In my opinion, applications that benefit the most from AWS Lambda are event-driven workloads like real-time data processing, file uploads, API backends, scheduled jobs, and microservices where workloads are unpredictable or come in bursts, because Lambda automatically scales and you only pay for what you use, making it very cost-efficient and flexible. It’s especially useful for tasks like processing images, handling IoT data, or building lightweight APIs without worrying about infrastructure. However, teams can face challenges such as cold start latency, which may impact performance for time-sensitive applications, as well as limitations around execution time, memory, and debugging complexity compared to traditional environments. Managing dependencies, monitoring distributed functions, and avoiding vendor lock-in can also become tricky as systems grow. Overall, while Lambda is powerful for building scalable and efficient applications, it requires thoughtful design and awareness of its constraints to use it effectively.