Serverless actual pros: "infinite" (meaning wallet level) scalability. Integrated deployment tooling usually. Integrated ingress usually. Those last 2 reall

Serverless actual pros: "infinite" (meaning wallet level) scalability. Integrated deployment tooling usually. Integrated ingress usually. Those last 2 really don't matter though as neither problem is that difficult if you know what you are doing. They both would have been a huge selling point in a world where k8s doesn't exist. Alas it does and thus mostly moot. The first however is a big deal as managing very bursty loads on k8s can actually be a bit of a challenge. This is doubly true when you are using some sort of queue and don't have good queue scaling metrics for whatever reason. Serverless lets you cop out of managing that by using infinite concurrency. Ok so now cons of serverless: Turns all your code into spaghetti, this is probably the biggest one. Cold boot performance is highly varible and generally worsens with added function complexity but this depends on tech choice. Infinite concurrency is a bit of a curse. Want to use that MySQL DB that contains all your business critical data? Better use some MySQL Serverless proxy nonsense because unbounded connections isn't fun. Lock-in is awful, migration story is awful. Amount of Infrastructure as Code overhead, ala Terraform, CloudFormation, whatever else floats your boat to support serverless is insane. The sheer number of objects that need to defined, kept in sync etc is just bonkers. Not to mention if you have multiple services setup like this it's all boilerplate you either need to abstract or carry around. Hides serious programming deficiencies like memory leaks because context is thrown away after servicing request. Unpredictable runtime makes observability more complicated, probably forcing you into poor decisions as a result, i.e prom push gateway. Runtime/execution time limits mean people trying to do all-serverless end up doing horrible things to accomplish long-running tasks. All of the above leads to increasing pressure to make poor architectural decisions to work around limitations of the runtime. I could probably go on but that is a reasonable set for you. EDIT: Actually I forgot the worst con. The cost. The $/CPU/RAM cost of Serverless is beyond bonkers. When I was pricing up Cloud Functions vs Spot instances on GKE I think I came to the conclusion Cloud Functions are about 300x as expensive. If your code can run on serverless it can probably run on Spot instances which you can just add to your GKE deployment using another node pool and only schedule things that can handle nodes going away within 60s there and instantly reap 300x cost savings. This is because Serverless is sold at a massive premium to CPU list prices and Spot is sold at like ~30-40% of list prices depending on machine type (for those curious when I last checked T2D was the best for price/performance for highly single thread performance dependent workloads, ala Node.js)