What is serverless computing?

To understand what serverless computing is all about and how it came to be, we first need to travel back in time to the era of mainframes and traditional data centers! Sounds like a long-lost time, right? Don't worry, we are not going that far back. This is probably in the time when most IT organizations had massive in-house data centers for hosting almost all enterprise applications and services. First, these applications were hosted directly on physical servers, and then eventually migrated onto the virtualized environments that provided a better utilization of resources as well as helped to slash down the overall costs and time for deployments from months to days. With the advent of the virtualization era, we also started to develop and use more convenient deployment tools that helped to deploy our applications with more ease, but it still meant managing the application's underlying operating system, software platform, and so on:

With virtualization clearly not having all the answers, we started looking for a much simpler application deployment model and, in return, found Containers. Unlike their earlier counterparts, Virtual Machines, Containers don't require a lot of resources or overhead to run. They are far easier and quicker to deploy, hence, reduce the overall application deployment time from days to minutes! You could now easily roll out a new patch for your application, scale your application dynamically based on incoming requests, and even orchestrate various other functions using a vast variety of container management products. However, the question of managing the Containers still remains, and trust me, managing a fleet of thousands of Containers and their underlying physical servers is no easy task. A better, more efficient, deployment model was needed; something that provided us with the agility and flexibility of containers, but without all the hassle and trouble of managing them. Enter serverless computing!

Serverless computing is all about running your application code on small ingots of some CPU and memory without having to worry about the OS type, the software platform, or any of the underlying hardware either. Just take your code and run it! Yes! It's that simple! Serverless computing today is offered by most public cloud providers, such as Amazon Web Services, Google Cloud Platform, Microsoft Azure, and even by IBM as a managed service. This essentially means that all you need to do is write your code or functions that perform a very specific task, select the quantity of resources (in this case RAM) required to run your code and submit it to the serverless cloud computing service to execute on. The service makes sure that your code gets the required amount of memory and CPU cycles it needs to execute. Hence, the collective term Function as a Service (FaaS).

Pros and cons of serverless computing

Here is a quick look at some of the key benefits that you, as a developer, can attain with the help of serverless computing:

• No ware to manage: Perhaps one of the biggest reasons for the hype about serverless computing is the fact there is absolutely no hardware or software to manage. The management of the serverless computing environment all the way from the underlying hardware to the OS, to even the application's platform layer, is managed by the cloud provider itself.
• Faster execution time: Unlike your standard cloud instances, which generally take a good minute or two to boot up, functions, on the other hand, spin up very quickly, mostly in a matter of seconds. This could be due to the fact that the functions are made to run on top of a containerized platform.
• Really low costs: Since there is virtually no opex involved with serverless computing, it is fairly cheap, even when compared to hosting and managing instances in the cloud. Also, the pricing model for serverless computing is a little different from that of your traditional cloud pricing model. Here, you are generally billed on the duration of your function's execution and the amount of memory it consumed during its execution period. The duration is calculated from the time your code begins executing until it returns or otherwise terminates and is rounded up to the nearest 100 ms.
• Support of popular programming languages: Most cloud providers that provide serverless computing frameworks today, support a variety of programming languages, such as Java, Node.js, Python, and even C#. Azure functions allows the use of F#, PHP, Bash, Batch and PowerShell scripts in addition to the few mentioned.
• Microservices compatible: Since serverless computing functions are small, independent chunks of code that are designed to perform a very specific set of roles or activities, they can be used as a delivery medium for microservices as well. This comes as a huge advantage as compared to hosting your monolithic applications on the cloud, which do not scale that effectively.
• Event-driven applications: Serverless functions are an ideal choice for designing and running event-driven applications that react to certain events and take some action against them. For example, an image upload operation to a cloud storage triggers a function that creates associated thumbnail images for the same.

Feeling excited already about giving serverless computing a try? Hold on! There are a few cons to serverless computing as well that you should be aware of before we proceed further:

• Execution duration: Serverless functions are designed to run for short durations of time, ideally somewhere under 300 seconds only. This is a hard limit set by most cloud providers, however, there are a few workarounds to this as well.
• Stateless: Serverless functions are purely stateless, which means that once the function completes its execution or is terminated for some reason, it won't store any data locally on its disk.
• Complexity: The smaller you make things, the more complex it's going to become. Although writing functions that perform very particular tasks is a good idea, it can cause complexity issues when you view your application as a whole system. A simple example can break one large application into some ten different functions such that each perform a specific task. Now you need to manage ten different entities rather than just one. Imagine if you had a thousand functions instead.
• Lack of tools: Although serverless computing is all at its hype, it still doesn't provide a lot of out-of-the-box tools for management, deployment, and even monitoring. Most of your monitoring tools that you use today were designed for long-running, complex applications; not for simple functions that execute in a mere seconds.
• Vendor lock-in: With each cloud provider providing its own unique tool sets and services around serverless computing, you often tend to get tied down to a particular vendor. This means that you cannot change your cloud provider without making some changes to your functions as well.

With these key points in mind, let us get to understanding and learning a bit more about the core serverless computing service that this book is all about--AWS Lambda.