In my opinion, Azure Functions is most commonly used for event-driven use cases like building lightweight APIs, processing background jobs, handling file or data transformations, integrating services through queues or events, and automating routine tasks such as scheduled workflows, because it scales automatically and reduces the need to manage infrastructure. It’s especially useful in microservices architectures and scenarios where workloads are unpredictable or bursty. However, teams can face challenges in production, such as cold start latency that may impact performance for time-sensitive applications, limitations around execution time and resource usage, and increased complexity in debugging and monitoring distributed functions. Managing dependencies and maintaining consistency across environments can also be tricky, and like other serverless platforms, there is a risk of vendor lock-in if the solution becomes tightly coupled with platform-specific features. Overall, while Azure Functions provides great flexibility and efficiency, it requires careful design and observability practices to run smoothly at scale.