Serverless computing allows the startup to eliminate server management tasks, enabling them to concentrate on developing the application. It automatically adjusts resources based on demand, optimizing costs during periods of low traffic. However, the team should consider the implications of cold start delays and the possibility of vendor lock-in.

Adopting serverless computing necessitates the upfront purchase of server capacity to accommodate peak traffic, resulting in increased expenses. This approach offers less scalability than traditional server-based solutions, making it inappropriate for applications with variable traffic patterns.

Serverless computing offers straightforward pricing models and enhances the ease of debugging and monitoring, thereby simplifying application maintenance. It is most effective for applications with consistent and predictable traffic flows.

Serverless computing is well-suited for applications experiencing unpredictable traffic, as it dynamically scales resources without requiring manual adjustments. It optimizes costs by charging only for the actual compute resources consumed, though developers may encounter difficulties with debugging and monitoring in a distributed environment.

Serverless computing provides the ability to handle sudden spikes in traffic without manual scaling, but it may introduce latency during the initial request processing. It also offers built-in high availability and fault tolerance, though teams must design their applications to accommodate the stateless nature of serverless components.