Gatsby is currently generating a ton of buzz as the new hot thing for generating static sites. This has lead to a number of frequent questions like: A static…what now? How is GraphQL involved? Do I need to set up a GraphQL server? What if I’m not a great React developer, really more of a bad React developer?
I’ve been working on creating AWS Cognito User Pools in CloudFormation, and thought this would be a good time to share some of what I’ve learned.
The high-level steps for implementing chaos experiments involve: defining your application’s steady state, hypothesizing the steady state in both the control and experimental groups, injecting realistic failures, observing the results, and making changes to your code base/infrastructure as necessary based off of the results.
A few months back, I blogged about my experience arriving at Stackery after code school. Months later, each day is still interesting and challenging and I’m so glad to have decided to pursue serverless as my concentration. I credit my AWS certifications for narrowing my focus enough to lead me to this point. The serverless community puts so much emphasis on exploration and getting started on your work or experiments today that, getting some exposure to AWS, you can get started right away.
It’s the beginning of a new year and when it comes to computing, going serverless is the resolution of many engineering teams. At Stackery, this excites us because we know how significant the positive impacts of serverless are and will be. So much, in fact, that we’re already thinking about its applications for next year and beyond.
As the CEO of Stackery, I have had a unique, inside view of serverless since we launched in 2016. I get to work alongside the world’s leading serverless experts, our customers, and our partners and learn from their discoveries. It’s a new year: the perfect time to take stock of professional progress, accomplishments, and goals.
Over the last couple of weeks, we’ve prioritized some sustaining product goals to polish the codebase and update some big ticket dependencies. Among those updates were: React, Redux, and Webpack - the biggies. The first two were pretty painless and inspired the confidence to approach updating Webpack from v2 to v4 like maybe no big deal! Though confidence level was on high, I felt a slight chill and a twinge of doubt by the prospect of making changes to our build configs.
My career as a software engineer started in 2007 at Purdue University. I was working in the Linux kernel and researching how data was shuffled between the kernel and the user application layers. This was happening in huge clusters of machines that all talked to each other using OpenMPI — how supercomputers, like those at Los Alamos National Labs, operate to perform their enormous calculations around meteorology, physics, chemistry, etc.
Lambda layers and runtime API are two new feature of AWS Lambda which open up fun possibilities for customizing the Lambda runtime and enable decreased duplication of code across Lambda functions. Layers lets you package up a set of files and include them in multiple functions. Runtime API provides an API for interacting with the Lambda service function lifecycle events which lets you be much more flexible about what you run in your Lambda.
AWS’s announcement of Lambda Layers means big things for those of us using serverless in production. The creation of set components that can be included with any number of Lambdas means you no longer have to zip up your application code and all its dependencies each time you deploy a serverless stack. This allows you to include dependencies that are much more bespoke to your particular serverless environment.
