Wacky Wednesday: AWS Lambda Managed Instances — When Serverless Meets Servers
AWS re:Invent 2025 dropped a feature that made me do a double-take: Lambda Managed Instances.
Yes, you read that right. Lambda. On EC2.
Wait, Isn't That Just... EC2?
At first glance, it sounds like AWS is trolling us. "Here's serverless, but with servers!" But dig deeper and it actually makes sense.
The Problem It Solves:
Lambda is brilliant for most workloads, but it has constraints:
- •No access to specialized hardware (GPUs, Inferentia, Graviton)
- •Memory and compute limits
- •Cold start penalties for heavy runtimes
Meanwhile, EC2 gives you hardware flexibility but requires you to manage scaling, patching, and availability.
Lambda Managed Instances: The Middle Ground
Now you can:
- •Write Lambda functions with the same programming model
- •Deploy to EC2 instances AWS manages for you
- •Access specialized hardware without changing your code
- •Keep serverless scaling behavior
Real Use Cases:
1. ML Inference:
Run your Lambda-packaged model on GPU instances
2. Heavy Compute:
CPU-intensive workloads that hit Lambda limits
3. Custom Runtimes:
Specialized environments that don't fit Lambda's constraints
The Wacky Part:
We spent years explaining "serverless doesn't mean no servers" and now AWS is like "here's serverless WITH servers, explicitly."
The serverless purists are confused. The pragmatists are celebrating.
My Take:
This is AWS acknowledging that the "serverless vs. servers" debate was always a false dichotomy. The real goal is developer experience + right-sized infrastructure.
Lambda Managed Instances delivers both.
Sometimes the wackiest ideas are the most practical.