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Reliable Professional-Cloud-Database-Engineer Exam Price, Latest Professional-Cloud-Database-Engineer Exam Cost

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Google Professional-Cloud-Database-Engineer exam is intended for individuals with experience in database administration and development, including knowledge of SQL and database design principles. Candidates should also have experience working with Google Cloud Platform, including knowledge of its database services such as Cloud SQL, Cloud Spanner, and Cloud Bigtable. Successful candidates will be able to implement and manage highly available, scalable, and secure databases on Google Cloud Platform, and provide optimal database solutions to meet an organization's needs. Google Cloud Certified - Professional Cloud Database Engineer certification is suitable for professionals working in roles such as database administrator, database developer, data engineer, and cloud architect.

Earning the Google Professional-Cloud-Database-Engineer Certification can help you advance your career in the field of cloud database management. Google Cloud Certified - Professional Cloud Database Engineer certification demonstrates that you have the skills and expertise required to design, develop, and maintain scalable and secure databases on the Google Cloud Platform. With this certification, you can enhance your job prospects and increase your earning potential. Additionally, you can gain recognition as a proficient database professional who can handle complex database management tasks on the cloud.

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Google Cloud Certified - Professional Cloud Database Engineer Sample Questions (Q89-Q94):

NEW QUESTION # 89
Your organization has a production Cloud SQL for MySQL instance. Your instance is configured with 16 vCPUs and 104 GB of RAM that is running between 90% and 100% CPU utilization for most of the day. You need to scale up the database and add vCPUs with minimal interruption and effort. What should you do?

A. Issue a gcloud sql instances patch command to increase the number of vCPUs.
B. Issue a gcloud compute instances update command to increase the number of vCPUs.
C. Back up the database, create an instance with additional vCPUs, and restore the database.
D. Update a MySQL database flag to increase the number of vCPUs.

Answer: A

NEW QUESTION # 90
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 Cloud SQL instance monitoring in the Google Cloud Console.
B. Use Query Insights for Cloud SQL.
C. Use the Cloud Monitoring dashboard with available metrics from Cloud SQL.
D. Use log messages produced by Cloud SQL.

Answer: C

NEW QUESTION # 91
Your retail organization is preparing for the holiday season. Use of catalog services is increasing, and your DevOps team is supporting the Cloud SQL databases that power a microservices-based application. The DevOps team has added instrumentation through Sqlcommenter. You need to identify the root cause of why certain microservice calls are failing. What should you do?

A. Watch Cloud Trace for application requests that are failing.
B. Watch the Cloud SQL recommenders for overprovisioned instances.
C. Watch Query Insights for long running queries.
D. Watch the Cloud SQL instance monitor for CPU utilization metrics.

Answer: C

Explanation:
Cloud Trace doesn't support Cloud SQL. Eliminate D. Cloud SQL recommenders for overprovisioned instances would tell you about Cloud SQL instances which are too largefor their workload. Eliminate C.
Monitoring CPU utilization wouldn't tell you why microservice calls are failing. Eliminate B. SQLcommenter integrates with Query Insights. So A is the best answer. https://cloud.google.com/blog/topics/developers- practitioners/introducing-sqlcommenter-open-source-orm-auto-instrumentation-library

NEW QUESTION # 92
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?

A. Use query parameters to speed up frequently executed queries.
B. Use SQL statements to analyze SPANNER_SYS.QUERY_STATS* tables.
C. Use SQL statements to analyze SPANNER_SYS.READ_STATS* tables.
D. Change the Cloud Spanner configuration from multi-region to single region.

Answer: C

Explanation:
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.

NEW QUESTION # 93
You are building a data warehouse on BigQuery. Sources of data include several MySQL databases located on-premises.
You need to transfer data from these databases into BigQuery for analytics. You want to use a managed solution that has low latency and is easy to set up. What should you do?

A. Use Cloud Data Fusion and scheduled workflows to extract data from MySQL. Transform this data into the appropriate schema, and load this data into your BigQuery database.
B. Use Datastream to connect to your on-premises database and create a stream. Have Datastream write to Cloud Storage. Then use Dataflow to process the data into BigQuery.
C. Create extracts from your on-premises databases periodically, and push these extracts to Cloud Storage. Upload the changes into BigQuery, and merge them with existing tables.
D. Use Database Migration Service to replicate data to a Cloud SQL for MySQL instance. Create federated tables in BigQuery on top of the replicated instances to transform and load the data into your BigQuery database.

Answer: B

NEW QUESTION # 94
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