Pass the Google Cloud Database Engineer Professional-Cloud-Database-Engineer Questions and answers with ValidTests

From Google's documentation, "For stateful resources, such as databases, ensure that deletion protection is enabled. The syntax is: lifecycle { prevent_destroy = true } https://cloud.google.com/docs/terraform/best-practices-for-terraform#stateful-resources

https://cloud.google.com/spanner/docs/iam#spanner.databaseUser

The Cloud SQL overprovisioned instance recommender helps you detect instances that are unnecessarily large for a given workload. It then provides recommendations on how to resize such instances and reduce cost. This page describes how this recommender works and how to use it. https://cloud.google.com/sql/docs/mysql/recommender-sql-overprovisioned#:~:text=The%20Cloud%20SQL%20overprovisioned%20instance%20recommender%20helps%20you%20detect%20instances%20that%20are%20unnecessarily%20large%20for%20a%20given%20workload.%20It%20then%20provides%20recommendations%20on%20how%20to%20resize%20such%20instances%20and%20reduce%20cost.%20This%20page%20describes%20how%20this%20recommender%20works%20and%20how%20to%20use%20it .

This answer is correct because it meets the requirements of having an optimal and highly available environment with automatic failover. According to the Google Cloud documentation1, a regional Cloud SQL instance is an instance that has a primary server in one zone and a standby server in another zone within the same region. The primary and standby servers are kept in sync using synchronous replication, which ensures zero data loss and minimal downtime in case of a zonal outage or an instance failure. If the primary server becomes unavailable, Cloud SQL automatically fails over to the standby server, which becomes the new primary server1.

Cloud Spanner is a fully managed, mission-critical, relational database service that offers transactional consistency at global scale, automatic, synchronous replication for high availability, and support for two SQL dialects: Google Standard SQL (ANSI 2011 with extensions) and PostgreSQL.

https://cloud.google.com/database-migration/docs/postgres/faq

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.

https://cloud.google.com/blog/products/databases/manage-semi-structured-data-in-cloud-spanner-with-json