Serverless architecture has moved well past "emerging technology" status. In 2026, it is a default deployment model for event-driven workloads, AI inference endpoints, and scalable SaaS backends. The numbers reflect this shift: the global serverless computing market reached USD 28 billion in 2025 and is projected to grow to USD 92 billion by 2034, at a CAGR of approximately 14–18% depending on the segment. More than 70% of organizations on AWS, Azure, or Google Cloud now run at least one managed serverless service in production.
Source: Grand View Research (historical data through 2025; current market projections: USD 28B in 2025, USD 92B by 2034 — Precedence Research)
More organizations are using this computing model to build and deploy their applications in the cloud. The drivers are well established: growing adoption of microservices and DevOps practices, the maturation of cloud-native development, and pressure to reduce infrastructure overhead while shipping faster. In 2026, AI and ML workloads have added another major push — serverless functions are increasingly the runtime of choice for lightweight inference, automated retraining triggers, and real-time data pipelines.
We build on Serverless (AWS Lambda) because we don’t think managing servers is a core part of our business. Instead, we focus on building business logic and data transformation. We start small, only pay for what we need, and the service automatically scales for us
Vadim Parizher
TL;DR
Serverless architecture lets you run backend code without managing servers — the cloud provider handles provisioning, scaling, and maintenance automatically. You pay only for execution time, not idle capacity. The main platforms are AWS Lambda, Google Cloud Functions, and Azure Functions. Serverless is best suited for event-driven workloads, APIs, mobile backends, and AI inference pipelines. The historical downsides — cold starts, limited observability — have been significantly addressed by 2026. It is not the right fit for latency-critical real-time systems or applications requiring fine-grained infrastructure control.
Understanding of Serverless Architecture: The Truth About Whether There is No Server in The Serverless Architecture
Serverless architecture is a cloud computing approach to building and running applications and services without the need for infrastructure management. The term "serverless" can be misleading, as it doesn't mean that no servers are involved but rather that the developer doesn't have to worry about managing them. The application is still running on the servers, but a third-party cloud service is solely responsible for those servers.
The origins of serverless architecture were the emergence of abstract serverless computing in the mid-2000s. Cloud computing has allowed companies to rent computing resources as needed instead of investing in their own hardware and infrastructure. In 2014, Amazon Web Services (AWS) released AWS Lambda, which is often considered the first mainstream serverless computing platform. Since then, serverless architecture has gained popularity and has been adopted by other cloud providers such as Microsoft Azure and Google Cloud Platform (GCP), which released their serverless offerings.
At Brocoders, we have over ten years of experience helping clients benefit from SaaS technology. Our developers and engineers specialize in developing and deploying custom SaaS solutions to suit their unique business needs. Our expertise includes helping companies migrate existing applications and data to the cloud, optimizing application infrastructure, and reducing costs through the development of serverless functions. We also help clients seamlessly integrate their SaaS solutions with other business systems, and we combine serverless architecture with solid DevOps practices to ensure deployments are automated, observable, and production-ready from day one.
In this article, we'll talk about what serverless architecture is, discuss its benefits and challenges, and provide some practical tools to help in your transition toward a serverless system. Serverless architecture might help to optimize infrastructure and create more efficient, scalable, and cost-effective applications. So, let's discover serverless architecture and how it can benefit your business!
What is Serverless Architecture?
In traditional server-based architecture, developers have to worry about managing servises, scaling, availability, and security. In contrast, serverless architecture abstracts away the infrastructure and lets developers focus on writing code.
According to martinFowler.com, the serverless architecture includes two concepts:
FaaS (Function as a Service) - a cloud computing model that allows developers to deploy code without having to manage server infrastructure. It enables developers to upload parts of the functionality to the cloud and allows them to run independently. The application developer is still responsible for writing the server-side logic. However, unlike traditional architectures, it is executed within stateless compute containers. And the cloud provider then runs the functions in response to specific events, such as an HTTP request, a message in a queue, or a change in a database.
Some popular FaaS platforms include AWS Lambda, Google Cloud Functions, and Microsoft Azure Functions.
BaaS (Backend as a Service) is a cloud computing model that allows developers to outsource aspects of the backend, such as user authentication, data storage, server-side logic etc. The cloud provider manages the backend infrastructure, while the developer focuses on the frontend user interface and business logic.
Some popular BaaS platforms include Firebase, AWS Amplify, and Parse.
How Serverless Architecture Works
Let’s see how a popular type of serverless architecture, FaaS, works.
- Developers write and deploy function code to a serverless platform.
- Function code is a small, self-contained unit of logic that can be executed in response to events.
- Functions are triggered by events (user requests or changes to data).
- When an event occurs, the cloud provider automatically provisions the necessary compute resources, creates a container, and loads the code.
- Compute resources are provisioned dynamically.
- The code runs and performs the necessary computations, processing data and interacting with other services as needed.
- The cloud provider takes care of server management and maintenance.
- Once the computation is complete, the serverless platform shuts down the container and releases the resources.
AWS Serverless Architecture Diagram
Source: AWS Lambda AWS Lambda
The diagram shows an example of AWS Lambda, Amazon S3, API Gateway, and DynamoDB working together to get weather data for a web or mobile app.
The API Gateway is used to receive HTTP requests from clients and route them to the appropriate Lambda function. The Lambda function then processes the request and returns a response. Generally, a Lambda function can be triggered by various event sources such as an API gateway, S3 bucket, or DynamoDB.
Key components of Serverless Architecture
Typically serverless architecture has a few key components that make it work.
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Function as a Service. In a serverless application, developers create functions that contain basic business logic and are written in a specific programming language, such as JavaScript or Python. These functions run on a FaaS platform, a computing service offered by a cloud provider. It is a core component of serverless architecture as it allows developers to deploy the units of code in the form of functions that are executed in response to events.
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Event triggers. That is what causes the function to execute, meaning that specific events or actions trigger functions. Event triggers can come from an HTTP request, a database update, a file upload or a scheduled task.
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API Gateway. This component is an interface that enables the communication between multiple serverless functions and serves as a connector that links backend services to serverless functions. It provides a way for clients to interact with serverless functions through a common API endpoint and can be used to trigger functions. API Gateway can handle authentication, rate limiting, caching tasks etc.
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Third-party services. These are cloud services that provide pre-built backend features such as authentication, storage, and databases. This allows developers to focus on building the frontend of their application and rely on the cloud provider to handle the backend services.
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Cloud Provider. A cloud provider, such as Amazon Web Services, Microsoft Azure, or Google Cloud Platform, provides the serverless infrastructure.
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Compute Resources. The cloud provider manages the compute resources required to execute the functions, including scaling, load balancing, and server maintenance.
These components work together to provide a scalable and cost-effective way to build modern cloud applications.
Benefits of Serverless Architecture
Serverless architecture offers several benefits for businesses, making it an attractive option for building modern cloud applications.
Cost-effectiveness
The serverless architecture eliminates the need for additional resources, application scaling, server maintenance, and storage and database systems. This allows businesses to reduce the initial cost of equipment, the need to replace obsolete equipment, and the need for personnel to maintain this equipment and data centers. All this lower investment in the IT budget.
The key point is that employing serverless architecture significantly reduces infrastructure costs since you pay only for the resources used and not for a fixed amount of server capacity. You are only billed for the execution time of your function, measured to the nearest 100 milliseconds, not for the time your process is idle.
Faster development
Additionally, the serverless architecture enables faster development. Developers can focus on writing code and building applications without worrying about managing servers or scaling infrastructure. Thus, running a minimum viable product requires fewer resources. In the case of app updates, developers can upload the changes and rely on the cloud to make the necessary adjustments.
Increased scalability
Serverless architecture also offers increased scalability. The cloud provider automatically provisions and scales resources from zero to peak demand as needed. This enables applications to handle spikes in traffic without manual intervention. The cloud provider manages the underlying infrastructure, so the business does not have to worry about scaling up or down based on traffic.
Reduced time-to-market
Serverless architecture frees developers from back-end issues. This, in turn, leads to faster development cycles, allowing companies to bring their products to market faster.
Improved security
Serverless architecture can provide improved security, as the cloud provider is responsible for securing the infrastructure and handling security updates.
Challenges of Serverless Architecture
While a serverless architecture offers many benefits, some issues must be considered.
Cold starts
In a serverless environment, applications are not running constantly. Instead, they are turned off between requests, and the provider activates the necessary resources only when a request is received to respond.
Cold start occurs when a function is executed for the first time or after a period of inactivity, and the cloud provider needs to provision a new container. This situation can cause a delay in response time, which was historically one of the main criticisms of serverless for latency-sensitive workloads.
By 2026, this problem is largely mitigated. Cloud providers now offer provisioned concurrency and always-warm execution pools, reducing cold start latency by 60–80% for production applications. WebAssembly runtimes such as Cloudflare Workers achieve sub-millisecond cold starts. Edge functions — deployed across 300+ global data centers — execute within milliseconds at the location closest to the user. These improvements mean cold starts are no longer a blocking concern for most SaaS use cases, though they still require planning for latency-critical, high-frequency workloads.
Debugging
Debugging serverless applications can be tricky because the code runs on a remote server instead of the local machine. Therefore, developers must rely on logs and other debugging tools to detect and resolve bugs. Thus, debugging serverless applications can be more complicated than debugging traditional applications due to the distributed nature of the architecture.
Vendor lock-in
Serverless architecture can lead to vendor lock-in, as each cloud provider has its own implementation of serverless architecture. This can make switching providers or using a hybrid cloud approach difficult.
However, this is solvable since the application's business logic lies in its functions, which can be easily transferred to another serverless provider. And to reduce the risk of vendor lock-in, you can choose generic components that use a common standard, such as a SQL database.
Limited control over infrastructure
It should be noted that a serverless architecture can lead to limited control over the infrastructure. The cloud service provider manages the infrastructure and provides a limited set of tools and services. This can be a problem for applications requiring fine-grained infrastructure control or specific performance or security requirements.
Therefore, in case of a hardware fault, data center outage, or other issue affecting one of your servers, you rely on your cloud provider to resolve it.
Serverless Architecture Use Cases
Event-driven applications
Serverless architecture is an excellent choice for building event-driven applications that respond to real-time events or notifications. These events could be triggered by a user action, such as clicking a button on a website, or by an external system, such as receiving a message from a sensor or another application.
Examples of event-driven applications include:
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Chat applications.
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Social media platforms.
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Real-time analytics systems.
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IoT (Internet of Things) applications.
Serverless architecture suits them, providing real-time processing, scalability, and high availability. It is a good solution for applications with unpredictable or variable workloads.
Serverless Architecture vs Microservices
Microservices and Serverless are not mutually exclusive. Microservices is a design pattern that breaks down an application into smaller, independent services that can be developed and deployed separately. On the other hand, serverless architecture is a way of running applications without traditional servers.
In fact, the serverless architecture allows developers to build applications with a microservices architecture, where each function can be developed, deployed, and scaled independently. By hosting microservices on a serverless platform, developers can take advantage of the scalability, and cost-effectiveness, improve application performance and reduce latency.
Serverless architecture gives microservices many benefits: real-time data processing and analysis, data transformation and integration, and API gateways that expose microservices to the outside world.
Mobile backends
By using serverless architecture, developers can quickly build mobile backends. Mobile applications with a serverless backend allow them to take advantage of the benefits of serverless computing, such as scalability, reliability, and cost-effectiveness.
The serverless backend can perform the work required for real-time communication, which is beneficial, for example, for messaging apps. It can also easily upgrade backend services without worrying about impacting the underlying infrastructure. This makes it easy to add or update new features without disrupting the user experience. Furthermore, the serverless backend can automatically scale to handle the increased traffic, ensuring the application remains available to end-users.
Processing file uploads
Downloading files can be resource-consuming and require a lot of processing power and storage. However, a serverless architecture can handle file uploads of any incoming files. Plus, the serverless architecture can migrate uploaded file storage to cloud storage services such as Amazon S3, reducing the need to manage file storage on servers.
The serverless architecture can be used to build applications that process various types of files, such as images, videos, and documents. This may include resizing photos, transcoding videos, or converting file formats.
Sending emails
The serverless architecture is suitable for building applications that send various emails, such as transactional, marketing, or notification emails. In addition, the serverless architecture can outsource email creation to cloud services specializing in email marketing or transactional emails.
Handling API requests
Serverless features can handle API requests and move the management of API gateways to cloud services such as AWS API Gateway or Azure API Management. These services provide automatic scaling and caching capabilities, as well as support for authentication, tracking, securing APIs and rate limiting.
Serverless Architecture Examples
Here are just a few examples of the many use cases for serverless architecture:
- Airbnb has implemented an event-driven architecture using AWS Lambda and Amazon Simple Notification Service (SNS) to send email notifications to their customers.
- Netflix uses serverless computing to manage and scale their video transcoding pipeline, which allows them to convert video content to different formats for playback on various devices.
- Coca-Cola uses serverless architecture to power their e-commerce platform. They have implemented a microservices architecture using AWS Lambda and Amazon API Gateway to provide a highly scalable and fault-tolerant e-commerce platform.
- Fintech startups. Acorns, a popular savings app, uses serverless architecture to handle their user authentication and account management functions.
- Media companies. The New York Times and the Guardian use serverless architecture to build and deploy their online content delivery systems. They use serverless computing to handle the large volume of traffic and user requests to their websites and applications.
At scale, the numbers are striking: AWS Lambda processes tens of trillions of function invocations monthly across more than 1.5 million customers, with usage growing over 100% year-over-year. That scale is only possible because the serverless model abstracts the infrastructure entirely — companies focus on business logic, and the platform handles everything else.
Serverless architecture in healthcare
Serverless architecture offers automation, flexibility, and personalization, most needed in the medical field. Managed by cloud vendors, serverless technology separates infrastructure provision and storage from internal processes. This allows companies to build and deploy applications without managing downtime or security issues. Serverless technology enables faster development, cost savings, and scalability. An example of its use is a patient portfolio application, where services are managed based on usage and demand, with managed authentication services like Cognito and AWS Aurora Serverless.
Serverless architecture for healthcare management system Source
Tools That Support Serverless Architecture
The market for serverless architecture is highly competitive. Big cloud providers and third-party vendors offer a variety of tools and services that make it easier and faster to create and launch serverless applications. Let’s see some major players in this market.
Nowadays, serverless computing platforms provide a fully managed, event-driven computing environment that scales automatically and runs code in response to triggers. So you only pay for the compute time used to run their code, not for a dedicated server or virtual machine. And they also provide tools for monitoring and logging, as well as for securing access to applications.
AWS Lambda: AWS Serverless Architecture
AWS Lambda is a serverless, event-driven computing service. It enables the execution of code for many applications and backend services without the need to provision or manage the server. And with over 200 AWS services and SaaS applications to trigger Lambda.
Some Features:
- Supports programming languages and technologies, including Python, Java, Go, PowerShell, Ruby, and C#, Node.js.
- Integrates with other AWS services, such as Amazon S3 for storage, Amazon DynamoDB for databases, and Amazon API Gateway for building and managing APIs.
- With AWS Lambda, you can create new on-demand application backend services using the Lambda Application Programming Interface (API) or custom API endpoints created using Amazon API Gateway.
- There is high scalability of your applications, as AWS Lambda can run codes in parallel and individually process each of them.
Google Cloud Functions
Google Cloud Functions is a serverless execution environment. It enables running event-driven code in a completely managed environment. Simplify the developer experience and speed up development.
Some Features:
- Supports programming languages and technologies, including Node.js, Python, and Go.
- Integrates with other Google Cloud Platform services, such as Google Cloud Storage for storage, Google Cloud Pub/Sub for messaging, and Google Cloud SQL for databases.
- Allows avoiding lock-in with open technology. Framework supports local development environment, on-premises, Cloud Run, and other Knative-based serverless environments.
- Allows to trigger code from Google Cloud, Google Assistant, Firebase, and even call it directly from a web, mobile or backend application.
Azure Functions
Azure Functions is a serverless computing platform offered by Microsoft. It allows developers to build event-driven applications and microservices in a serverless architecture.
Some Features:
- Supports programming languages and technologies, including C#, F#, Java, JavaScript, Python, Node.js, TypeScript, and PowerShell.
- Integrates with other Azure services, such as Azure Storage for data storage, Azure Event Hubs for messaging, Azure API Management for building and managing APIs, and SaaS offerings.
- Azure Functions provides a rich set of development tools, including Visual Studio, Visual Studio Code, and the Azure Functions Core Tools.
- It is open source.
OpenFaaS
OpenFaaS is an open-source serverless computing platform that allows developers to build and deploy serverless functions and microservices on any infrastructure.
Some Features:
- Supports programming languages and technologies, including Node.js, Python, Java, Go, Ruby, PHP, and C#.
- Allows you to bring along your existing microservices written with custom frameworks like Express.js, Vert.x, Flask, ASP.NET Core, FastAPI and Django.
- Integrates with other technologies and tools, such as Kubernetes for container orchestration, Prometheus for monitoring, and Grafana for visualization.
- Makes it easier to deploy functions and existing code to Kubernetes.
Knative
Knative is an open-source platform that enables serverless workloads to run on Kubernetes. It provides a set of building blocks for creating modern, container-based applications that can scale automatically and run on-demand without the need for managing servers or infrastructure.
Some Features:
- Supports programming languages and technologies, including Node.js, Python, Java, Ruby, .NET and Go.
- It can run on any cloud or on-premises infrastructure that supports Kubernetes.
- Integrates with other Kubernetes technologies, such as Istio for service mesh, Kubernetes API Server, Kubernetes Custom Resources and others.
- Open-source project.
Serverless Framework
Serverless Framework is an open-source framework that provides a platform-agnostic way to develop, deploy, and operate serverless applications. It supports multiple cloud providers, such as AWS Lambda, Azure, Google Cloud, and more, as well as on-premises environments.
Some Features:
- Supports programming languages and technologies, including Node.js, Typescript, Python, Java, and Go.
- It is a command-line tool that employs YAML syntax making it possible to deploy your code and cloud infrastructure for a wide range of serverless application scenarios.
- Provides a rich set of plugins and integrations with other tools, such as Terraform for infrastructure management and CI/CD pipelines.
Serverless Architecture Trends in 2026
The serverless landscape in 2026 looks different from even two years ago. Three shifts stand out.
AI and ML inference on serverless. Serverless functions have become a standard runtime for AI workloads: lightweight inference, automated retraining triggers, real-time ETL, and feature transformation pipelines. The event-driven model maps naturally onto AI-driven applications — a user action triggers a function, the function calls a model endpoint, the result is returned and stored. Teams building AI-powered SaaS on serverless report significantly faster iteration cycles compared to managing dedicated GPU or container infrastructure.
Edge computing as a deployment default. Edge functions have shifted from experimental to mainstream. Platforms like Cloudflare Workers, Vercel Edge Functions, and Deno Deploy now run production workloads across 300+ global data centers. The performance difference is significant: edge functions deliver response times measured in milliseconds rather than tens of milliseconds, because the function runs close to the user. For SaaS products with a global user base, edge deployment is increasingly the expected baseline, not an optimization.
Serverless and DevOps convergence. Serverless does not eliminate the need for DevOps practice — it changes it. Infrastructure-as-code tools (Terraform, Pulumi, SAM) and CI/CD pipelines are now first-class parts of any serverless deployment. Observability — distributed tracing, structured logging, and cost monitoring per function — has matured alongside the tooling. Teams that treat serverless as "someone else's ops problem" still run into the same issues: runaway invocation costs, silent failures, and untracked dependencies. The teams that succeed combine serverless architecture with proper DevOps practices from the start.
Thus, serverless architecture offers several advantages over traditional server-based architectures, including increased scalability, faster deployment times, and lower costs. It benefits your application development and deployment processes, allowing developers to focus on coding and delivering value to your customers.
Such a solution for building modern cloud applications is great for client-intensive applications and applications that grow quickly and need unlimited scale.
However, it may not be suitable for all types of applications. Developers must carefully consider factors such as performance, security, and vendor lock-in when deciding whether to adopt a serverless architecture for their projects. Note that migrating legacy applications to the cloud may be inefficient. For example, a monolithic architecture usually doesn't perform as well in the cloud as microservices. Therefore, it is important to carefully consider the trade-offs and limitations before adopting this architecture for a particular application or use case.
FAQ
Serverless architecture is a way of running backend code in the cloud without managing servers. You write functions that execute in response to events. The cloud provider starts them when needed, scales them automatically, and shuts them down when done. You pay only for the time your code actually runs.
No — servers are still involved. The term means you as a developer do not manage or provision them. A third-party cloud provider (AWS, Azure, GCP) owns and operates the infrastructure. You only write and deploy the code.
The key benefits are cost efficiency (pay-per-execution instead of reserved capacity), automatic scaling with no manual intervention, faster development cycles since teams focus on code rather than infrastructure, and reduced operational overhead. Companies implementing serverless consistently report infrastructure cost reductions of 60–70%.
The main challenges are cold starts (delays when a function is invoked after inactivity), more complex debugging due to the distributed nature of the architecture, potential vendor lock-in, and limited control over the underlying infrastructure. Cold starts have improved significantly in 2026 with provisioned concurrency and WebAssembly runtimes, but they still require planning for latency-sensitive applications.
Serverless is a poor fit for long-running processes (functions have execution time limits), applications requiring persistent in-memory state, workloads with consistently high and predictable traffic (where reserved capacity is cheaper), and systems needing fine-grained control over the runtime environment or hardware.
They are complementary, not competing. Microservices is an architectural pattern — breaking an application into small, independently deployable services. Serverless is a deployment and execution model. You can run microservices on serverless infrastructure, which adds automatic scaling and cost efficiency on top of the microservices design.
AWS Lambda is the most widely adopted, with the deepest ecosystem and over 200 native integrations. Google Cloud Functions and Azure Functions are strong choices if you are already invested in those cloud ecosystems. For edge use cases, Cloudflare Workers and Vercel Edge Functions offer sub-millisecond cold starts and global distribution across 300+ data centers.
Serverless shifts, rather than eliminates, DevOps work. Infrastructure-as-code (Terraform, SAM, Pulumi), CI/CD pipelines, distributed tracing, and per-function cost monitoring all become critical. Teams that treat serverless as "zero ops" typically run into runaway costs, silent failures, and untracked dependencies. Solid DevOps practices remain essential.