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AWS Lambda Versions and Aliases Explained By Example

In this blog, you will learn how to use AWS Lambda versions and aliases by means of a Java example. You will create a simple AWS Java Lambda, create several versions for it and you will learn how to use aliases for your environments. Enjoy!

1. Introduction

AWS Lambda allows you to run serverless functions onto the AWS environment. More general information about AWS Lambda can be found at the Amazon website. An important item when working with lambdas, is how to keep control over the different versions of your lambda and over which version runs onto which environment. You can imagine that you have a production environment which runs version 1 of your lambda, a test environment which runs version 2 and a development environment which runs version 3. Version 1 is your stable version, version 2 is the one with extra functionality or fixed bugs and is about to make the step to production but needs to be verified by the customer first, version 3 is your development version and is not yet tested and therefore the most instable version. In this post, you will learn how to manage your versions in these different environments. You will create a sample Java lambda and will create several versions of it. The sources for this blog can be found at GitHub.

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Fast Spring Boot AWS Lambdas with GraalVM

In my previous blog post, I documented how to take a Java Spring Boot application and convert it into a serverless function, which can be run in AWS Lambda. 

Anyone who's done this before knows that cold starts are a big downside - Java and Spring Boot are not known for their speedy startup times, and a typical full fat Spring Boot-converted lambda can take anything from 10 to 90 seconds depending on how much memory and CPU you allocate it. This may force you to over-provision them to compensate for the cold starts, but that's a pretty expensive sledgehammer. There is always provisioned concurrency, but that doesn't work out much cheaper either (and negates the responsive scalability of lambda as you have to anticipate how many you'll need in advance).

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Examining Serverless Security Strategies, Tools, and (Current) Best Practices

Developers and DevOps teams considering the efficiency, scalability, and cost benefits that serverless functions have to offer shouldn’t be daunted by the challenge of securing serverless applications throughout development and into production. They should take it very seriously. In this article, I will cover how to begin developing serverless functions using AWS Lambda and the best development tools to use, as well as the most effective serverless security strategies and best practices. 

To begin, approaches to serverless security fall into two categories: runtime security, and static security.

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AMI and Snapshot Management Using AWS Lambda

Create AMIs automatically with AWS Lambda

Automating tasks and continuously improving workflows are key parts of DevOps. In a CI/CD pipeline, being able to simplify processes is a huge plus. Not only will simplifying systemic processes make life easier for you as a developer, but there are other added benefits to gain as well. For example, you can significantly reduce the cost of running services in the cloud with refined and automated scaling of infrastructure.

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API Development Using AWS Serverless Architecture

I recently had the opportunity to work on an AWS-based Serverless architecture solution. This is for ZIP files processing requirements. At a high level, the requirements expected to be delivered from AWS are summarized below:

  1. Create a final output zip file from the contents of source zip files and arrange them in a specific hierarchy of folder structure. There are 2 Systems that will make source ZIP files available in the S3 bucket.
  2. Delete the set of files requested by Pega.
  3. Transfer the output zip file to the external SFTP server.

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