In my opinion, the biggest limitations of AWS Lambda are execution time limits, cold start latency, memory and resource constraints, and reduced control over the underlying runtime environment, which can become challenging as applications grow in complexity. While it works very well for event-driven, lightweight, and bursty workloads, it may not be suitable for long-running processes, compute-intensive applications, or systems that require consistent low-latency performance. Debugging and monitoring can also become more difficult in distributed serverless architectures, especially when multiple functions interact across a workflow. Because of these constraints, organizations should consider alternative solutions like containers or virtual machines when they need greater control, predictable performance, or support for heavy and long-duration workloads.