I’ve been comparing Lambda and EC2 pricing, and I’m struggling to understand why people claim Lambda is more expensive. For example, a 128MB Lambda costs $0.00756/hour, while a t4g.nano EC2 instance (with 0.5GB RAM) costs $0.0042/hour. I’m considering using Lambda, but I’m not sure where the cost concerns come in. If a Lambda doesn’t run 100% of the time, and assuming it stays warm for 10 minutes, shouldn’t Lambda be cheaper? It seems like the decision only becomes tricky if the function uses more memory. Am I missing something? Any thoughts on this would be greatly appreciated!
Well, the core difference is really in how the services are billed and architected. Lambda charges you per execution, factoring in memory and runtime. So for small, infrequent tasks, it’s brilliant. But when you’re running functions frequently or for longer durations, those milliseconds start stacking up quickly. Not to mention the cold start latency that can affect performance—and in some cases, cost too if retries are involved. EC2, on the other hand, is always-on and much more predictable cost-wise for steady workloads.
Yeah, I’ve managed both Lambda and EC2 in production environments, and I’d definitely echo what Tom said. Adding to that
“Why is Lambda considered more expensive than EC2 for serverless computing?”
It really comes down to scale. Lambda looks affordable at first glance, but once your usage increases, think frequent invocations or higher memory functions, you begin to realize just how fast those charges can grow. EC2 gives you a fixed hourly cost, which makes budgeting easier for services that are constantly running. Plus, EC2 allows optimization techniques like reserved instances and autoscaling that can drive the cost down even further, something that’s harder to manage with Lambda’s consumption-based model.
From my side, working closely with DevOps teams, I’ve seen cost reports surprise teams more than once—and the culprit? You guessed it.
People often overlook the hidden costs in Lambda—data transfer, cold starts, and logging can all add up. It’s a fantastic choice for quick-trigger microservices, but for anything requiring consistency or sustained processing, EC2 is more predictable and easier to optimize. With EC2, you can choose instance types, control provisioning, and even colocate services to reduce latency and costs. Lambda abstracts away a lot, which is great for simplicity, but that abstraction often means you pay a premium for convenience.