In this chapter, we learned what serverless architecture is. Most importantly, the chapter helps architects decide if serverless is the way forward for their team and their engineering, and how to transition/migrate from their existing infrastructure to a serverless paradigm. We also looked at the paradigm of microservices and how they help make lightweight and highly agile architectures. This chapter also went into great detail about when a team should start thinking about microservices and when can they migrate or break their existing monolith(s) into microservices.
We then learned the art of building batch architectures in the serverless domain. One of the most common myths is that serverless systems are only for real-time computation purposes. However, we have learned how to leverage these systems for batch computations too, thus facilitating a whole lot of applications with the serverless paradigm. We looked at the pros and cons of going serverless so that better engineering decisions can be taken accordingly.
In the next chapter, we will cover a very detailed understanding of how AWS Lambda works, which is the core component of serverless engineering in the AWS cloud environment. We will understand how triggers work and how AWS Lambda functions work. You will learn about the concept of leveraging containers for executing serverless functions and the associated computational workload. Following that, we will also learn about configuring and testing Lambda functions, along with understanding the best practices while doing so. We will also cover versioning Lambda functions, in the same way versioning is done in code, and then create deployment packages for AWS Lambda, so that the developer can accommodate third-party libraries comfortably, along with the standard library ones.
