AWS Lambda functions can only run for a maximum of five minutes. This must be distinctly understood, or nothing wonderful can come of the story you are about to hear.
This past summer, my team and I set out to build an internal software system used for deployment testing on AWS. The application would run a large number of workflow executions in parallel each night and might perform a few one-off executions during the day – maybe six hours total use out of every twenty-four, with only a small fraction of that time spent doing actual compute tasks. Trying to scale, manage and spend money on EC2 instances for that workload didn’t interest us. We wanted to run our whole workflow process end-to-end on AWS Lambda.
And we did. Heaven help us, we did. This is our story.
Continue reading “Serverless Workflows on AWS: My Journey From SWF to Step Functions”
The open source Serverless project, which currently has nearly 10,000 stars on Github, provides tooling around AWS’s “Function as a Service” ecosystem that includes Lambda and API Gateway. I recently had the opportunity to chat with Florian Motlik, CTO of Serverless, about his thoughts on serverless architectures and the future of the Serverless framework.
The following interview has been edited and condensed.
Forrest: Although AWS Lambda is less than two years old, we’re already seeing a robust tooling ecosystem appear around it, including the Serverless Framework. How did the Serverless project get started?
Florian: Austen Collins, our founder, started Serverless about a year ago. In his previous life as a consultant, he worked with AWS Lambda while building various applications. Austen saw two things about Lambda that made a huge difference for him. First, it enables you to build applications without having to maintain infrastructure. And as someone who had to maintain infrastructure in the past, he saw that was a really interesting direction for the industry to go. Second, Lambda enables an event-driven architecture, where you just react to events that can be fired from anywhere to anywhere. Austen also saw that although Lambda was very powerful, its lack of tooling made it hard for new users to get started. So, about a year ago he started building the Serverless framework. The project took off right away, and towards the end of last year, he decided that this is not just an open source framework; it’s something we can build a company around. So that’s when I was brought on as the CTO to lead our engineering team, and we grew from there.
Continue reading “Lambda calculus: talking Serverless with Florian Motlik”
Pester and CI
If you’re doing Windows scripting in 2016, you’d better be using PowerShell. And if you’re writing PowerShell scripts, you’d better be checking them into source control and covering them with Pester tests.
It turns out that you can do more with Pester than just run tests manually at the console. As part of a continuous integration (CI) process, you may want to invoke Pester tests on a remote server and report the results up through the build chain. Handily, you can export Pester test output in an NUnit XML format that modern CI systems like Jenkins understand.
But what if you’re not using a build server to invoke Pester? What if your CI setup is … dun dun dun … “serverless”?
Continue reading “Invoke Pester Tests Serverlessly with AWS Lambda and SSM”
Is there such a thing as too much automation?
At a family wedding the other weekend, I fell into conversation with a relative who has several decades of experience in the aerospace industry. He bemoaned a growing problem among the younger engineers who work for him. It seems that some of these highly-paid professionals have not developed the ability to look at a finished piece of work and say – “That doesn’t seem right” – because they rely on their advanced computer systems to do the validation. When the computer makes a mistake, they do not have the breadth of experience to realize it.
This point resonated with me for the simple reason that I experience it every day. I’m a professional automator – I automate software processes for a living – and I spend a lot of time inside the Amazon Web Services cloud. AWS handles the compute, storage and networking details for me so I can focus on higher-level tasks, which is both nice and worrisome. Nice because I can get more done in less time, worrisome because I don’t get the opportunity to grapple with the implementation details of server and network virtualization. I understand those things on a theoretical level, but I don’t get to play with them much, and this sometimes hampers my grasp of what’s really going on beneath all the automation.
Continue reading “AI, automation and the merry-go-round of the mind”
This cookbook is still in progress and will grow over time.
Lambda, AWS’s bite-size “serverless” compute service, is mostly awesome. However, it still has a relative lack of good documentation.
I’ve been using Lambda a lot lately, meaning I’ve had a lot of browser tabs open trying to find examples of the latest features like VPC support, Cloudformation integration and Python 2.7 functions. In this post, I’ll try to save you some time by sharing examples of a few things that have sent me searching.
Continue reading “My AWS Lambda Cookbook”
What’s that old schoolyard rhyme? “AWS and Azure, sitting in a tree, I – A -A – S, P – A -Y – G. First come VMs, then containers, then come stateless microservices running on public cloud infrastructure at fractions of a cent per second.” Or something like that.
Anyway, application deployments are getting lighter, backend microservices are getting smaller, and now many development shops are moving toward “serverless architectures” in which dynamic computational tasks are handled using a few cycles on somebody else’s managed server. As of 2016, the public cloud giants (AWS, Google Cloud and Microsoft Azure) all have their own “serverless services” that allow you to buy processing time for cheap. And I do mean cheap – a million AWS Lambda requests per month, each lasting five seconds, will set you back about $10.62.
Developers gravitate toward this approach because it’s scalable, cost-effective and requires little to no infrastructure maintenance. In AWS, you might deploy an application with data stores in RDS or DynamoDB, static web content hosted in S3, an API Gateway directing traffic and Lambda functions running the business rules – look Mom, no servers!
But wait a minute. Is a pay-as-you-go public cloud really the only place to run serverless compute functions? After all, a handful of computer scientists have been running little pieces of code on distributed computers for years, at a price even Lambda will never beat: free.
Continue reading “Could serverless computing work in a public volunteer cloud?”
“CloudPleasers” is a humorous look at life in the cloud, drawn on a semi-irregular basis.