- A. Provision a Cloud SQL for MySQL instance in us-central1-a.
Create a multiple-zone instance in us-east-b.
Create a read replica in us-east1-c. - B. Provision a Cloud SQL for MySQL instance in us-central1-a.
Create a multiple-zone instance in us-east1-b.
Create a read replica in us-central1-b. - C. Provision a Cloud SQL for MySQL instance in us-central1-a.
Create a multiple-zone instance in us-central1-b.
Create a read replica in us-east1-b. - D. Provision a Cloud SQL for MySQL instance in us-central1-a.
Create a multiple-zone instance in us-west1-b.
Create a read replica in us-east1-c.
Answer: C
Explanation:
https://cloud.google.com/sql/docs/sqlserver/intro-to-cloud-sql-disaster-recovery
NEW QUESTION # 30
You have a regional Spanner instance with no autoscaler that is serving a production workload.
You observed a surge in write activities to the database during an ongoing promotional event.
You received an alert that the database is close to the storage limit. Based on the storage utilization trend, the database will run out of storage in the next few hours. You want to resolve this issue as soon as possible. What should you do-
- A. Archive and delete historical data from the database.
- B. Create a custom instance configuration and add a custom read-only replica to the Spanner instance.
- C. Increase the compute capacity of the Spanner instance.
- D. Move the Spanner instance to a multi-regional configuration.
Answer: A
Explanation:
To immediately relieve the storage pressure, you should archive and remove obsolete or historical data. This reclaims space right away so your instance can continue handling writes without interruption.
NEW QUESTION # 31
You are using Memorystore for Redis to cache frequently accessed data and improve your application's performance. Recently, your application is experiencing sudden spikes in latency when interacting with the Memorystore for Redis instance. Upon checking the logs, you discover a high number of "evicted keys" messages. You want to reduce the occurrences of latency spikes and their impact on the application. What should you do-
- A. Enable read replicas. Deploy additional read replica instances to distribute read workloads.
- B. Redeploy your application to the same zone as the Memorystore instance.
- C. Scale the Memorystore instance to a larger memory size.
- D. Increase the time to live (TTL) value of all the keys within the cache.
Answer: C
Explanation:
Scaling up the instance's memory prevents frequent evictions by giving Redis more headroom, which reduces eviction-induced latency spikes.
NEW QUESTION # 32
You need to migrate existing databases from Microsoft SQL Server 2016 Standard Edition on a single Windows Server 2019 Datacenter Edition to a single Cloud SQL for SQL Server instance. During the discovery phase of your project, you notice that your on-premises server peaks at around 25,000 read IOPS.
You need to ensure that your Cloud SQL instance is sized appropriately to maximize read performance. What should you do?
- A. Create a SQL Server 2019 Standard on High Memory machine type with 16 vCPUs, 104 GB of RAM, and 4 TB of SSD.
- B. Create a SQL Server 2019 Enterprise on High Memory machine type with 16 vCPUs, 104 GB of RAM, and 500 GB of SSD.
- C. Create a SQL Server 2019 Standard on High Memory machine type with at least 16 vCPUs, 104 GB of RAM, and 200 GB of SSD.
- D. Create a SQL Server 2019 Standard on Standard machine type with 4 vCPUs, 15 GB of RAM, and 800 GB of solid-state drive (SSD).
Answer: A
Explanation:
Given that Google SSD performance is related to the size of the disk in an order of 30 IOPS for each GB, ti would require at least 833 GB to handle 25000 IOPS, the only answer that exceeds this value is C.
https://cloud.google.com/compute/docs/disks/performance
NEW QUESTION # 33
You have a Cloud SQL for MySQL instance with a table of product information including a column of product descriptions. Your application development team is building a customer facing chatbot and would like to find the product that most closely matches a freeform text description provided by the customer. How should you enable this functionality-
- A. Create a SQL script that compares the product description and the customer's search text by using the SOUNDEXfunction.
- B. Create and populate a column of product description embeddings on the product table and perform an approximate nearest neighbor search using the customer's search text.
- C. Create a stored procedure that uses a regular expression to match the customer's search text to values in the product description column.
- D. Use the LIKEoperator to match the customer's search text to the product description and return similar rows.
Answer: B
Explanation:
By precomputing embeddings for each product description and storing them in your table, you can turn a freeform customer query into an embedding and then run an approximate nearest- neighbor search to find the semantically closest products. This approach delivers much more relevant matches than regex, LIKE, or SOUNDEX without overloading the database with expensive text-processing on every query.
NEW QUESTION # 34
When comparing Google Cloud managed NoSQL services, which cost component should you consistently emphasize for a precise TCO analysis?
- A. Storage capacity costs
- B. CMEK for data at rest
- C. Query execution and index upkeep costs
Answer: C
Explanation:
Workload driven charges such as query execution and index upkeep are the most variable across services and are tightly coupled to how your application actually uses the database. In Firestore every document write can update multiple indexes which increases index upkeep costs and every read or query incurs operation charges that fall under query execution. In Bigtable you provision for throughput which still maps to demand from query execution. Centering comparisons on query execution and index upkeep costs produces a more accurate and comparable total cost of ownership across architectures.
NEW QUESTION # 35
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?
- A. Increase the storage size for the instance.
- B. Increase the number of CPUs for your instance.
- C. Use many smaller Cloud SQL instances.
- D. Use Cloud Spanner instead of Cloud SQL.
Answer: C
NEW QUESTION # 36
Your ecommerce website captures user clickstream data to analyze customer traffic patterns in real time and support personalization features on your website. You plan to analyze this data using big data tools. You need a low-latency solution that can store 8 TB of data and can scale to millions of read and write requests per second. What should you do?
- A. Stream your data into BigQuery and use Dataproc and the BigQuery Storage API to analyze large volumes of data.
- B. Use Memorystore to handle your low-latency requirements and for real-time analytics.
- C. Write your data into Bigtable and use Dataproc and the Apache Hbase libraries for analysis.
- D. Deploy a Cloud SQL environment with read replicas for improved performance. Use Datastream to export data to Cloud Storage and analyze with Dataproc and the Cloud Storage connector.
Answer: C
NEW QUESTION # 37
Your ecommerce website captures user clickstream data to analyze customer traffic patterns in real time and support personalization features on your website. You plan to analyze this data using big data tools. You need a low-latency solution that can store 8 TB of data and can scale to millions of read and write requests per second. What should you do?
- A. Stream your data into BigQuery and use Dataproc and the BigQuery Storage API to analyze large volumes of data.
- B. Use Memorystore to handle your low-latency requirements and for real-time analytics.
- C. Write your data into Bigtable and use Dataproc and the Apache Hbase libraries for analysis.
- D. Deploy a Cloud SQL environment with read replicas for improved performance. Use Datastream to export data to Cloud Storage and analyze with Dataproc and the Cloud Storage connector.
Answer: C
Explanation:
Start with the lowest tier and smallest size and then grow your instance as needed. Memorystore provides automated scaling using APIs, and optimized node placement across zones for redundancy. Memorystore for Memcached can support clusters as large as 5 TB, enabling millions of QPS at very low latency
NEW QUESTION # 38
You have an application that performs numerous reads and writes all day running in a single Bigtable cluster. A new batch analytics job needs to read the same data and you want to make sure that the new job does not affect the existing workload. What should you do-
- A. Scale up the Bigtable instance by enabling Autoscaling.
- B. Add a new cluster to the existing instance, and enable multi-cluster routing in the app profile.
- C. Add a new cluster to the existing instance, and isolate the workloads with two app profiles.
- D. Scale up the Bigtable instance by manually adding more nodes.
Answer: C
Explanation:
This is the only way to isolate your analytical reads from the production workload-by adding a second cluster in the same Bigtable instance and creating two app profiles (one bound to the primary cluster for OLTP, and one bound to the new cluster for analytics). This keeps the batch job's heavy scans off your production nodes, while still reading the same underlying data.
NEW QUESTION # 39
You are evaluating Cloud SQL for PostgreSQL as a possible destination for your on-premises PostgreSQL instances. Geography is becoming increasingly relevant to customer privacy worldwide. Your solution must support data residency requirements and include a strategy to:
configure where data is stored
control where the encryption keys are stored
govern the access to data
What should you do?
- A. Replicate Cloud SQL databases across different zones.
- B. Create a Cloud SQL for PostgreSQL instance on Google Cloud for the data that does not need to adhere to data residency requirements. Keep the data that must adhere to data residency requirements on-premises. Make application changes to support both databases.
- C. Use features like customer-managed encryption keys (CMEK), VPC Service Controls, and Identity and Access Management (IAM) policies.
- D. Allow application access to data only if the users are in the same region as the Google Cloud region for the Cloud SQL for PostgreSQL database.
Answer: D
NEW QUESTION # 40
You are migrating your 10 TB on-premises PostgreSQL database to Cloud SQL for PostgreSQL by using Database Migration Service. During the migration, there will be schema changes in the source database. You need to ensure any schema changes are replicated, while keeping disruption to the ongoing migration to a minimum.
What should you do?
- A. Make the schema changes in both source and destination after stopping writes in source.
- B. Make the schema changes in the source by using the pglogical.replicate_ddl_command PostgreSQL extension.
- C. Stop the Database Migration Service migration job. Make the schema changes in the source.Restart the Database Migration Service migration job.
- D. Make the schema changes in the destination by using the
pglogical.replicate_ddl_commandPostgreSQL extension.
Answer: B
Explanation:
To keep disruption minimal while ensuring schema changes are replicated during an ongoing Database Migration Service (DMS) continuous migration for PostgreSQL, you should apply schema changes on the source using the pglogical.replicate_ddl_command extension so the DDL is propagated through logical replication to the destination automatically.
NEW QUESTION # 41
You released a popular mobile game and are using a 50 TB Cloud Spanner instance to store game data in a PITR-enabled production environment. When you analyzed the game statistics, you realized that some players are exploiting a loophole to gather more points to get on the leaderboard. Another DBA accidentally ran an emergency bugfix script that corrupted some of the data in the production environment. You need to determine the extent of the data corruption and restore the production environment. What should you do? (Choose two.)
- A. If the corruption is significant, perform a stale read and specify a recovery timestamp. Write the results back.
- B. If the corruption is significant, use import and export.
- C. If the corruption is insignificant, use backup and restore, and specify a recovery timestamp.
- D. If the corruption is insignificant, perform a stale read and specify a recovery timestamp. Write the results back.
- E. If the corruption is significant, use backup and restore, and specify a recovery timestamp.
Answer: D,E
Explanation:
https://cloud.google.com/spanner/docs/pitr#ways-to-recover
To recover the entire database, backup or export the database specifying a timestamp in the past and then restore or import it to a new database. This is typically used to recover from data corruption issues when you have to revert the entire database to a point-in-time before the corruption occurred.
This part describes significant corruption - A
To recover a portion of the database, perform a stale read specifying a query-condition and timestamp in the past, and then write the results back into the live database. This is typically used for surgical operations on a live database. For example, if you accidentally delete a particular row or incorrectly update a subset of data, you can recover it with this method.
This describes insignificant corruption case - E
https://cloud.google.com/spanner/docs/pitr https://cloud.google.com/spanner/docs/backup/restore-backup
NEW QUESTION # 42
You are deploying a new Cloud SQL instance on Google Cloud using the Cloud SQL Auth proxy. You have identified snippets of application code that need to access the new Cloud SQL instance. The snippets reside and execute on an application server running on a Compute Engine machine. You want to follow Google-recommended practices to set up Identity and Access Management (IAM) as quickly and securely as possible. What should you do?
- A. For the application server, set up a service account.
- B. For the application server, set up a common shared user account.
- C. For each application code, set up a dedicated user account.
- D. For each application code, set up a common shared user account.
Answer: C
NEW QUESTION # 43
Your organization is running a critical production database on a virtual machine (VM) on Compute Engine. The VM has an ext4-formatted persistent disk for data files. The database will soon run out of storage space. You need to implement a solution that avoids downtime. What should you do?
- A. In the Google Cloud Console, create a new persistent disk attached to the VM, and configure the database service to move the files to the new disk.
- B. In the Google Cloud Console, create a snapshot of the persistent disk, restore the snapshot to a new larger disk, unmount the old disk, mount the new disk, and restart the database service.
- C. In the Google Cloud Console, increase the size of the persistent disk, and use the resize2fs command to extend the disk.
- D. In the Google Cloud Console, increase the size of the persistent disk, and use the fdisk command to verify that the new space is ready to use
Answer: A
NEW QUESTION # 44
You are performing daily exports of native BAK files from Cloud SOL for SOL Server to Cloud Storage buckets by using gcloud sql export bakcommand at 6:00AM. You want to automate this routine using managed Google Cloud components so you can focus on other critical tasks of keeping your database healthy and performant. What should you do-
- A. Create a cron job to export and configure Pub/Sub as the target. Set a recurring schedule of 0 6 *
* * for the job. - B. Implement automated backups using the console and set the default retention to 7 days.
- C. Create a Cloud Run function to export with a Pub/Sub trigger. Create a Cloud Scheduler job to trigger the Cloud Run function daily.
- D. Enable retained backups for the instance.
Answer: C
Explanation:
The most reliable and managed way to automate daily exports is to use Cloud Scheduler to trigger a Pub/Sub topic, which then invokes a Cloud Run function that runs the gcloud sql export bak command. This eliminates the need for manual cron jobs or unmanaged scripts, providing a scalable, serverless, and fully managed automation solution.
NEW QUESTION # 45
Your company uses Bigtable for a user-facing application that displays a low-latency real-time dashboard.
You need to recommend the optimal storage type for this read-intensive database. What should you do?
- A. Recommend solid-state drives (SSD).
- B. Recommend splitting the Bigtable instance into two instances in order to load balance the concurrent reads.
- C. Recommend hard disk drives (HDD).
- D. Recommend mixed storage types.
Answer: A
Explanation:
if you plan to store extensive historical data for a large number of remote-sensing devices and then use the data to generate daily reports, the cost savings for HDD storage might justify the performance tradeoff. On the other hand, if you plan to use the data to display a real-time dashboard, it probably would not make sense to use HDD storage-reads would be much more frequent in this case, and reads that are not scans are much slower with HDD storage.
NEW QUESTION # 46
Larkspur Systems is building a browser based workspace where teams coauthor very large documents in real time. Each document can reach 25 MB and the system must handle about
60,000 edits per minute from users spread across three regions and it must keep a complete version timeline for every file with strong consistency. Which managed database on Google Cloud best satisfies these requirements?
- A. Firestore in Datastore mode
- B. Cloud Spanner
- C. Cloud Bigtable
- D. Cloud SQL with read replicas
Answer: B
Explanation:
It delivers globally distributed and strongly consistent transactions with high write throughput and can maintain an authoritative version history across regions.
This database scales horizontally and provides synchronous replication across multiple regions which matches the need to sustain about 60,000 edits per minute from users in three regions while preserving strong consistency. Its relational model and transactional SQL make it straightforward to design a versioned schema where each edit or snapshot is stored as a new row with committed ordering so you can reconstruct an exact timeline for every document.
NEW QUESTION # 47
Your Cloud SQL for PostgreSQL database supporting a financial application has been experiencing "deadlock detected" errors during end-of-month processing. You notice that CPU utilization spikes to 90% during these periods, and several long-running queries are consuming significant resources. You need to identify the specific queries causing the deadlocks and implement monitoring to solve similar issues before they cause application failures.
What should you do?
- A. Use Cloud SQL System Insights to identify long-running queries and number of deadlocks that occurred in the database. Enable a log_lock_waitsflag to determine if lock waits are causing poor performance. Set up Cloud Monitoring alerts for higher CPU utilization and connection count.
- B. Optimize SQL queries by adding appropriate indexes to frequently accessed columns and rewriting complex joins to use LEFT JOINinstead of INNER JOIN, where applicable.
- C. Increase the deadlock_timeoutparameter on the Cloud SQL for PostgreSQL instance. Export logs to Cloud Logging, and create log-based metrics to track deadlock occurrences.
- D. Implement connection pooling at the application layer to reduce the number of direct database connections and optimize shared_buffersand work_memparameters in Cloud SQL for PostgreSQL to improve query execution efficiency.
Answer: A
Explanation:
Cloud SQL System Insights helps you pinpoint the long-running and resource-heavy queries correlated with the deadlock periods and shows deadlock-related signals. Enabling log_lock_waits provides visibility into lock waits that typically precede or accompany deadlocks.
Cloud Monitoring alerts on CPU and connections gives proactive detection so you can investigate and remediate before the workload escalates into failures.
NEW QUESTION # 48
You are running an instance of Cloud Spanner as the backend of your ecommerce website. You learn that the quality assurance (QA) team has doubled the number of their test cases. You need to create a copy of your Cloud Spanner database in a new test environment to accommodate the additional test cases. You want to follow Google-recommended practices. What should you do?
- A. Use Cloud Functions to run the export in Avro format.
- B. Use Dataflow to run the export in Avro format.
- C. Use Cloud Functions to run the export in text format.
- D. Use Dataflow to run the export in text format.
Answer: B
NEW QUESTION # 49
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Google Professional-Cloud-Database-Engineer exam is an excellent choice for individuals who are looking to validate their skills and knowledge in the latest database technologies and showcase their expertise to potential employers or clients. Passing Professional-Cloud-Database-Engineer exam can open up new career opportunities in cloud database engineering and provide a competitive edge in the job market.
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