What is serverless computing?

When it comes to building applications, developers normally have a host of other server management tasks they need to carry out in order to deploy their code, such as defining resources for processing and storage, patching, load balancing, and more. All of these extra items lead to longer provisioning times and additional operational overhead that ultimately slows down development teams. 

Serverless computing attempts to provide an invisible “serverless” experience for developers, eliminating the need to think about servers or anything an application might need to run. Instead, the service provider does all the work behind the scenes to ensure you have the resources to execute your code and meet requirements without being charged for idle capacity. 

Think of serverless like getting water to your home. You could dig your own well, test the water quality, and install and maintain all the external plumbing needed to run it into the house. Or, you can connect to your city’s main water supply. You just turn the water tap and get as much water as you want exactly when you need it, and the city sends you a monthly bill for the exact amount of water you consume. 

Similarly, cloud providers automatically spin up the infrastructure resources and runtime environments needed to execute your serverless apps and automatically scale back down to zero when the execution is complete. Typically, you are charged based on the resources during the execution time. However, this can vary depending on the service and the vendor. 

But wait, don’t other types of cloud computing provide on-demand resources on a pay-as-you-go basis? It’s true that cloud service models like Infrastructure as a Service (IaaS) and Platform as a Service (PaaS) also provide on-demand access to computing resources. 

However, the cloud infrastructure allocated to you remains active even if you’re not using it. It’s also your responsibility to scale server capacity or configure your applications to scale up or down in response to user demand. 

Serverless architectures, on the other hand, are event-driven. Under this model, the provider only gives you resources when an event triggers your code to run and will scale instantly and automatically to requests.

Within serverless cloud computing, there are generally two types of services: Function as a Service (FaaS) and Backend as a Service (BaaS). 

FaaS provides the computing resources needed to execute application logic in response to requests. These pieces of logic (or functions) are run in containers that are fully managed by the cloud service provider. Serverless applications are typically broken into single functions that perform one action in response to an event. 

BaaS delivers the entire backend functionality of web or mobile applications as a service, such as authentication services, database management, cloud storage, push notifications, and hosting. BaaS also removes the need to manage servers, containers, or virtual machines. 

Within development, the term “serverless” is usually used to describe FaaS offerings. However, it’s important to note that FaaS is technically a subset of serverless technology. Serverless computing includes any type of service where the server management, configuration, scaling, and billing are abstracted from the end user. This can include databases, storage, event streaming, messaging, and API gateways. 

In general, serverless computing is still primarily used for simple, short-lived tasks. Some of the most common serverless computing examples include: 

• Integrating with third-party services and APIs
• Running scheduled tasks (for example, daily reports, backups, or business logic) 
• IT process automation like removing access automatically, initiating compliance security checks, or sending approvals
• Real-time data processing for structured and unstructured data 
• Automating continuous integration and continuous delivery (CI/CD) pipelines
• REST API backends
• Trigger-based actions or running scheduled tasks (for example, daily reports, backups, or business logic)
• Asynchronous processing
• Real-time or scheduled notifications

One of the biggest disadvantages of serverless computing is that it is still a relatively new technology. As a result, it is not yet suitable to meet all potential use cases. 

In addition, the intentionally ephemeral nature of serverless and its ability to scale down to zero make it unsuitable for certain types of applications. It’s not built to execute code for long periods and cannot always serve applications with strict low-latency requirements, such as financial services applications. 

Last but not least, the advantages of handing over the management of all computing resources to a third-party provider can also come with several downsides. While it frees up time to focus on code, it can also be tricky to migrate to a new cloud provider. You also have no visibility into where or how your service is run and have limited control over how you scale, what type of hardware code runs on, and disaster recovery situations. 

Still, there’s a lot to like when it comes to serverless computing, especially for organizations that are looking to help empower developers to move faster and looking for a simpler, more cost-effective way to build cloud-based applications. 

It’s also clear that some of the current weaknesses that exist will be solved over time as serverless computing continues to evolve. In particular, a lot of work is already being done on open source implementations of serverless and finding ways to make cloud services more open to make solutions portable across different platforms and environments.