You are analyzing Java applications in production. All applications have Cloud Profiler and Cloud Trace installed and configured by default. You want to determine which applications need performance tuning. What should you do? (Choose two.)
You are analyzing Java applications in production. All applications have Cloud Profiler and Cloud Trace installed and configured by default. You want to determine which applications need performance tuning. What should you do? (Choose two.)
To determine which applications need performance tuning, two effective approaches are: examining the latency time, wall-clock time, and CPU time, and monitoring heap usage. If the latency time is consistently burning down the error budget and the difference between wall-clock time and CPU time is minimal, it suggests inefficiencies in the application's use of CPU resources, indicating areas for optimization. Additionally, low heap usage can indicate that the application is not utilizing available memory resources effectively, which can also present opportunities for performance tuning and optimization.
I asked Google's Gemini AI and this is what it answered. Here's why these options are correct: D: Latency time: High latency directly impacts user experience and can negatively affect your error budget. Wall-clock time: This represents the elapsed time from start to finish of a request. A large difference with CPU time indicates bottlenecks outside the CPU, requiring optimization. CPU time: This represents the actual CPU processing time used by the application. Minimal difference with wall-clock time suggests inefficient use of CPU, potentially needing optimization. E: Heap usage: Low heap usage can indicate under-provisioning or potential memory leaks. Either way, it implies inefficient resource utilization and deserves investigation.
A conflicts with D hence A gets excluded. B and C don't have direct relation with CPU time/wall time hence excluded either. Answers are D and E.
https://cloud.google.com/profiler/docs/concepts-profiling
D for sure, since "If the CPU time is similar to the wall time, then that indicates the code is CPU intensive; almost all the time it takes to run is spent by the CPU. Long-running CPU-intensive blocks of code might be candidates for optimization."
Choose options D and E. - Option D suggests examining the latency time, wall-clock time, and CPU time of the application. If the latency time is consistently burning down the error budget and the difference between wall-clock time and CPU time is minimal, it indicates potential areas for optimization. This helps identify performance bottlenecks that may be impacting the user experience. - Option E suggests examining the heap usage of the application, and if the usage is low, marking the application for optimization. Low heap usage may indicate that the application is not fully utilizing available resources, presenting an opportunity for optimization to enhance efficiency and responsiveness. Together, these approaches provide insights into areas where performance improvements may be beneficial for the applications.
Choose options D and E. - Option D suggests examining the latency time, wall-clock time, and CPU time of the application. If the latency time is consistently burning down the error budget and the difference between wall-clock time and CPU time is minimal, it indicates potential areas for optimization. This helps identify performance bottlenecks that may be impacting the user experience. - Option E suggests examining the heap usage of the application, and if the usage is low, marking the application for optimization. Low heap usage may indicate that the application is not fully utilizing available resources, presenting an opportunity for optimization to enhance efficiency and responsiveness. Together, these approaches provide insights into areas where performance improvements may be beneficial for the applications.
https://cloud.google.com/profiler/docs/concepts-profiling D. When you examine the latency time along with the wall‐clock and CPU times, a minimal difference between wall‐clock and CPU times indicates that the code is CPU‑intensive (i.e. it isn’t waiting on I/O). If at the same time the latency is eroding the error budget, this signals that the application isn’t keeping up with user expectations and is a candidate for performance tuning. E. Low heap usage implies that the application isn’t heavily utilizing its available memory. In Java applications, if the heap usage remains low despite ample allocation, it suggests that increasing memory won’t improve throughput or latency. Instead, the code itself may be inefficient (for example, it might not be caching or reusing objects effectively) and therefore should be optimized.
In summary, when Cloud Profiler shows that: - The latency is gradually consuming the error budget and CPU time closely matches wall‐clock time (Option D), and - Heap usage is low (Option E), it indicates that adding more resources (like CPU or memory) won’t resolve the underlying inefficiencies. Instead, you should focus on code-level optimizations.