  This abstract presents a serverless approach to seismic imaging in the cloud
based on high-throughput containerized batch processing, event-driven
computations and a domain-specific language compiler for solving the underlying
wave equations. A 3D case study on Azure demonstrates that this approach allows
reducing the operating cost of up to a factor of 6, making the cloud a viable
alternative to on-premise HPC clusters for seismic imaging.
