- Serverless Tutorial
- Serverless - Home
- Serverless - Introduction
- Serverless - Installation
- Serverless - Deploying Function
- Serverless - Regions, Memory-Size, Timeouts
- Serverless - Service
- Serverless - Scheduled Lambdas
- Serverless - API Gateway Triggered Lambdas
- Serverless - Include/Exclude
- Serverless - Plugins
- Serverless - Packaging Dependencies
- Serverless - Layer Creation
- Serverless - REST API with DynamoDB
- Serverless - Telegram Echo Bot
- Serverless Useful Resources
- Serverless - Quick Guide
- Serverless - Useful Resources
- Serverless - Discussion
Serverless - Introduction
What is Serverless?
Well, the name gives you quite some hints. Computation without the headache of maintaining a server − that's the crux of serverless computing (or serverless in short). The concept is quite revolutionary and disruptive. It has been widely adopted. Several fresh applications begin by designing a serverless backend, and the legacy applications with dedicated servers are also slowly migrating to the serverless architecture. So what has led to the widespread adoption of serverless? As with everything, the economics have made serverless quite favorable.
You see, with serverless, you only pay for what you use. Imagine you need to perform some routine maintenance on your database every day. This process may take about 10 minutes every day.
Now, in the absence of serverless computing, your maintenance cron may be residing in a server. Unless you have something else to do with your server in the remaining time, you may end up paying for 24 hours, for a task that takes 10 minutes. Quite a waste of money, right? What if you were told that there is a new service that will charge you exactly for those 10 minutes that your maintenance cron takes to execute? Won't you want to simply switch to that new service? That's exactly why serverless adoption has been so swift and widespread. It has brought down the backend bills for several organizations, and also reduced their server maintenance headache.
The cloud service provider (AWS, Azure, etc.) takes the headache of making sure that the serverless application is available exactly when required, and in the quantity required. Thus, during high loads, you may invoke multiple serverless applications, while you may invoke a single application during normal load. And of course,you will pay for the extra invocations only for the duration of the high load.
What is Serverless, again?
The concept explained above seems great, but how do you implement it? You need a framework for that. It is called, uh, serverless.
The serverless framework helps us develop and deploy functions/ applications designed to run in a serverless fashion. The framework goes a step ahead and takes care of the deployment of the entire stack required for our serverless functions to run. What is a stack? Well, the stack comprises of all the resources that you will require for deploying, storing, and monitoring your serverless applications.
It includes the actual function/ application, storage containers, monitoring solutions, and a lot more.For example, in the context of AWS, your stack will consist of your actual Lambda function, S3 bucket for your function files, Cloudwatch resources linked to your function, and so on.The serverless framework creates this entire stack for us. This allows us to focus completely on our function. Serverless takes away the headache of maintaining a server and serverless (framework) takes away the headache of creating and deploying the stack necessary to run our function.
The serverless framework also takes care of assigning the necessary permissions to our functions/ applications.Some applications (examples of which we will see in this tutorial) even require databases to be linked to them. Serverless framework again takes care of creating and linking the DBs. How does serverless know what to include in the stack and which permissions to provide? All of it is mentioned in the serverless.yml file, which will be our main focus in this tutorial. More on it in the upcoming chapters.
Serverless in AWS
There are many services of AWS that fall under the umbrella of 'serverless computing'. You can find the entire organized list here. There are Compute services, Integration services, even Data Storage services (yes, AWS even has Serverless DBs). We will be focusing on the AWS Lambda functions throughout the tutorial. So what is AWS Lambda? The AWS Lambda website defines it as follows −
AWS Lambda is a serverless compute service that lets you run code without provisioning or managing servers, creating workload-aware cluster scaling logic, maintaining event integrations, or managing runtimes.
In layperson terms, AWS Lambda is your window to serverless computing on AWS. It is AWS Lambda that has made the serverless concept so popular. All you need to do is define your function and the trigger to your function, and the function will be invoked exactly when you want it to be invoked, and you will be charged only for the time the function takes to execute. What's more,you can link AWS Lambda with almost every other service that AWS provides − EC2, S3, dynamoDB, and so on.
Therefore, if you have already been a part of the AWS ecosystem, then Lambda integration is quite seamless. If you are new to the AWS ecosystem like I was when I first learned about AWS Lambda, it will act as a good gateway to the AWS universe.
In this tutorial, we will be learning all about the deployment of AWS Lambda functions using the serverless framework. Are you excited? Then move on to the next chapter to get started.