Google Professional Cloud DevOps Engineer Question 259
Select 2Google Cloud PlatformYour team is running a critical microservices-based application on Google Kubernetes Engine (GKE). Recently, users have reported intermittent latency issues, but the logs do not provide sufficient information to identify the root cause. As a DevOps engineer, you want to implement a debugging solution to monitor the application and identify performance bottlenecks. Which tools should you use to address this issue?
- A
Cloud Debugger to inspect application variables in real-time without stopping the application.
- B
Cloud Trace to analyze latency and identify slow requests across services.
- C
Cloud Logging to aggregate logs from all microservices for detailed analysis.
- D
Cloud Profiler to monitor resource-intensive methods and optimize code performance.
- E
Cloud Scheduler to periodically trigger microservices for enhanced debugging insights.
Show answer and explanation
Correct answers: B, D
Explanation
To debug intermittent latency issues in a microservices-based application, you need tools that can analyze and optimize performance at a granular level. Cloud Trace helps identify slow requests and latency patterns, while Cloud Profiler provides insights into resource usage and inefficient methods. Together, these tools enable effective debugging and performance optimization.
- A. Incorrect.
Cloud Debugger is useful for debugging individual applications by inspecting variables and state but is not designed for analyzing latency or bottlenecks across distributed systems.
- B. Correct.
Cloud Trace is specifically designed to analyze latency issues in distributed applications, making it a key tool for identifying performance bottlenecks.
- C. Incorrect.
Cloud Logging can be helpful for general log aggregation but does not provide the detailed latency or performance insights required for debugging bottlenecks.
- D. Correct.
Cloud Profiler is designed to monitor resource usage in an application and can help identify resource-intensive methods, making it essential for optimizing performance.
- E. Incorrect.
Cloud Scheduler is used for scheduling jobs or tasks at specific times and is not relevant for debugging or analyzing application performance issues.