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?
To effectively diagnose and address the root cause of why certain microservice calls are failing, monitoring at the application request level using Cloud Trace is essential. Cloud Trace allows you to see a comprehensive view of application performance, including application requests that are failing, which is necessary in a microservices-based architecture. This approach will help you pinpoint where in the flow the issue occurs, whether it's at the application layer or further down in the database interactions, provided adequate instrumentation is set up.
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
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.
A. Query insights is always the correct answer
D - To diagnose and address application-level issues, monitoring at the application request level (Option D) is the appropriate choice.
https://cloud.google.com/blog/topics/developers-practitioners/introducing-sqlcommenter-open-source-orm-auto-instrumentation-library
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.
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.