With AWS Lambda, we can deploy and scale individual functions. However, we as engineers still like to think in terms of services and maintain a mapping between business capabilities and service boundaries. The service level abstraction makes it easier for us to reason about large systems. As such, cohesive functions that work together to serve a business feature are grouped together and deployed as a unit (i.e. a service) through CloudFormation.

Don’t you just hate it when APIs are failing and you have absolutely no clue why? Now imagine you don’t have access to the VM, cluster or container where your software is running. Want me to continue with this nightmare? Yes, that’s what debugging AWS Lambda functions tends to seem like. A horrid nightmare of not knowing what is happening nor why things are failing. This article will show you a way of logging function invocations.

We recently released a new search key autocomplete feature here at Honeybadger. It was such a fun project that I just had to write it up for you all. Not only does it showcase an exciting use of DynamoDB, but it also shows the challenges of using Dynamo cost-effectively with large amounts of frequently-updated data.

In the world of web applications, Web Frameworks (WF) existed for a very long time. Traditional WF existed in a world without the notion of microservices, let alone the notion of serverless. Many first-time serverless users use WF to ease the transition into the ecosystem, sometimes unaware of its effect on the performance. The following post focuses on potential cold start issues when using WF in the NodeJS ecosystem.

With AWS Lambda, deploying a new version of our application has never been simpler. However, we still need to take care of some underlying plumbing. Such as managing the configuration for our functions as well as other related resources such as API Gateway, CloudWatch log groups and IAM policies. Depending on the event sources you would like to use, you also need to provision the necessary EventSourceMapping in order to use Lambda with the likes of Kinesis Streams and SQS.

AWS introduced Lambda Layers at re:invent 2018 as a way to share code and data between functions within and across different accounts. It’s a useful tool and something many AWS customers have been asking for. However, since we already have numerous ways of sharing code, including package managers such as NPM, when should we use Layers instead?

Smarter people than myself, once said that you should do things you don’t like first so that you can enjoy the things you’re doing later. Nobody wants cold starts. They’re annoying, and we continuously feel an itching sensation in our brains because of them. The serverless world would be a much better place to work in if they weren’t there.

While trying to verify the claims made on a somewhat facile rundown of serverless security threats, I ran across Jeremy Daly’s excellent writeup of a single vulnerability type in serverless, itself inspired by a fantastic talk from Ory Segal on vulnerabilities in serverless apps. At first I wanted to describe how injection attacks can happen. But the fact is, the two resources I just shared serve as amazing documentation; Ory found examples of these vulnerabilities in active GitHub repos!

Today, I’m thrilled to announce our new free tier and pricing model for teams adopting modern serverless application development. I believe cloud-side development is the future and I want everyone to experience it at their own pace. We also now offer a model that can scale with either teams or workflows depending on how aggressively you decide to adopt cloud-side development.