Check out my new course Learn you some Lambda best practice for great good! and learn the best practices for performance, cost, security, resilience, observability and scalability.
With AWS Lambda and the Serverless framework, deploying your code has become so simple and frictionless.
As you move more and more of your architecture to run on Lambda, you might find that, in addition to getting things done faster you are also deploying your code more frequently.
But, as you rejoice in this new found superpower to make your users and stakeholders happy, you need to keep an eye out for that regional limit of 75GB for all the uploaded deployment packages.
At Yubl, me and a small team of 6 server engineers managed to rack up nearly 20GB of deployment packages in 3 months.
We wrote all of our Lambda functions in Nodejs, and deployment packages were typically less than 2MB. But the frequency of deployments made sure that the overall size of deployment packages went up steadily.
Now that I’m writing most of my Lambda functions in Scala (it’s the weapon of choice for the Space Ape Games server team), I’m dealing with deployment packages that are significantly bigger!
Serverless framework: disable versionFunctions
By default, the Serverless framework would create a new version of your function every time you deploy.
In Serverless 0.X, this is (kinda) needed because it used function alias. For example, I can have multiple deployment stages for the same function?—?
production. But in the Lambda console there is only one function, and each stage is simply an alias pointing to a different version of the same function.
Unfortunately this behaviour also made it difficult to manage the IAM permissions because multiple versions of the same function share the same IAM role. Since you can’t version the IAM role with the function, this makes it hard for you to add or remove permissions without breaking older versions.
Fortunately, the developers listened to the community and since the 1.0 release each stage is deployed as a separate function.
Essentially, this allows you to “version” IAM roles with deployment stages since each stage gets a separate IAM role. So there’s technically no need for you to create a new version for every deployment anymore. But, that is still the default behaviour, unless you explicitly disable it in your
You might argue that having old versions of the function in production makes it quicker to rollback.
In that case, enable it for the production stage only. To do that, here’s a handy trick to allow a default configuration in your
serverless.yml to be overridable by deployment stage.
In my personal experience though, unless you have taken great care and used aliases to tag the production releases it’s actually quite hard to know which version correlates to what. Assuming that you have reproducible builds, I would have much more confidence if we rollback by deploying from a
support branch of our code.
Clean up old versions with janitor-lambda
versionFunctions in the
serverless.yml for all of your projects is hard to enforce, another approach would be to retroactively delete old versions of functions that are no longer referenced by an alias.
To do that, you can create a cron job (ie. scheduled CloudWatch event + Lambda) that will scan through your functions and look for versions that are not referenced and delete them.
After we employed this Janitor Lambda function, our total deployment package went from 20GB to ~1GB (we had a lot of functions…).
I specialise in rapidly transitioning teams to serverless and building production-ready services on AWS.
Are you struggling with serverless or need guidance on best practices? Do you want someone to review your architecture and help you avoid costly mistakes down the line? Whatever the case, I’m here to help.
Check out my new podcast Real-World Serverless where I talk with engineers who are building amazing things with serverless technologies and discuss the real-world use cases and challenges they face. If you’re interested in what people are actually doing with serverless and what it’s really like to be working with serverless day-to-day, then this is the podcast for you.
Check out my new course, Learn you some Lambda best practice for great good! In this course, you will learn best practices for working with AWS Lambda in terms of performance, cost, security, scalability, resilience and observability. We will also cover latest features from re:Invent 2019 such as Provisioned Concurrency and Lambda Destinations. Enrol now and start learning!
Check out my video course, Complete Guide to AWS Step Functions. In this course, we’ll cover everything you need to know to use AWS Step Functions service effectively. There is something for everyone from beginners to more advanced users looking for design patterns and best practices. Enrol now and start learning!
Are you working with Serverless and looking for expert training to level-up your skills? Or are you looking for a solid foundation to start from? Look no further, register for my Production-Ready Serverless workshop to learn how to build production-grade Serverless applications!
Here is a complete list of all my posts on serverless and AWS Lambda. In the meantime, here are a few of my most popular blog posts.
- Lambda optimization tip – enable HTTP keep-alive
- You are wrong about serverless and vendor lock-in
- You are thinking about serverless costs all wrong
- Just how expensive is the full AWS SDK?
- Many faced threats to Serverless security
- We can do better than percentile latencies
- Yubl’s road to Serverless
- AWS Lambda – should you have few monolithic functions or many single-purposed functions?
- AWS Lambda – compare coldstart time with different languages, memory and code sizes
- Guys, we’re doing pagination wrong
- Top 10 Serverless framework best practices