Running Elixir on Lambda

Aug 21, 2022

A while back, I discovered that Johns Hopkins publishes daily COVID case and death counts for all 50 US states. The graphs reminded me a lot of metric graphs for monitoring services, and I began to imagine a system of mirroring the data into CloudWatch and paging myself whenever they breached a certain threshold.

Johns Hopkins COVID case and death count time series graph for

This idea ended up evolving into CovidPager, and while I never did get as far as paging myself (PagerDuty kinda expects me to be a company), I do want to talk about the most interesting part of the project: the fact that it ended up as an Elixir application running on Lambda!

Run Whatever You Want

The beginning of this journey starts with Lambda and its custom runtime. Although your typical Lambda function would use an officially supported runtime, ever since 2018, Lambda has also begun providing custom runtimes. This is our ticket into running an Elixir Lambda handler.

A handler running in a custom runtime interfaces with Lambda by interacting with the Lambda Runtime API. The runtime API is available as an HTTP service and is quite simple. It’s made up of four operations: get the next invocation, respond to an invocation, report a service initialization error, and report an invocation error.

Lambda runtime API

In order for Elixir to run on Lambda, at minimum, we would need to write an Elixir application with an HTTP client that is able to poll requests from the next invocation endpoint, process the requests, and send responses to the response endpoint. This is a lot of boilerplate work. Thankfully, someone else has done it for us already in the form of the AWS Lambda Elixir Runtime! Building on top of the runtime implementation is as simple as adding :aws_lambda_elixir_runtime as a dependency in our Mix project, writing the Lambda handler, and deploying a custom runtime Lambda function that targets the handler using its identifier.

Run In Wherever You Like

If you are like me and followed the AWS Lambda Elixir Runtime guide by deploying the release artifacts directly to Lambda, there is a high chance you ran into an error related to a dependency for beam.smp. The reason behind this is that Elixir itself depends on the BEAM virtual machine which was compiled for your machine’s environment as part of the prerequisite Erlang installation for Elixir. Your machine is most likely not configured exactly the same as Amazon Linux 2 (AL2), the environment that the custom runtime Lambda function runs in, which will result in incompatibilities. In my case, BEAM needed glibc version 2.29 while Amazon Linux 2 has version 2.26 at the time of writing. The only real solution for this would be to spin up an EC2 instance running AL2, re-download and re-compile Erlang and Elixir on it, and then rebuild my application. I took one look at my wallet, one look at the time, and decided nah.

Normally, this would be where the experiment ends, but back in 2020, Lambda released support for container images. What this means is that our function’s environment does not have to be tied to Amazon Linux anymore. We can just steal acquire a pre-existing Docker image for Elixir and build our application on top of that! Lambda will run our container and any dependency issues between our machine and Amazon Linux disappears since we can just model our environment via Docker instead! For CovidPager, I ended up using an Elixir Alpine image and set up Docker to build and run the application binary.

# Dockerfile

FROM elixir:1.13-alpine


RUN mix do local.hex --force, local.rebar --force


COPY mix.exs mix.lock ./
COPY config config
RUN mix deps.get

COPY lib lib
RUN mix release

ADD aws-lambda-rie-x86_64 /usr/local/bin/aws-lambda-rie
COPY ./ /

CMD [ "Elixir.CovidPager:handler" ]

You may have noticed that the Dockerfile also contains an ENTRYPOINT that points to a shell file called This is to support locally testing the container image function. To do this, AWS provides a Runtime Interface Emulate (RIE) which is a stand-in for the real Lambda Runtime Interface web server. We can include the RIE binary in our image and then configure the entrypoint of the image to a program (in this case, which will conditionally run the service using RIE or the actual binary depending on whether the Lambda runtime is present. If deployed locally, RIE allows the Lambda function to be triggerable via HTTP POST to the local Docker endpoint.


if [ -z "${AWS_LAMBDA_RUNTIME_API}" ]; then
  exec /usr/local/bin/aws-lambda-rie _build/prod/rel/covid_pager/bin/covid_pager start $@
  exec _build/prod/rel/covid_pager/bin/covid_pager start $@

Having the ability to do this kind of local testing is powerful since it means that we can test our service as if it were truly deployed instead of only being able to test through unit tests. Unit tests can’t test entire integrations since they usually mock out key dependencies, such as external services, so being able to see a service’s real behavior during local development helps to uncover any sort of integration failure cases as early as possible.

Once I was able to test locally, it was time to deploy for real. I uploaded the image to ECR and spun up a Lambda container image function that would consume the uploaded image. The infrastructure specification ended up being just a single function in CDK.

// deployment-stack.ts

const fn = new lambda.DockerImageFunction(this, 'ECRFunction', {
  functionName: 'CovidPager',
  code: lambda.DockerImageCode.fromImageAsset('/PATH/TO/PROJECT/ROOT'),
  timeout: cdk.Duration.seconds(30),

But…Why Run Like This At All?

Question time. Yes, you in the back.

Ok um, so the question was: why in the world would anyone want to do this? That’s a great question. I’m not really sure.

One of Elixir’s major selling points is its ability to deal with faults. An Elixir application does this with supervisors that watch child processes. If a child fails, supervisors can take further action based on a supervisor’s strategy. For example, a one-for-one strategy will restart just the failing child if a child fails while a one-for-all strategy will restart all children under the supervisor if a child fails. A more complex application may have a supervisor tree with higher-level supervisors that watch lower-level supervisors that themselves watch the actual worker processes.

Example supervision

The supervisor design works best for long-running applications since it allows for a service to recover from faults by only restarting parts of the application as opposed to the whole in order to keep the overall service up and running. However, this isn’t really a great fit for Lambda which is meant for only short-lived tasks (currently, a Lambda function’s max execution time is 15 minutes).

Moreover, with serverless design, it feels that fault tolerance is intended to be taken care of by the infrastructure rather than by the actual service. Because of this, AWS services end up doing most of the heavy lifting to recover from or avoid faults (ex. ensuring a service is healthy in ECS by automatically restarting unhealthy containers or ensuring requests are processed by a service by fronting them with an SQS queue). All in all, this seems to make Elixir’s fault-tolerant design feel redundant when paired with Lambda.

In my opinion, the greatest benefit of running Elixir on Lambda may simply be access to the Elixir language itself. Choosing Lambda for infrastructure does not mean that Elixir is off the table as a choice for language and vice versa. Moreover, as a functional language, Elixir generally feels like a good fit for writing Lambda functions since both are designed for stateless execution.

Closing Thoughts

The upshot is that running Elixir in Lambda is not only theoretically possible, but actually quite accessible through the AWS Lambda Elixir Runtime and Lambda’s support for containers. While Elixir’s fault-tolerance benefits are lost within a Lambda function, it’s still neat that Lambda can run Elixir, and it opens up the door for Elixir development on Lambda from anyone who wants to try.

That being said, running Elixir in Lambda still poses a risk since it is not officially supported by Lambda. Even though some well-known companies are already using Elixir (Heroku and Discord to name names), the language itself is not mainstream like Python or Java. If Elixir and functional programming as a whole really do reach widespread popularity in the coming years, it would be interesting to see its effect on how developers design services in the future as well as how cloud providers will react to those shifting design paradigms.