How to Build Your First Serverless App

Are you creating an app but now feel overwhelmed by the thought of managing servers? 

As a novice developer, you’ll struggle with server setup, maintenance costs, and complex infrastructure. These challenges often stop people from even starting their projects.

Here’s the good news.

Serverless computing changes everything. With serverless apps, you don’t worry about servers at all. Someone else handles the heavy lifting while you focus on writing code. Plus, you only pay when your app runs, making it perfect for beginners on a budget.

In this guide, you’ll learn:

• Step-by-step instructions to build and deploy your function
• What does serverless computing mean
• How to choose the right platform for your first serverless app
• Clever tricks to avoid common mistakes
• Ways to save money while keeping your app fast

Let’s jump right in and build something incredible together.

Building Your First Function Step by Step

Let’s build a simple serverless function together. We’ll create a basic API that returns a greeting message. 

This might sound too simple, but every complex app starts with basics like this.

Step 1: Set Up Your Account

First, create an account with your chosen platform. For AWS, go to aws.amazon.com and click “Create an AWS Account.” You’ll need an email address and a credit card, but remember, you won’t pay anything if you stay within the free tier.

After signing up, enable two-factor authentication for security. Then download the command-line tools for your platform. For AWS, this means installing the AWS CLI. For Azure, download the Azure Functions Core Tools. Google Cloud needs the gcloud CLI.

These tools let you control everything from your computer’s terminal. It feels more professional than clicking around a website, and you’ll need this skill as you grow.

Step 2: Write Your Function

Open your favorite code editor. Let’s write a simple function in Python because it’s easy to read. Create a new file called lambda_function.py and add this code:

def lambda_handler(event, context):

name = event.get(‘name’, ‘Friend’)

return {

‘statusCode’: 200,

‘body’: f’Hello, {name}! Welcome to serverless.’

}

This function does something simple.

It takes a name and returns a greeting. If no name is provided, it says “Friend” instead. The function accepts an event (which contains incoming data) and context (which gives you information about the function itself).

Notice how short this code is. No server configuration, no complex setup. Just the logic you care about.

Step 3: Create Supporting Files

Serverless functions often need a configuration file. For AWS, create a file called requirements.txt to list any extra libraries your code needs. For this simple function, the file can stay empty.

If you use JavaScript instead of Python, you’d create a package.json file. The idea stays the same: list your dependencies so the platform knows what to install.

Step 4: Deploy Your Function

Now comes the exciting part. Open your terminal and navigate to your project folder. For AWS Lambda, type these commands:

zip function.zip lambda_function.py

aws lambda create-function –function-name MyFirstFunction \

–runtime python3.9 –role your-role-arn \

–handler lambda_function.lambda_handler \

–zip-file fileb://function.zip

This creates a zip file with your code and uploads it to AWS. The platform unpacks it, sets up everything, and prepares to run your function.

For Azure, you’d use:

func init MyFirstFunction –Python

cd MyFirstFunction

func azure functionapp publish MyFirstFunction

Google Cloud uses:

gcloud functions deploy my-first-function \

–runtime python39 –trigger-http \

–entry-point lambda_handler

Each platform has slightly different commands, but they all accomplish the same goal: getting your code onto their servers.

Step 5: Test It Out

After deployment is complete, you’ll receive a URL. Copy that URL and paste it into your web browser. Add ?name=YourName to the end.

You should see: “Hello, YourName! Welcome to serverless.”

Congratulations! You just deployed your first serverless function. It’s live on the internet, ready to handle requests from anywhere in the world.

Connecting the Pieces

A single function is great, but real serverless apps need multiple parts working together. Let’s expand your function into a tiny application.

Add a Database

Your function needs to store information. Serverless databases like AWS DynamoDB, Azure Cosmos DB, or Google Firestore work perfectly here. These databases scale automatically, just like your functions.

For example, you could store user messages in DynamoDB. Each time someone sends a message through your function, you save it. Later, another function retrieves all messages when someone requests them.

Create an API Gateway

Right now, your function has a long, ugly URL. An API Gateway provides clean, professional URLs such as api.myapp.com/greet. It also adds features such as rate limiting (to prevent abuse) and authentication (to verify who’s allowed to use your app).

AWS API Gateway, Azure API Management, and Google Cloud Endpoints all do this job well. They sit in front of your functions and route traffic properly.

Add More Functions

Think of your serverless app as a team of specialists. One function handles user login. Another processes payments. A third sends email notifications. Each function does one job well.

This design, called microservices, makes your app easier to maintain. When you need to fix the email function, you don’t touch the payment function. Everything stays separate and organized.

Or you just covered all that, and you don’t even know what serverless means?

What Does Serverless Mean?

Think of serverless like using electricity in your home. You flip a switch, the lights turn on, and you pay for what you use. You don’t need to know how a power plant works or how to maintain the electrical grid. That’s exactly how serverless computing works.

When you build a serverless app, you write small pieces of code called functions. These functions sit quietly, waiting. When someone uses your app or triggers an event, the function wakes up, does its job, and goes back to sleep. 

The cloud provider handles everything behind the scenes, including servers, scaling, updates, and security.

This approach flips traditional app development on its head. 

Before serverless, developers had to buy servers, set them up, monitor them constantly, and pay for them 24/7, even when no one was using the app. Now, servers still exist somewhere, but you never see them or manage them.

The market tells us this approach works. Right now in 2026, the serverless computing industry is worth $26.51 billion, and experts predict it will grow to $76.91 billion by 2030. That’s because more developers discover how much easier life gets without server headaches.

Why Beginners Love Serverless Apps

Let me share why serverless makes sense for your first project.

You Save Money Fast

Traditional server hosting costs money every single day. Even when your app sits idle at 3 AM, you’re still paying. Serverless flips this model completely. You pay only when your code runs, measured in milliseconds.

For example, AWS Lambda gives you 1 million free requests every month. Google Cloud Functions offers 2 million free requests monthly. This means you can build and test your serverless app for weeks or months without spending a penny. Companies that switched to serverless report cutting their infrastructure costs by 60-80%. 

That’s a huge savings.

Your App Grows Automatically

Imagine launching your app, and suddenly 10,000 people try to use it at once. With traditional servers, your app would crash. You’d scramble to add more servers, which would take time and cause downtime.

Serverless handles this automatically. Whether one person uses your app or one million people do, the platform adjusts instantly. The system creates more copies of your function when needed and removes them when traffic drops. You don’t lift a finger.

You Build Faster

Traditional app development requires knowledge of servers, networking, load balancers, databases, and security configurations. That’s a lot to learn before writing your first line of actual app code.

With serverless, you skip most of that learning curve. 

You write your function, upload it, and boom. You’re done. This speed matters. What used to take days or weeks now takes hours. You can test ideas quickly, fail fast, and move on to better ideas.

Picking Your First Platform

Three major platforms dominate the serverless world: AWS Lambda, Azure Functions, and Google Cloud Functions. Let’s break down each one in plain English.

AWS Lambda

AWS Lambda leads the pack with the biggest market share. It supports popular programming languages like Python, JavaScript, Node.js, Java, Go, Ruby, and C#. The free tier includes 1 million requests per month and 400,000 GB-seconds of compute time.

Lambda works well if you plan to use other Amazon services, such as S3 for file storage or DynamoDB for databases. Everything connects smoothly. However, the AWS dashboard can feel overwhelming at first with its hundreds of services and options.

Azure Functions

Azure Functions are a natural fit if you already work in the Microsoft ecosystem. It supports languages like C#, Java, JavaScript, Python, PowerShell, and Go. You get 1 million free requests monthly.

Azure shines for enterprise applications and business tools. It integrates perfectly with Office 365, Active Directory, and other Microsoft products. The dashboard feels familiar to Windows users.

Google Cloud Functions

Google Cloud Functions offers 2 million free requests per month, double the limit from AWS. It supports JavaScript, Python, Go, Java, .NET, Ruby, and PHP.

Google excels at data processing and machine learning tasks. If your serverless app analyzes data or uses AI features, Google’s platform makes this easier. The interface looks cleaner and simpler than AWS.

How to Choose

Ask yourself these questions:

• Do you already use cloud services? Stick with the same provider for easier integration.
• What programming language do you know? Pick a platform that supports it well.
• How much free usage do you need? Google offers the most generous free tier.
• What does your app do? Data-heavy apps often work better on Google, while business apps prefer Azure.

For beginners learning from scratch, I recommend starting with AWS Lambda. Why? It has the most tutorials, the largest community, and the most job opportunities if you want to make this a career later.

Avoiding Common Beginner Mistakes

Let’s talk about problems you’ll likely face, and how to dodge them.

Cold Starts: When Functions Feel Sluggish

Remember how functions go to sleep when not used? Waking them up takes time, usually under 1 second. Research shows that cold starts affect fewer than 1% of requests, but those delays can still annoy users.

Python and JavaScript functions wake up fast, typically in 200-400 milliseconds. Java and C# functions take longer, sometimes 500-700 milliseconds. If speed is critical to your app, choose Python or JavaScript.

You can also “warm up” functions by calling them regularly. Set up a timer that pings your function every 5 minutes. This keeps it awake and ready. Some platforms offer “provisioned concurrency,” which keeps functions permanently warm for a small fee.

Debugging Gets Tricky

When your code runs on your computer, you can see exactly what happens. Serverless functions run somewhere in the cloud, making problems harder to spot.

Every platform provides logging tools. AWS has CloudWatch, Azure has Application Insights, and Google has Cloud Logging. These tools show you what your function does, any errors it encounters, and how long operations take.

Add print statements liberally in your code. Something like print(“Processing payment for:”, user_id) helps you track what’s happening. In serverless, good logging makes the difference between quick fixes and hours of frustration.

Vendor Lock-In

Each platform works differently. Code written for AWS Lambda won’t run on Google Cloud Functions without changes. This creates “vendor lock-in,” where switching platforms becomes expensive and time-consuming.

To minimize this risk, keep your business logic separate from platform-specific code. Put the core functionality of your app into standalone functions. Then create thin wrapper functions that connect to AWS, Azure, or Google.

This approach requires slightly more up-front work, but pays off if you ever need to switch platforms or run on multiple platforms simultaneously.

Unexpected Costs

While serverless usually costs less, you can still be surprised. Functions that run constantly or process vast amounts of data can generate big bills.

Set up billing alerts immediately. Both AWS and Google let you create alarms that email you when spending exceeds a threshold. Set your first alert at $10, then $50, then $100. You’ll catch problems before they become disasters.

Also, review the pricing calculator for your platform. AWS has one at calculator.aws. Play with different scenarios: “What if my function runs 10,000 times per day?” versus “What if it runs 10,000 times per hour?” Understanding the math prevents surprises.

Making Your App Fast and Cheap

Let’s cover practical tips that improve performance while reducing costs.

Keep Functions Small

Each function should do one thing well. A function that logs users in shouldn’t also process their photos. Separate tasks into separate functions.

Small functions start faster, use less memory, and cost less. They’re also easier to debug because there’s less code to check when something breaks.

Choose Memory Wisely

When you create a function, you choose how much memory it gets. More memory costs more, but it also makes functions run faster because you get more CPU power.

Start with 512 MB and test your function. If it completes quickly, try reducing it to 256 MB. If it times out or runs slowly, increase to 1024 MB. Finding the sweet spot between cost and speed takes experimentation.

Remove Unused Dependencies

Every library your function imports adds to its size. Bigger functions take longer to start up, especially during cold starts. Go through your imports and remove anything you don’t use.

For JavaScript, use tools like webpack or esbuild to bundle only the code you need. For Python, create a virtual environment with just your required packages. This attention to detail can cut cold start times in half.

Cache When Possible

If your function fetches the same data repeatedly, cache it. Store frequently-accessed information in memory between function calls. The execution environment sticks around for a while, so global variables persist across multiple invocations.

For example, if you fetch a configuration file at startup, store it in a global variable. Subsequent invocations reuse that data without re-fetching it. This speeds things up significantly.

What the Future Holds

Serverless computing continues to evolve rapidly. Here’s what’s coming soon that you should know about.

Edge Computing Gets Popular

Edge computing runs your functions closer to your users geographically. Instead of code running in one giant data center, it runs on servers near Tokyo for Japanese users, near London for British users, and so on.

This approach cuts response times dramatically. Cloudflare Workers and AWS Lambda@Edge lead this trend. As internet speeds increase and users demand instant responses, edge computing will become standard.

AI Integration Becomes Normal

More platforms now make it easy to add artificial intelligence to your functions. Google Cloud Functions integrate seamlessly with TensorFlow and other ML frameworks. AWS offers SageMaker for machine learning.

Soon, adding smart features like image recognition, language translation, or recommendation engines to your serverless app will be as simple as calling a function. You won’t need a PhD in AI to build intelligent apps.

Multi-Cloud Strategies Grow

Companies increasingly use multiple cloud providers simultaneously. They might run some functions on AWS, others on Google Cloud, and still others on Azure. This approach, while complex, prevents vendor lock-in and leverages each platform’s strengths.

Tools like the Serverless Framework and Terraform make managing multi-cloud deployments easier. As these tools mature, expect more developers to adopt this strategy.

According to recent surveys, 89% of enterprises now operate cloud-native technologies, showing how mainstream these practices have become. This mainstream adoption means more jobs, better tools, and stronger communities supporting serverless developers.

Your Next Steps

You’ve learned the basics of serverless computing, how to choose a platform, and how to build and deploy your first function. 

Where should you go from here?

Start by building something real, even if it’s simple. 

Create a function that sends you a daily weather report. Build a URL shortener. Create a simple API to store and retrieve notes. The best learning comes from doing.

Join the serverless community. 

Reddit’s r/serverless and AWS Lambda forums have helpful people who answer questions. Twitter and Discord have active serverless channels where developers share tips and solve problems together.

Read the official documentation for your chosen platform. 

AWS, Azure, and Google all maintain excellent guides, tutorials, and reference materials. Bookmark these resources and refer to them often.

Experiment with different services. Try connecting your function to a database. Set up a scheduled task that runs automatically. Add authentication to protect your API. Each small project teaches new skills.

Most importantly, don’t let mistakes discourage you. 

Every developer breaks things while learning. When your function returns an error or your bill surprises you, treat it as a learning opportunity. Google the error message, ask for help, and keep building.

The serverless revolution is happening now. The industry continues growing at 23.7% annually, creating opportunities for developers who understand these technologies. By starting today, you’re positioning yourself at the forefront of modern app development.

Remember that serverless isn’t just a technical choice, it’s a mindset shift. You’re no longer a server administrator who happens to write code. You’re a developer who focuses purely on solving problems and creating value. The servers, scaling, and infrastructure fade into the background where they belong.

The hardest part is beginning, and you’ve already done that by reading this guide. Take what you’ve learned, open your code editor, and create something amazing.