Serverless computing frees developers from the time-consuming task of managing infrastructure, making it possible for them to produce apps more quickly. When you use serverless apps, the cloud service provider automatically sets up, scales, and manages the infrastructure that the code needs to run.

What is Serverless Computing?

Serverless computing is a type of computing in which back-end functions are made available only when they are required. Users can create and release software with no consideration for the underlying server infrastructure when using a serverless provider. Because the service is self-scaling, a business that uses a serverless provider for its back-end needs only pay for the resources it actually uses. It's important to remember that despite the "serverless" moniker, developers still work with real servers.

Serverless and other cloud backend models

Backend-as-a-Service and Platform-as-a-Service are two technologies that are frequently confused with serverless computing. Despite their similarities, these models are not guaranteed to work with a serverless setup.

Backend-as-a-service (BaaS)

It is a type of service model in which a cloud provider gives backend services to developers, such as data storage, so that the developers may concentrate on building code for the front end of the application. But while serverless apps are event-driven and run on the edge, BaaS applications might not fit either of these requirements.

Platform-as-a-service (PaaS)

It is a concept in which developers essentially rent from a cloud provider all of the required tools to develop and deploy programs, such as operating systems and middleware. PaaS apps, on the other hand, are more difficult to readily scale than serverless applications. In addition, PaaS do not necessarily run on the edge and frequently have a visible starting delay, whereas serverless applications do not have either of these issues.

Infrastructure-as-a-service (IaaS)

It is an umbrella phrase that refers to cloud vendors who host clients' infrastructure on behalf of those customers. Even though IaaS providers might offer serverless features, this doesn't mean that the two ideas are the same. 

Serverless technology goes beyond FaaS

Using a cloud computing service known as "function-as-a-service," or FaaS, programmers can trigger the execution of containers containing code in response to events or requests without having to worry about or manage the underlying infrastructure.

Serverless is generally defined as a computing model in which FaaS plays a central role. However, serverless computing is much more than just functions as a service. Rather than worrying about the infrastructure behind their applications, serverless architectures allow the cloud provider to take care of everything behind the scenes, making provisioning, maintenance, and invoicing completely transparent to developers. Also included are the following services:

  • Storage (especially object storage) and database management systems (both SQL and NoSQL) that don't require a server are the backbone of the data layer. Taking a serverless approach to these technologies entails making the switch from supplying "instances" with fixed limits on capacity, connections, and queries to models that scale infrastructure and price linearly with demand.
  • Examples of serverless architecture include the open-source Apache Kafka event streaming platform, which is used for both event streaming and messaging. This architecture is particularly well-suited to event-driven and stream-processing workloads.
  • API gateways are proxies for web operations. As such, they handle the routing of HTTP methods, client ID and secret management, rate limiting, cross-origin resource sharing (CORS), monitoring API activity, reviewing response logs, and setting API distribution policies. 

Evolution of Serverless Computing

Alongside the rise in popularity of containers and on-demand cloud services, the serverless architecture and "functions as a service" (FaaS) concepts have also gained traction. The development of serverless computing was broken down into three stages in a report that was produced by 451 Research in collaboration with Red Hat.

The serverless model was in its "1.0" phase when it initially debuted, and it had some constraints that made it less than ideal for general computing. The following are some characteristics of Serverless 1.0:

  • HTTP and few other sources
  • Functions only
  • Limited execution time
  • No orchestration
  • Limited local development experience

When Kubernetes came out, it started a time called "Serverless 1.5." During this time, many serverless frameworks started to add auto-scaling for containers.

The term "Serverless 2.0" describes the current state of the industry, which is characterized by the addition of integration and state. In order to make serverless computing appropriate for general-purpose commercial operations, providers have begun integrating the components that were previously absent. The following are characteristics of Serverless 2.0:

  • Basic state handling
  • Use of enterprise integration patterns
  • Advanced messaging capabilities
  • Blended with enterprise PaaS
  • Enterprise-ready event sources
  • State and integration

What are Knative and serverless Kubernetes?

It's no surprise that Kubernetes, a container orchestration platform, is widely used to power serverless infrastructure by facilitating the deployment and management of containerized applications. However, Kubernetes does not come pre-configured to execute serverless apps natively.

When it comes to installing, running, and managing serverless apps on Kubernetes, the open source community project Knative is invaluable. The project is managed by the Knative team. You are able to deploy code to a Kubernetes infrastructure, such as Red Hat OpenShift, by utilizing the serverless environment provided by Knative. When using Knative, the process of developing a service entails first packaging your code into a container image and then delivering that image to the system. Because Knative handles starting and ending instances on its own, your code is only executed when it is absolutely necessary.

Knative consists of three primary components:

  • Build: A versatile method for constructing source code into containers
  • Serving: A request-driven model for delivering workloads on demand lets containers be set up quickly and scaled automatically.
  • Eventing: An architecture for consuming and creating events to drive app development Events from your own apps, cloud services from different providers, SaaS platforms, and Red Hat AMQ streams can all trigger apps.

In contrast to earlier serverless frameworks, Knative was built for the deployment of every type of contemporary software workload, from monolithic programs to microservices and even tiny functions. This is because Knative was built with a modular architecture.

Pros and cons of serverless



Computing without servers has the potential to increase developer productivity while also reducing running costs. The regular processes of provisioning and administering servers can be offloaded, which frees up more time for developers to concentrate on their applications.

Serverless computing makes it easier for companies to embrace DevOps by eliminating the necessity for software developers to provide detailed descriptions of the infrastructure that they want operations to set up for them.

It is possible to further simplify the process of developing mobile applications by combining full components derived from the offerings of third-party BaaS providers.

Instead of always running and administering your own servers, which incurs ongoing costs, a serverless architecture allows you to pay just for the amount of cloud-based compute time that you actually utilize. This results in lower operational costs overall.


There may be problems if you don't have complete control over the server and its logic.

Cloud providers may have strong limits on how their components may be interacted with, in turn influencing how flexible and personalized your own systems can be. When working in a BaaS environment, developers may find themselves dependent on services over which they do not have control of the underlying code.

If you let go of certain parts of your IT infrastructure, you leave yourself vulnerable to vendor lock-in. If you choose to switch providers, you also need to be prepared to pay the expense of modifying your systems so that they are compliant with the standards of the new vendor.

Serverless use cases

Consider a task such as the bulk processing of incoming picture files. This kind of job might only run once in a while, but it must always be prepared in case a huge number of image files arrive all at once. Or it might be a task such as monitoring a database for incoming changes and then applying a sequence of functions to those changes, such as comparing them to quality standards or automatically translating them.

The adaptability of serverless apps makes them a good fit for use cases including inbound data streams, chatbots, scheduled tasks, and business logic. Serverless computing is also often used for back-end APIs and web applications, business process automation, serverless websites, and integration across many platforms. 

Final thoughts

An approach known as serverless computing provides software developers, teams, and organizations with a level of abstraction that makes it possible for them to reduce the amount of time and resources spent on infrastructure maintenance. This strategy is beneficial to each and every component of an application, including but not limited to computation, the database engine, messaging, analytics, and artificial intelligence.