Exam Professional Cloud Database Engineer topic 1 question 65 discussion

A. 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 large for 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

https://cloud.google.com/blog/topics/developers-practitioners/introducing-sqlcommenter-open-source-orm-auto-instrumentation-library

Only using Query Insight we can able to check why its failing

The answer should be D. A looks not right because Query Insight is for internal Cloud SQL performance and it's not about calls are failing.

Cloud Trace does not automatically support Cloud SQL, meaning it won't natively track latency or errors within Cloud SQL queries without additional instrumentation. Cloud Trace can provide comprehensive tracing of application requests, but for Cloud SQL queries to be included, explicit instrumentation is needed, typically via tools like Sqlcommenter. Cloud Trace should be able to include latency data for SQL queries. This setup helps team see the impact of database performance on the overall application performance. This helps in identifying the root cause of microservice call failures.

answer : D While Query Insights is a powerful tool for optimizing database performance and identifying query-related issues, it does not provide the necessary breadth of information required to diagnose failures in a microservices-based application. Cloud Trace, on the other hand, offers a comprehensive view of application performance, including but not limited to database interactions, making it a more suitable choice for identifying the root cause of microservice call failures.

https://cloud.google.com/blog/topics/developers-practitioners/introducing-sqlcommenter-open-source-orm-auto-instrumentation-library

D - To diagnose and address application-level issues, monitoring at the application request level (Option D) is the appropriate choice.

I'll go for A

A: Watch Query Insights for long running queries. Sqlcommenter is an open source library that enables ORMs to augment SQL statements before execution, with comments containing information about the code that caused its execution. This helps in easily correlating slow queries with source code and giving insights into backend database performance. In short, it provides observability into the state of client-side applications and their impact on database performance. Application developers need to do very little application code change to enable Sqlcommenter for their applications using ORMs. Observability information from Sqlcommenter can be used by application developers directly using slow query logs, or it can be integrated into other products or tools, such as ***** Cloud SQL Insights, to provide application-centric monitoring.