When I was working on an NLP-based chatbot, we occasionally encountered Out of Memory (OOM) issues. These were not frequent enough to disrupt the service entirely, but happened often enough to raise concern. Since we were building the application from scratch, we hadn’t initially included the appropriate Java arguments to generate a heap dump, which made it difficult to debug the issue when it happened. These OOM errors occurred sporadically, and during that time, the system was serving more than 50,000 concurrent users. Since none of the customers reported issues, we couldn't immediately prioritize deeper investigation. Eventually, we added the necessary Java arguments to generate a heap dump when an OOM occurs and waited for the issue to happen again. While waiting may not sound like the best strategy, we did our best to reproduce the problem under controlled scenarios. If you're interested in learning how to capture and analyze heap dumps, I’ve written a dedicated post about...