Traditional server-based computing model, where the company leases virtual machines and manually scales them up or down based on traffic predictions. This option requires significant manual intervention and does not offer automatic scaling.

Infrastructure as a Service (IaaS) model, where the company manages the virtual machines but the cloud provider manages the physical infrastructure. While this reduces some management overhead, the company still needs to manually scale the VMs, which does not fully meet the requirement for automatic scaling.

Platform as a Service (PaaS) model, where the company develops and deploys applications without managing the underlying infrastructure, but still needs to configure scaling parameters. This option reduces infrastructure management but requires initial setup for scaling, which may not be as responsive as needed for sudden traffic spikes.

Serverless computing model, where the company writes code that runs in response to events, and the cloud provider automatically manages the computing resources, scaling them instantly in response to the number of executions. This model offers automatic scaling without manual intervention and charges only for the compute time consumed, aligning with the company's cost efficiency goals.

Container as a Service (CaaS) model, where the company deploys applications in containers that can be automatically scaled by the cloud provider. This option offers automatic scaling and reduces management overhead, but may not be as cost-efficient as serverless computing for applications with highly variable traffic.