Serverless computing: real-world examples

Welcome to the world of serverless computing! If you’re diving into the world of serverless computing, you’ve probably heard all the buzzwords, but what does it really mean for you? In this guide, we’ll give you real-world examples to help you really understand how serverless computing can be used in your projects to increase efficiency and even reduce costs. Whether you’re an experienced developer or just starting out, this guide will help you realize the full potential of serverless computing.

Table of Contents

What is serverless computing?
Why serverless?
Serverless in action: examples for every use case

• Backend-as-a-Service (BaaS)
• Function-as-a-Service (FaaS)
• Event-driven computing
• Microservices

Popular serverless platforms

• AWS Lambda
• Google Cloud Functions
• Azure Functions

Serverless examples from the real world

• Serverless for startups
• Serverless for large companies
• Serverless in the IoT
• Serverless in AI/ML
• Serverless for content management
  

Challenges and disadvantages of serverless
How to get started
Conclusion

What is serverless computing?

Before we get into the examples, let’s quickly clarify what “serverless” actually means. Despite the name, serverless computing doesn’t mean that you don’t use servers. Rather, it means that you don’t manage them directly. The cloud provider takes care of the maintenance, scaling and resource allocation of the servers for you.

And this is where it gets interesting for you: with serverless, you can focus entirely on writing your code without worrying about the infrastructure. You don’t have to scale the servers when your app’s traffic increases, nor do you have to worry about downtime when traffic decreases. For developers like you who want to spend more time innovating and less time managing infrastructure, this is a game changer.

Why serverless computing?

Why should you care about serverless computing? Well, there are some compelling reasons:

• Cost efficiency: you only pay for the computing time you use. You don’t have to over-provision resources.
• Scalability: Serverless functions automatically scale with demand. No manual intervention is required.
• Focus on the code: You no longer have to worry about infrastructure maintenance, you can focus on feature development.
• Faster deployment: Developers can deploy code faster without having to worry about infrastructure deployment.
• Reduced complexity: You don’t have to worry about operating systems, patch updates or server configurations.

These are exactly the reasons why serverless computing is so popular. But to truly appreciate its value, you need to see it in action in real-world use cases. Let’s take a look at how you can use serverless in different scenarios.

Serverless Computing in action: examples for every use case

Serverless computing can be broken down into different categories, each tailored to specific needs. Here’s a look at how these apply to different real-world situations you might encounter.

Backend-as-a-Service (BaaS)

When you develop an application, certain backend components are essential: authentication, databases, file storage and user management. With Backend-as-a-Service, you can outsource these functionalities without having to write your own backend code.

Example: Imagine you are developing a mobile app that requires user authentication. Instead of developing and maintaining your own authentication system, you can use a service like Firebase Authentication. It takes care of everything, from login and user management to social media login integration.

This means you spend less time on backend logic and more time perfecting the user experience.

Function-as-a-Service (FaaS)

Function-as-a-Service (FaaS) allows you to execute individual functions in response to events without having to manage a server. You simply upload your function code and the cloud provider executes it when an event occurs, e.g. an HTTP request or a database update.

Example: Imagine you are working on an e-commerce website that needs to send an order confirmation email after a purchase. Instead of running an entire server just for this task, you could create a Lambda function in AWS. This function is triggered when a new order is placed, compiles the email and sends it out. The function is only executed when needed, and you only pay for the execution time.

Event-Driven Computing

With event-driven architecture, your code responds to specific events (such as changes in a database, user input or external system requests) without the need for a server to be constantly running. Serverless platforms can easily implement this pattern.

Example: Suppose you manage an online photo platform where users upload images. You need to resize the images for different device sizes. When a user uploads a photo, this triggers an event in your system and an AWS Lambda function automatically resizes the image.

This approach not only simplifies your code, but also ensures that you don’t waste resources by running processes that aren’t needed.

Microservices

You can use serverless architectures to build a collection of small, loosely coupled services, often referred to as microservices. Each microservice performs a specific task and communicates with other services via APIs.

Example: You build an application that provides up-to-date weather data. You could create a microservice that retrieves the weather data, another that processes the data and a third that displays it to users. Each service runs independently in its own serverless function and scales as required.

The beauty of this is the modularity: you can update one part without affecting the rest of the application. you also save on infrastructure costs as the services only run when needed.

Popular serverless computing platforms

There are several serverless platforms that allow you to take advantage of serverless computing. Let’s take a look at the most popular platforms and what they offer.

AWS Lambda

AWS Lambda is probably the best-known serverless platform. It is part of the AWS ecosystem and integrates with many other AWS services such as S3, DynamoDB and API Gateway. You write your functions, choose when they should be triggered (HTTP requests, file uploads, etc.), and Lambda does the rest.

Google Cloud Functions

Google Cloud Functions is Google’s answer to serverless. Like AWS Lambda, it is event-driven, meaning your functions are executed in response to events generated by other Google Cloud services. It’s a good choice if you’re already working within the Google Cloud ecosystem, especially if you’re using Google services like BigQuery or Firebase.

Azure Functions

If you are working within the Microsoft ecosystem, Azure Functions is the serverless platform to consider. It offers deep integration with Azure services such as Cosmos DB and Azure DevOps. Azure Functions also supports a wide range of programming languages, making it flexible for a variety of development teams.

Serverless Computing examples from practice

Now that we’ve covered the basics, let’s look at specific examples of serverless computing in different industries and use cases.

Serverless for startups

If you work in a startup or are building your own project, serverless can be a lifesaver. Startups are usually on a tight budget and need to scale quickly without getting bogged down in infrastructure.

Example: Imagine a startup developing a real-time chat application. By using AWS Lambda and API Gateway, you can process incoming chat messages, trigger events for notifications and even scale your service to thousands of users without manual intervention.

With serverless, you don’t pay for unused servers, which is a huge advantage for a startup where every dollar counts.

Serverless for large enterprises

Large enterprises are also adopting serverless architectures to improve scalability and reduce infrastructure costs.

For example, imagine a retail giant like Nordstrom uses serverless to run its online shopping system. During peak times, like Black Friday, traffic can spike unpredictably. Instead of over-provisioning servers (which is expensive), the company can use a serverless model to automatically scale with demand.

Serverless is also perfect for handling batch jobs in large organizations, such as payroll or data analytics.

Serverless in the IoT

The Internet of Things (IoT) generates enormous amounts of data that can be inefficient to process using conventional servers. Serverless computing offers a solution.

Example: Imagine you are working on a project with smart home devices that send data to the cloud. A serverless architecture can process the incoming data in real time, e.g. turn on the lights when someone enters a room.

With AWS Lambda, for example, you can trigger a function as soon as the IoT device sends new data and analyze it in real time.

Serverless computing in AI/ML

AI and ML tasks are resource-intensive, but serverless computing can help optimize costs by running only when needed.

For example, let’s say you’re developing a speech recognition app that needs to convert speech to text. Instead of running a server around the clock, you could set up a serverless function in Google Cloud Functions that is triggered whenever a user uploads a new speech file. The function is executed, transcribes the file and then saves the result in a database.

This way, you only pay for the transcription process when it is used, which significantly reduces overheads.

Serverless computing for content management

Running a CMS like WordPress can be resource intensive and requires continuous server management. Serverless computing offers an alternative for content-driven websites or applications.

Example: Suppose you manage a news website with high traffic at certain times of the day. With serverless frameworks like Netlify or Vercel, you can host your static website while using serverless features to handle dynamic tasks like commenting systems, user logins or search queries.

This approach drastically reduces infrastructure management overhead while ensuring that your website can handle traffic spikes with ease.

Challenges and disadvantages of serverless computing

Of course, no technology is perfect. Although serverless has many benefits, there are also some challenges you should be aware of:

• Cold starts: functions that haven’t been used for a while may take longer to start up the first time, which can impact performance.
• Limited execution time: Many serverless platforms have a maximum execution time, so tasks that require longer processing may not be suitable.
• Vendor dependency: If you rely too heavily on a single cloud provider’s serverless infrastructure, it can be difficult to switch platforms later.
• Complexity for large applications: Managing multiple serverless functions for a large application can become complex, as troubleshooting and tracking across all functions can be difficult.

How to get started

So, are you ready to dive into the world of serverless computing? Here are a few tips to help you get started:

1. Choose the right platform: decide which serverless platform best suits your needs. AWS Lambda, Google Cloud Functions and Azure Functions are good choices depending on your technical setup.
2. Start small: If you’re new to serverless, start with a simple project, such as setting up an API with AWS Lambda and API Gateway. Once you have familiarized yourself with the technology, you can expand it step by step.
3. Use tutorials and documentation: Every serverless platform has excellent documentation that you should use. AWS, for example, has a variety of step-by-step guides to walk you through creating your first Lambda function.
4. Test and monitor: Testing is very important in serverless environments as functions often interact with multiple services. You should also use monitoring tools to keep an eye on performance and detect problems early on.

Conclusion

Serverless computing opens up a world of possibilities, whether you’re building a startup, running a large enterprise or working on an IoT or AI/ML project. The flexibility, cost efficiency and scalability are unparalleled and give you more time to focus on what really matters: developing great apps and services.

By now, you’ve seen serverless being used in the real world — from backend systems and microservices to AI/ML and IoT. So why don’t you give it a try? Jump into a platform like AWS Lambda or Google Cloud Functions and start experimenting. You’ll be amazed at what you can build without ever touching a server.

If you’re ready to take the leap into serverlessness, now is the perfect time. With these examples and tips, you can transform your development process and take full advantage of the serverless revolution.