So far we have seen that certain applications can be broken down into one or more simple nuggets of code called as functions and uploaded to AWS Lambda for execution. Lambda then takes care of provisioning the necessary resources to run your function along with other management activities such as auto-scaling of your functions, their availability, and so on. So what exactly are we supposed to do in all this? A developer basically has three tasks to perform when it comes to working with Lambda--writing the code, packaging it for deployment, and finally monitoring its execution and fine-tuning.

In this section, we are going to explore the different components that actually make up a Lambda function by understanding what AWS calls as a programming model or a programming pattern. Currently, AWS officially supports Node.js, Java, Python, and C# as the programming...

In the real world, we often have different environments to work out of, for example development, QA, staging, pre-production, production, and so on. Having to manage a single Lambda function across all these environments can be a real pain, and also tricky especially, when each of your environments provide different configuration options, such as different connection strings for databases hosted for development and production, different roles and resource settings.

Lambda thus provides few add-on services that help you better categorize, and manage functions in the form of versions and aliases.

Versioning is a simple way to create one or more versions of your working Lambda code. Each version that you create is basically a snapshot of your origin function. Versions are also immutable which means, that each version you create from the origin or [$LATEST]...

We touched on the concept of packaging and deploying a simple Lambda function earlier in Chapter 1, Introducing AWS Lambda and parts of it in this chapter as well, however in this section, we will be doing things a bit differently! Rather than covering the steps all over again, we will be exploring a few simple and powerful open source Lambda deployment tools that are currently out there in the market today! Why tools you ask? Well, why not?

As a developer we always want to make the deployment and management of our codes simpler and hassle free, especially when it comes to working with a lot of Lambda projects at the same time. These tools accelerate time to development and also help us reduce any errors that may occur when working with the AWS Management Console or the AWS CLI. In this section we will be exploring two such tools that are gaining a lot...

Following is a list of some of the recommendations and best practices to follow:

• Optimize your code: Writing syntactically correct Lambda functions is one thing and writing optimized functions is totally another. For example, it's always a good practice to initialize any external services like DynamoDB, SNS outside your function code. The reason for this is simple, each time Lambda starts your code, the underlying container starts up. At this point, the code outside the handler runs first (initialization). When subsequent function calls are invoked, Lambda reuses the same container to run your functions and as a result you save resources and time by not instantiating the external services again.
• Versioning and aliases: As discussed before, versioning and aliases are a very important set of tools that you should leverage when creating and...

With the chapter almost at the end, here are few key next steps that I feel are worth trying out before we jump over to the next chapter. Firstly, create your own Lambda functions and deploy them either by using APEX or Claudia.js. This will help you in understanding versioning and aliases a bit better along with added simplicity to deploying functions as we move along this book. Additionally, there are other deployment tools and services present out there such as lambda-tools, gordon, and serverless which we will be covering in the later chapters.

Next, with the programming model in mind, try out developing the Lambda functions with Java and Python as well. In fact, you can use APEX to deploy your functions with golang as well. You can read more about the steps here at https://www.wolfe.id.au/2016/08/13/bootstrap-an-apex-golang-project/. More importantly...

It has been a long yet awesome chapter to learn. So let us summarize what we have learnt so far. First up, we deep dived into the Lambda programming model and understood each of its sub components (handlers, context objects, errors and exceptions) with easy to follow examples. Next, we covered how to effectively write and develop functions using the concepts of versioning and aliases. Finally, we concluded the chapter by understanding the use of environment variables and also looked at a few essentials recommendations and best practices to keep in mind when writing Lambda functions.

In the next chapter we will be learning about the importance of testing your code along with some really useful testing tools and frameworks. So stick around, we are just starting out!