I trained an object detection model on a mixed dataset containing people, vehicles, and small objects like phones and traffic signs.The model detects large objects such as cars and people very reliably.However, it almost completely ignores smaller objects, ...
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I enabled autoscaling to handle traffic spikes.Instead of improving performance, latency increased.Cold starts seem frequent.This feels counterproductive.
I’ve tested all major features and everything works as expected, but security scanners keep reporting issues.I’m trying to understand why these problems don’t show up during normal testing and what I might be missing?!
prompt failure
Security controls are technically sound, but teams push back.Workflows feel slower and more restrictive.I’m trying to understand how organizations manage this transition successfully.
Short sequences work fine.Longer sequences cause GPU crashes.No code changes were made.Only input size increased.
The containers start normally and serve traffic correctly for a while.After some time, requests hang and the services become unreachable.Restarting the containers fixes the issue temporarily.No errors appear in the application logs.
I was told that zero trust removes the need for traditional network security.However, I still see recommendations for segmentation and firewall rules.I’m trying to understand why network controls are still needed in a zero-trust setup.