Moving AWS Lambda functions with Golang to Graviton chips

Stathis Peioglou
4 min readMar 12

AWS Lambda allows you to configure new and existing functions to run on Arm-based AWS Graviton2 processors in addition to x86-based functions.

On top, with this choice you can save money in two ways. First, your functions run more efficiently due to the Graviton2 architecture. Second, you pay less for the time that they run. In fact, Lambda functions powered by Graviton2 are designed to deliver up to 19 percent better performance at 20 percent lower cost.

But what is the high-level architecture exactly?

Every vCPU is a physical core and this offers better scalability. It offers more cache on per CPU-basis, and as depicted above, it means that there’s no simultaneous multi-threading (SMT) with more isolation between vCPUs. By contrast, every vCPU on a 5th generation instance type with Intel chips, is a hyper-thread. Having large L1 and L2 caches for every vCPU means that most of the times, a large portion of your workload will fit in cache, without the extra roundtrip in memory.

Gravitons are also implemented using a single socket with a flat memory hierarchy and with a single Non-uniform memory access domain. Under NUMA, a processor can access its own local memory faster than non-local memory. This accommodates for the same latency and bandwidth to memory for every vCPU.

How to run an AWS Lambda function with Golang on Graviton

For Golang to run on Graviton, you need to specify the Architecture to arm64 and the Runtime to provided.al2 (Provide your own bootstrap on Amazon Linux 2).

Then, for your handler code to run in a custom runtime, you need to package it with code that handles the Lambda Runtime API into a binary called bootstrap. The aws-lambda-go library provides a custom runtime mode out of the box and it has the logic to determine whether it is running in a native…

Stathis Peioglou

Senior Solutions Architect, AWS. Software Engineer by ❤️ All views are my own.