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Serverless run times with custom Bash AWS Lambda layers
A Code Bash
Amazon Web Services (AWS) Lambda functions [1] have grown immeasurably popular over the last year or two and will unquestionably have a place in the future when it comes to running repetitive tasks on cloud infrastructure while managing to avoid the costs and overhead of maintaining servers.
Something that tripped me up initially when I began adopting Lambda functions, however, was the growth in favoritism for the Python programming language. It seems that Node.js and Python have become the de facto sweetheart languages (or run times) of choice when it comes to Lambda functions, with Ruby appearing at points, too. Although I can pick away and tweak Python scripts, it's never been a priority for me to learn the language; as a result, creating a payload for Lambda functions was never easy.
I discovered something very clever the other day that allows Bash to be used as a custom run time in AWS Lambda functions. A GitHub project [2] clearly extols the virtues of using Bash as a serverless run time. In this article, I explore a relatively new addition to Lambda functions in AWS called "layers" and, with the use of a Bash layer provided on the GitHub page by author Graham Krizek [3], I run a Bash script that uses the latest and greatest serverless tech on AWS.
Bashes and Bumps
In simple terms, you might say that an AWS layer is an additional library you can inject into your Lambda function to run alongside your payload. Why would you want to do that, you might well ask? Well, you might have a common piece of code that you want to share around your infrastructure that gets updated periodically. It might contain anything, such as SSL/TLS certificates for your payload to connect securely into a service, or a shared
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