Serverless

I’ve looked at Pulumi to do a bunch of things, including creating subnets in a VPC, building EKS clusters, and DynamoDB tables. The one thing I hadn’t explored yet was how to deploy AWS Lambda functions using Pulumi, so that’s exactly what this blog is about.

As a developer, I’ve built apps and wrote code. As a cheesecake connoisseur, I’ve tried many different kinds of cheesecake. After I got to talk to some of the bakers, I realized that building apps and baking cheesecake have a lot in common. It all starts with knowing and trusting your ingredients. According to Tidelift, over 90 percent of applications contain some open source packages. Developers choose open source because they believe it’s better, more flexible, and more extendible.

Using serverless requires us to change our mindset on how we build apps and requires us to unlearn things we learned building apps in the past. At AWS re:Invent I got a chance to do a VMware Code session and talk about how we took part of our ACME Fitness Shop and transformed it into serverless functions with AWS Lambda.

As a trend cloud vendors tend to use the word serverless quite loosely. While serverless comes in a lot of shapes and sizes and as long as the characteristics fit within the four categories from my last blog, it is a serverless service. To make sure that we’re all on the same page, I’ll use the following definition for serverless:

“Serverless is a development model where developers focus on a single unit of work and can deploy to a platform that automatically scales, without developer intervention.”

In this blog post, we’ll look at how that model works on AWS Fargate, which allows you to run containers without having to manage servers or clusters.

There are many predictions from market analyst firms on the size of the global serverless architecture market and how fast it will grow. The numbers range from $18B to $21.99B in the next few years with the compound annual growth rate (CAGR) in the double digits. But is serverless only a fancy name for products like AWS Lambda and Azure Functions?

The CTO of a company I have worked for used to say that services should be loosely coupled but tightly integrated. I didn’t realize until a lot later how true that statement is as you’re building out microservices. How those microservices communicate with each other has also changed quite a bit. More often than not, they send messages using asynchronous protocols. As an industry, we decided that this new way of building apps should be called “Event-Driven Architecture (EDA).”

Imagine this, it’s 5pm on a Friday afternoon and while you really want to go enjoy the weekend, you also need to deploy a new version of your app to production. Using AWS CloudFormation (CF), you add a new instance to your fleet of EC2 instances to run your app.

In my talk “Duct Tape and String: Continuously Delivering Serverless Microservices” at swampUP 2019, I got to talk about some best practice for the project that got me excited about both serverless and K8s: OpenFaaS! For me that meant I got to combine a lot of the things I care about (Containers, Serverless, and Golang), while talking about the awesome possibilities that using Artifactory brings you.

Ever since I discovered Kubernetes, I’ve been looking at OpenFaaS to build and deploy serverless functions on top of it. So as I started building more and more functions to help the Developer Relations team at JFrog, I wanted to share how I use JFrog Artifactory and OpenFaaS together!

I’ve been playing with OpenFaas ever since I learned about Minikube a few years ago, so when one of my colleagues mentioned Google’s Distroless project I obviously needed to see if my Go projects could work using those images too.