To determine which Java applications need performance tuning when Cloud Profiler and Cloud Trace are installed and configured, you should focus on analyzing the performance metrics that indicate inefficiencies. Option A suggests examining the wall-clock time and CPU time, and if the difference is substantial, increasing CPU resource allocation. This is correct because a significant difference between wall-clock time and CPU time often indicates that the application is spending a lot of time waiting (e.g., for I/O operations), which might not be solved by just throwing more CPU resources at the problem but indicates a need for optimization. Option D suggests examining the latency time, wall-clock time, and CPU time, and if the latency time is slowly burning down the error budget with minimal difference between wall-clock time and CPU time, marking the application for optimization. This is also correct because it identifies applications that are not efficiently using CPU resources (minimal difference between wall-clock and CPU time) but are still causing latency issues, indicating a need for code or architecture optimization. Options B and C are incorrect because increasing memory or local disk storage allocation does not directly address performance issues indicated by the difference between wall-clock time and CPU time. Option E is incorrect because low heap usage does not necessarily indicate a need for optimization; it might simply mean the application is efficiently using memory.