To add to the other comments, using serverless with AWS Lambda has been very useful for us in our data pipeline, in a large part because you can hook them up to

To add to the other comments, using serverless with AWS Lambda has been very useful for us in our data pipeline, in a large part because you can hook them up to respond to a number of events like S3 uploads, updates to dynamo tables, or to an SNS or message queue topic. It scales up effortlessly and is very cheap to run. Could we have done this by avoiding serverless? sure but we would have to maintain quite a bit more infrastructure - why do that when someone else can handle that infrastructure cheaply? I realize my example is provider-specific but I think having them act as asynchronous data transforms and workflows are where the serverless really shines, especially given the invocation overhead of 20-30ms or so when hot, and several seconds when cold. We have run into instances where the serverless model doesn't work so well, like when we updated our graphql API to query a postgres store - each lambda invocation created its own connection pool and would overload the database. Currently theres no way to reliably persist those somewhere else and have the lambdas pick up the persistent connection (like how a redis session store would work) - perhaps that will change. the lambdas work best when they're more-or-less "pure functions", so if you have to keep things like sql connection pools, or a session around, you still need your own persistent server.