What Is Serverless Computing? How It Works + Examples

Serverless computing is one of the fastest-growing areas in software development, along with hybrid clouds and multi-cloud strategies.

The global serverless architecture market is experiencing rapid growth. It was valued at approximately $18 billion in 2025 and is projected to exceed $22 billion in 2026, growing at a compound annual growth rate of roughly 22–24%. By the mid-2030s, multiple analyst projections place the market above $100 billion.

The serverless approach promises to help developers beat the cons of self-managed and even virtual server infrastructure.

But is serverless right for you?

In this detailed guide, we’ll explore what serverless computing is, how serverless architecture works, and the advantages and disadvantages you should weigh before making the switch.

What Is Serverless?

Serverless is a cloud-based development approach that frees developers to focus solely on writing code to solve business problems, rather than managing server issues. In a serverless computing model, the cloud provider dynamically allocates compute, storage, and networking resources on demand — and you pay only for what you use.

The computing approach uses event-driven functions to determine the scope of those needs. When an event occurs — an HTTP request, a file upload, a database change — the provider spins up the necessary resources, executes the function, and scales back down to zero when the work is done. That’s why serverless architecture is also referred to as Function-as-a-Service (FaaS).

Before serverless, developers had to anticipate application usage and buy fixed numbers of servers or amounts of bandwidth to support operations. That typically meant purchasing more capacity than necessary, because underprovisioning would degrade application performance. The redundancy approach cost more than many teams were willing to accept. Maintaining a dedicated physical server, and even a virtual one, also took time away from primary coding work.

Serverless architecture changes this dynamic entirely. 

Serverless services allow you to pay for only the resources you use:

The pay-as-you-go billing model helps teams save time and money to be more agile and respond to customer needs faster.

Serverless Computing 101: How It Works

Physical servers are still involved in serverless computing. But developers do not handle infrastructure issues.

So, why is it called serverless?

In a serverless approach, a cloud service or vendor manages all the backend services. Those services are everything DevOps needs to get their application up, running, up-to-date, and up-to-the-task, and include:

Your cloud service provider takes care of all that for you. This model contrasts with the Infrastructure-as-a-service (IaaS) model, where your developers also need to handle app scaling and host management tasks.  

Serverless developers do not have to know anything about the infrastructure supporting their code. From their end, the servers do not exist.

They just need to focus on writing code that solves customers’ issues fast, affordably, and on flexible infrastructure.

What Is Serverless Computing Used For?

The serverless approach is suitable for organizations that want to streamline their cloud migration or optimize the efficiency of their cloud-based applications.

Serverless is ideal for high-latency backend tasks such as multimedia and big data processes, thanks to edge computing.  

Edge computing is a technology that brings data processing closer to where it is created by using localized data centers. It helps prevent the potential slowness and latency in data transfers that physical distance from a data center tends to cause.

It helps save bandwidth, boosts response times, streamlines data transfers, and supports real-time responsiveness.

Common serverless application types include event-driven data processing (responding to file uploads, IoT sensor readings, or database changes in real time), API backends that handle variable traffic without overprovisioning, scheduled batch jobs such as nightly ETL pipelines or report generation, and chatbot or voice-assistant backends where usage spikes unpredictably.

Overall, the edge computing aspect of serverless helps make deploying applications faster and more cost-efficient. Serverless computing is also ideal for applications that need rapid, scalable, and efficient infrastructure to support fast growth. If you can’t predict how much server load an application might take, serverless architecture can be the most dynamic way to accommodate rapid changes.

Real Life Serverless Architecture Examples

We’ll take three examples of companies you know all too well.

Coca Cola

When the soft drinks behemoth piloted serverless computing on its vending machines, it saw significant savings and fully embraced the approach.

How it works:

Vending machines need to communicate with a headquarters, where inventory is kept. Coca-Cola realized that keeping all vending machines on at all times was wasteful.

Now, every time a person purchases a drink, the action acts as a trigger that activates the underlying Amazon Web Services (AWS) Lambda function through the machine’s payment gateway.

Coca-Cola then only pays AWS for the actual number of transactions that happen, not on a fixed monthly/yearly fee, regardless of sales like before.  

Slack

The cloud-based platform uses several bots to power successful online collaboration among teams.

How it works:

Slack’s Marbot, in particular, is the serverless bot that helps Slack developers and operations teams receive notifications from AWS through Slack.

It works with Auto-scaling Notifications, CloudWatch alarms, and CloudWatch Events to make that happen fast, dynamically, and affordably.

Netflix

When you’re everyone and their aunt’s favorite movie streaming service, you get to serve billions of hours of video to hundreds of millions of people every year.

Netflix needs to constantly encode millions of video hours from publishers before it can stream them to users. The streaming service requires the video to be encoded into 60 separate parallel streams.

How it works:

The files upload to S3, and AWS triggers an event that calls AWS Lambda to split the videos into five-minute clips. The platform then aggregates and deploys the processed video using sophisticated rules.

But there’s more.

Using serverless helps Netflix achieve a couple of gigantic needs, according to John Bennet, Senior Software Engineer at Netflix:

Netflix completed a full migration to the AWS serverless infrastructure for those reasons.

Learn how Netflix, Slack, Lyft, and others built their cloud cost management tools to monitor and optimize their cloud costs in our article, “Cloud Cost Management Tools Used at the World’s Top Tech Companies”.

What Are The Benefits Of Using Serverless?

According to Datadog’s 2025 State of Containers and Serverless report, more than 70% of organizations using AWS now run at least some production workloads on Lambda. Nearly 80% of organizations running containers have also adopted Lambda, signaling that serverless has moved well beyond early adoption.

We’ve already touched on some of the advantages of serverless computing. Let’s examine them in more detail.

Credit: O’Reilly 2019 Serverless Survey

1. Serverless is cost-efficient

Serverless takes a cost-first approach.

That means you do not have to spend a premium to buy, set up, and hire expert staff to manage physical or cloud-based server infrastructure. You do not have to spend money and time upgrading your code’s underlying infrastructure.

Instead, you can focus on using the platform to develop your core product so that it can reach the market as soon as possible.

Additionally, the pay-per-usage billing method allows developers to pay only for the services they use. Some vendors, such as AWS, can calculate prices based on 100-millisecond increments.

You don’t need to burn your IT budget on an expensive monthly fee, only to end up using only 15-25% of your paid capacity.

2. Automatic Scaling Without Capacity Planning

The traditional server and cloud computing approaches require that you allocate fixed resources and hope everything goes to plan.

However, a spike in usage from, say, a viral promotion that increases your server requests can lead to degraded application performance. On the contrary, serverless would allow you to handle as many requests as possible without compromising performance.

You would just need to increase functions, which happens automatically inside the server.  

3. You can make quick and real-time updates to your application

In a serverless environment, vendors provision a collection of functions. That means you can upload bits of code to help launch a “bare minimum” version of your application to market.

You can then upload updates on an ongoing basis to further improve the application. A serverless architecture would help you update the app one function at a time. Yet, you can still make changes to the whole application, add extensive features, and patch multiple security issues if you want.

4. Serverless computing boosts productivity

When server management tasks do not take your developers off their primary coding projects, they can create solutions to existing issues much faster. Or, they can focus on improving the DevOps metrics that matter so you can keep up with fast-changing software trends and user experience demands.

That also means enterprises can devote fewer people and processes to create fully scalable applications. The rest of the team can help with other vital tasks.

The Disadvantages Of Serverless Computing

Serverless is not perfect, either. So, what are some of the challenges associated with serverless computing?

1. Cold starts tend to cause latency

Serverless computing uses an aggressive resource reclamation approach to produce its cost benefits. If your application doesn’t trigger any function for a while, the cloud provider’s system puts it to sleep so it can save resources.

The next time your application calls up the function, it takes a moment to spin back up, causing latency. This slight delay is known as a cold start.

While the latency lasts for only milliseconds, in heavy applications, that time may mean delayed customer requests. For example, an e-commerce application needs to act fast so customers won’t feel frustrated and abandon their cart.

Top cloud providers employ tactics such as utilizing a Chrome V8 engine that can cold-start and execute JavaScript code in under five milliseconds.  

2. Serverless architecture may not be ideal for some applications

Serverless cloud providers are responsible for allocating dynamic resources. Some vendors may limit the amount of their overall resources you can use, potentially restricting you if you need more.  

Furthermore, their service may require clients to use specific protocols to interact with their platform. That means you may need to give up some customization options and surrender to what they have on offer.

So, you’ll want to work with a vendor who understands your needs and can help you achieve them without having to make significant sacrifices.

3. Debugging Distributed Functions Is Harder

First, serverless computing breaks monolithic stacks into smaller, independent functions. Finding the specific problem area can be tricky.

Second, your DevOps team doesn’t see how their code works on the server-side, making testing and debugging even trickier. Like Netflix, you would need to work closely with your vendor to identify and patch any glitches before they become a major issue for your application’s end users.

4. Security Requires Extra Attention

When you cede control of your code’s infrastructure to a third-party provider, you trust them to keep the service foolproof.

Yet, serverless computing handles several customers’ code on the same server simultaneously. That scenario is referred to as multitenancy in cloud computing, where several customers share server resources.  

Depending on your cloud provider, any mix-ups can lead to data leaks. That’s a big problem if you handle sensitive data, such as health, financial, or other personal information.

Also, if you decide to migrate a legacy application to the cloud without first modernizing it to work securely in the cloud, you may expose yourself to hacking. One way to prevent these issues from ruining your application’s performance is to work with a vendor that hosts each serverless function in its sandbox.

5. Switching serverless providers can be a challenge

There are several cloud providers right now, each offering slightly different advantages and workflows. In reality, though, switching vendors is not always practical.

Successfully using a serverless approach requires that your vendor customizes the infrastructure to your specific needs. When your core application’s functions are so intertwined with a particular vendor, leaving would mean making major changes to your application’s architecture before and after the transition — a costly and time-consuming affair known as vendor lock-in.

Some vendors attempt to solve this by writing code in an easier-to-migrate language, such as JavaScript, instead of through the service workers API.

How Does Serverless Compare To Other Cloud Computing Models?

How does the Function-as-a-Service model in serverless computing compare to other backend approaches?

Serverless vs. Platform-as-a-Service (PaaS)

PaaS is a cloud computing approach where developers rent essential tools they need to develop and run an application. The key difference is that PaaS environments typically require you to pick a runtime size and pay for it whether traffic arrives or not. Serverless scales to zero when idle and charges only for actual execution time. PaaS also does not always run applications at the cloud’s edge, tends to be slower to scale horizontally, and requires more manual configuration for capacity planning.

Serverless vs. Backend-as-a-Service (BaaS)

Like serverless, BaaS is a computing model where a vendor provides backend services, allowing developers to focus on improving frontend functions. But unlike serverless, the BaaS approach does not necessarily run applications at the edge of cloud computing or use event-driven triggers. BaaS tends to offer pre-built features (authentication, database, push notifications) rather than custom function execution.

Serverless vs. Containers

Containers package an application and its dependencies into a single deployable unit that runs consistently across environments. Both containers and serverless computing abstract away the underlying infrastructure, but they differ in control and responsibility. With containers (e.g., Docker on Kubernetes), your team still manages orchestration, scaling policies, and cluster maintenance. Serverless offloads all of that to the provider. Containers offer more control over the runtime environment and are better suited for long-running processes, while serverless excels at short-lived, event-driven workloads with unpredictable traffic patterns. Many organizations use both — containers for steady-state services and serverless for bursty, event-driven tasks.

Top Serverless Architecture Tools

As you can see, you can mitigate most of the downsides of serverless computing. Furthermore, your competition may already be taking advantage of the architecture’s benefits.

If you are considering implementing a serverless architecture for your needs, you have several cloud providers to choose from.

But you can use several tools to make your serverless implementation simpler.

Those tools include:

CloudZero

CloudZero provides cloud and AI cost intelligence for engineering, finance, and operations teams that want to understand their cloud costs — including COGS and unit costs, such as cost per customer — shift engineering decisions left, and optimize spend across AWS, Azure, GCP, Kubernetes, and AI providers. The platform provides real-time insights that help teams map costs to products, people, and features. Learn more about how CloudZero puts engineering in control of cloud spend.

AWS CodeBuild + CodePipeline

AWS CodeBuild and CodePipeline form a fully managed, serverless CI/CD solution that integrates seamlessly with Lambda. CodeBuild compiles your code, runs tests, and produces build artifacts. CodePipeline, on the other hand, automates the release process from commit to deployment.

This configuration eliminates the need for managing custom CI environments. You only pay for the build time used, and it scales automatically without pre-provisioned capacity. CodeBuild supports multiple runtimes, longer build durations, and fine-grained IAM control. This makes it more flexible and better supported than legacy tools such as Jenkins or LambCI.

Serverless Framework

The Serverless Framework is the most widely adopted open-source CLI tool for building and deploying serverless applications. It supports AWS Lambda, Azure Functions, and Google Cloud Functions through a single configuration file, making it easier to define functions, events, and resources without wrangling CloudFormation or ARM templates directly. Version 4 (released 2024–2025) added managed instances, built-in AppSync plugins, and native AWS SSO support.

AWS SAM (Serverless Application Model)

AWS SAM extends CloudFormation with shorthand syntax purpose-built for serverless resources. It includes a local testing environment (sam local) that lets developers invoke Lambda functions on their machine before deploying, which significantly shortens the feedback loop. SAM integrates natively with CodePipeline and CodeBuild for CI/CD, making it a natural fit for teams already invested in the AWS ecosystem.

Terraform (with Serverless Modules)

Terraform by HashiCorp is an infrastructure-as-code tool that supports serverless deployments across multiple cloud providers through a single declarative language (HCL). For teams running serverless functions alongside other infrastructure — databases, networking, monitoring — Terraform provides a unified workflow. Its state management and plan/apply cycle give teams visibility into exactly what will change before any deployment happens.

These tools can help you transition to serverless computing with minimal disruptions, and with the cost visibility to know your architectural decisions are paying off.

Optimize Your Serverless Approach With Cloud Cost Visibility

If you are a large organization, implementing serverless architecture can have significant cost, personnel, scalability, and security benefits.

If you are a nimbler startup, the serverless approach can help you get to market fast. You can then push updates as you test, debug, and collect user feedback. Next, you can add features that align with your customers’ aspirations to retain them longer.

However, migrating to the serverless architecture requires more than just “lifting and shifting” your applications. Without cost visibility, it’s impossible to ensure you’re making effective architectural decisions to optimize.

With CloudZero, you can make migration costs clear and predictable — for you and your finance team. Our approach provides real-time visibility into cloud costs during migration and maps these costs to specific products, features, and teams.

to see how you can use cloud cost intelligence to help you switch to serverless architecture.

Software and pricing information last verified May 2026. Features, pricing, and availability may have changed. Please verify current details with vendors before making decisions.