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| Vendor: | |
|---|---|
| Exam Code: | Professional-Cloud-Database-Engineer |
| Exam Name: | Professional Cloud Database Engineer |
| Exam Questions: | 141 |
| Last Updated: | May 21, 2026 |
| Related Certifications: | Google Cloud Certified |
| Exam Tags: | Professional Database EngineersCloud Architectsand Data Professionals |
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Your company is using Cloud SQL for MySQL with an internal (private) IP address and wants to replicate some tables into BigQuery in near-real time for analytics and machine learning. You need to ensure that replication is fast and reliable and uses Google-managed services. What should you do?
''Datastream is a serverless and easy-to-use Change Data Capture (CDC) and replication service that allows you to synchronize data across heterogeneous databases, storage systems, and applications reliably and with minimal latency. Datastream supports change data streaming from Oracle and MySQL databases to Google Cloud Storage (GCS). The service offers streamlined integration with Dataflow templates to power up to date materialized views in BigQuery for analytics, replicate their databases into Cloud SQL or Cloud Spanner for database synchronization, or leverage the event stream directly from GCS to realize event-driven architectures.''
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?
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.
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?
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.
Your organization works with sensitive data that requires you to manage your own encryption keys. You are working on a project that stores that data in a Cloud SQL database. You need to ensure that stored data is encrypted with your keys. What should you do?
You need to migrate a 1 TB PostgreSQL database from a Compute Engine VM to Cloud SQL for PostgreSQL. You want to ensure that there is minimal downtime during the migration. What should you do?
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