Coming from a Java background, I consider the Python development process to be a bit of a mess. The pieces are all there: a central repository for publicly-available packages, a way to install the packages you want, and several ways to run your program with only those packages. But it seems that everybody has a different way to combine those pieces. So when a colleague introduced me to Poetry, my first reaction was “oh great, another tool that solves part of my problem.” But after spending time with it, I don’t want to build Lambdas any other way.
Sujan Kapadia takes the reins as host this week and covers NFTs, pattern matching in JDK 16, and some excellent drone footage. Thanks, Sujan!
“Traditional” deployment patterns separate the application from its infrastructure. Lambda deployments turn this model on its head, binding the infrastructure tightly to the running code. This can be a challenge, especially when developing in a team: it is all too easy for one developer to accidentally overwrite another’s work. In this post I look at several deployment options, and how they impact a development team.
In my last post, I looked at how you could package your Lambda as a Docker image. In this post, I show how you can use the base Amazon images to build a “traditional” Lambda and ensure that it has libraries that are appropriate for the Lambda runtime environment.
Lambda Container Images were announced at re:Invent 2020, providing a new way to build and deploy Lambda functions. They arrived just in time to solve an annoying build problem for me, so got my attention. And there weren’t any tutorials floating around when I first Googled, so I figured it was worth writing one. But … Read More
Ken Rimple, Sujan Kapadia, and Keith Gregory talk AWS Lambda, Ruby 3.0, M1 discussions, Apple store closures, and a little bit of LISP.
Check out our YouTube playlist to watch all the talks from Emerging Technologies for the Enterprise 2020. Abstract Ah, Serverless. The term that means a dozen different things to a dozen different developers. In the most simple case, Serverless just means deploying applications to a platform where the servers are managed for you, and abstracted … Read More
Apps no longer just run on smartphones and tablets – they process verbal commands we speak to devices like Amazon Echo, run as bots in Slack channels, and are rapidly evolving customer experiences that span a range of IoT devices in homes, cars, offices, and industrial settings. Crucial to the success of all these ecosystems is one central idea: Code has to not just run in the cloud, it has to be easy to get it there and scale it there. Serverless computing – calling AWS Lambda functions instead of managing heavyweight applications on infrastructure – is changing how developers think about backends, event-driving processing, and application design. Infrastructure, deployment, and software platform setup that used to take days or weeks of time vanishes, replaced by microservices that do one thing well, require zero effort to deploy, and scale automatically and implicitly just by using them. At the same time, AWS Lambda and other serverless systems have redefined cloud economics by eliminating the possibility of cold servers, creating a radical new price point for applications running in the cloud and freeing developers and COO’s alike from worrying about paying for unused capacity. In this talk we’ll define Serverless computing, examine the key trends and innovative ideas behind the technology, and look in detail at design patterns for big data, event processing, mobile backends, and more using AWS Lambda.
In this talk we’ll define Serverless computing, examine the key trends and innovative ideas behind the technology, and look in detail at design patterns for big data, event processing, mobile backends, and more using AWS Lambda.