Serverless and FaaS

Topics

What is Serverless

Serverless is a term used to describe a computing model in which a cloud provider executes a piece of code in response to a specific trigger, such as an HTTP request or an event, and automatically manages the underlying infrastructure and resources required to run the code.

The developer does not need to worry about managing servers or infrastructure in a serverless model. They write and deploy their code, and the cloud provider runs it and scales it as needed. This can make it easier for developers to focus on writing code and building applications rather than worrying about infrastructure.

Serverless computing is often implemented using a technology called “function as a service” (FaaS), which allows developers to write and deploy code in the form of small, independent functions triggered by specific events. Some examples of FaaS platforms include AWS Lambda, Google Cloud Functions, and Azure Functions.

Serverless computing can be a cost-effective way to run applications since you only pay for the resources you consume when executing your code. It can also make it easier to scale applications up or down since the cloud provider handles the underlying infrastructure and resources automatically.

What is FaaS?

Function as a Service (FaaS) is a cloud computing model in which developers can create, deploy, and execute small, independent pieces of code, known as “functions,” without worrying about the underlying infrastructure. FaaS platforms provide developers with a simple, flexible, and scalable way to run code in response to specific triggers, such as an HTTP request, a timer, or an event.

FaaS platforms typically offer a range of features and tools to help developers build and deploy functions, including integrated development environments (IDEs), debugging tools, and monitoring and logging systems. They also handle the underlying infrastructure and resources required to run the code, such as servers and storage, and automatically scale the resources as needed to meet demand.

FaaS platforms are often used in serverless computing architectures, in which the cloud provider executes code in response to specific triggers and automatically manages the underlying resources. Some examples of popular FaaS platforms include AWS Lambda, Google Cloud Functions, and Azure Functions.

Example of a FaaS?

Here is an example of a function as a service that could be used to send an email in response to a specific trigger:

import smtplib

def send_email(to, subject, body):
server = smtplib.SMTP(‘smtp.example.com’)
server.login(‘user@example.com’, ‘password’)
message = f’Subject: {subject}\n\n{body}’
server.sendmail(‘user@example.com’, to, message)
server.quit()

def lambda_handler(event, context):
send_email(event[‘to’], event[‘subject’], event[‘body’])

In this example, the send_email function sends an email using the Simple Mail Transfer Protocol (SMTP). The lambda_handler function is the main entry point for the function, and it is triggered by a specific event (such as an HTTP request). When triggered, it calls the send_email function with the to, subject, and body parameters passed in the event data.

This function could be deployed to a FaaS platform, such as AWS Lambda, and triggered by various events, such as a new user sign-up, a database update, or a schedule. The FaaS platform would handle the underlying infrastructure and resources required to run the code and automatically scale the resources as needed to meet demand.

Backend and Front-end Roles in FaaS

In a typical web application, the frontend (also known as the client side) is the part of the application that runs in the user’s web browser, while the backend (also known as the server side) is the part of the application that runs on a server.

The front and back end are separate entities in serverless architecture, but the back end is implemented using FaaS functions. These functions are triggered by specific events, such as an HTTP request from the front end, and they execute code to perform a specific task, such as retrieving data from a database or sending an email.

From a technical perspective, the front-end and back-end communicate using APIs. The front end sends API requests to the backend to initiate specific actions, and the backend responds with the results of those actions. In a serverless architecture, the backend API is implemented using FaaS functions, which are triggered by the API requests and execute the necessary code to fulfill the request.

For example, consider a web application that displays a list of products to the user. The application’s front end might send an API request to the backend to retrieve the list of products from a database. The backend could implement this API using a FaaS function that queries the database and returns the results to the front end. The front end would then display the list of products to the user.

What kind of applications can be built with serverless?

Serverless computing is a flexible and scalable model that can be used to build a wide range of applications. Some examples of applications that can be developed with serverless include:

  • Web applications: Serverless architectures can be used to build and deploy web applications, using FaaS functions to handle backend tasks such as serving dynamic content, interacting with databases, and integrating with third-party APIs.
  • Mobile applications: Serverless architectures can be used to build and deploy mobile applications, using FaaS functions to handle tasks such as authenticating users, processing payments, and sending push notifications.
  • Microservices: Serverless architectures are well-suited to building microservices, which are small, independent units of code that can be composed to create larger applications. FaaS functions can implement individual microservices, easily scaled and managed independently.
  • Data processing and analytics: Serverless architectures can be used to build data processing and analytics pipelines, using FaaS functions to handle tasks such as data ingestion, transformation, and storage.
  • Internet of Things (IoT) applications: Serverless architectures can be used to build and deploy IoT applications, using FaaS functions to handle tasks such as processing sensor data, triggering alarms, and sending notifications.

Overall, serverless computing is a versatile model that can build many applications, from simple scripts to complex, scalable systems.

Limitations of Serverless

  • Cold starts: When a FaaS function is triggered for the first time or after a period of inactivity, it may experience a “cold start,” which is delayed as the function is initialized and the necessary resources are provisioned. This can result in slower performance for the first request and may be noticeable for infrequently used functions.
  • Resource limits: FaaS platforms often limit the resources allocated to a single function, such as memory and CPU. This can make it challenging to build certain applications, such as those that require a lot of processing power or large amounts of data.
  • Debugging and testing: Debugging and testing serverless applications can be more complex than traditional, monolithic applications since functions are independent units of code that are triggered by specific events. This can make it more difficult to replicate and test certain scenarios.
  • Dependency management: Serverless applications can depend on many external resources, such as databases and APIs, making dependency management more complex. This can be especially challenging in a microservices architecture, where functions are composed to create larger applications.
  • Cost optimization: While serverless computing can be a cost-effective model, it can also be more challenging to optimize costs compared to traditional, monolithic applications. This is because FaaS platforms charge based on the number of function invocations and the number of resources used rather than a fixed cost for a dedicated server. Careful monitoring and optimization of function usage can help to minimize costs.

Popular tools used in Serverless?

Several popular tools are commonly used to develop, deploy, and manage serverless applications:

  • AWS Lambda: AWS Lambda is a FaaS platform that Amazon Web Services (AWS) offers. It allows developers to build and deploy functions triggered by many events, such as HTTP requests, database updates, and system events.
  • Google Cloud Functions: Google Cloud Functions is a FaaS platform offered by Google Cloud. It allows developers to build and deploy functions triggered by many events, such as HTTP requests, database updates, and system events.
  • Azure Functions: Azure Functions is a FaaS platform offered by Microsoft Azure. It allows developers to build and deploy functions triggered by many events, such as HTTP requests, database updates, and system events.
  • Serverless Framework: The Serverless Framework is an open-source toolkit that helps developers build and deploy serverless applications on various cloud platforms, including AWS, Google Cloud, and Azure. It provides a set of libraries and tools for defining and deploying functions, as well as managing resources and dependencies.
  • Terraform: Terraform is an open-source infrastructure as code (IaC) tool that allows developers to define and manage infrastructure resources, such as servers, databases, and networks, using configuration files. It can deploy and manage serverless applications on various cloud platforms, including AWS, Google Cloud, and Azure.

These are just a few examples of the tools that are commonly used to develop, deploy, and manage serverless applications. There are many other options available, depending on the specific needs of the application and the cloud platform being used.

Open Source Serverless Frameworks

Several open-source serverless frameworks can be used to build and deploy serverless applications:

  • OpenFaaS: OpenFaaS is an open-source FaaS platform that can be deployed on various cloud platforms, including AWS, Google Cloud, and Azure. It provides a set of tools and libraries for building and deploying functions, as well as a user-friendly interface for managing functions and resources.
  • Kubeless: Kubeless is an open-source FaaS platform that can be deployed on top of the Kubernetes container orchestration platform. It provides tools and libraries for building and deploying functions and integrates with the Kubernetes ecosystem to provide additional features and functionality.
  • Fn: Fn is an open-source FaaS platform that can be deployed on various cloud platforms, including AWS, Google Cloud, and Azure. It provides a set of tools and libraries for building and deploying functions, as well as a command-line interface for managing functions and resources.
  • Apache OpenWhisk: Apache OpenWhisk is an open-source FaaS platform that can be deployed on various cloud platforms, including AWS, Google Cloud, and Azure. It provides tools and libraries for building and deploying functions and integrates with several other open-source technologies, such as Docker and Kubernetes.

Here are some key differences between these frameworks:

  • Deployment: OpenFaaS can be deployed on various cloud platforms, including AWS, Google Cloud, and Azure. Kubeless can be deployed on the Kubernetes container orchestration platform, while Apache OpenWhisk can be deployed on various cloud platforms, including AWS, Google Cloud, and Azure.
  • Programming languages: OpenFaaS and Apache OpenWhisk support many programming languages, including Python, JavaScript, Go, Java, and C#. Kubeless supports a smaller range of languages, including Python, JavaScript, and Go.
  • Features and functionality: OpenFaaS and Apache OpenWhisk provide various features and tools for building and deploying functions, including libraries and command-line interfaces. Kubeless integrates with the Kubernetes ecosystem to provide additional features and functionality, such as auto-scaling and resource management.

Overall, the choice between these frameworks will depend on the specific needs of the application and the cloud platform being used. OpenFaaS and Apache OpenWhisk are more flexible and support a wider range of languages and platforms, while Kubeless provides additional features and functionality by integrating with Kubernetes.

Table of Contents

Digiprove sealCopyright secured by Digiprove © 2022-2023
Scroll to Top