Serverless computing, also known as function as a service (FaaS), is the next evolutionary step of the cloud computing paradigm. It enables the invocation of scalable click and go functions running in event-driven systems (i.e., microservices) that are fully managed with high availability, security, scalability, and performance.
Serverless computing architectures have been available for nearly a decade. Nevertheless, over the years they have matured based on the evolution of cloud technologies like Platform as a Service (PaaS) and API Management (APIM). Furthermore, we have seen the combination of these technologies with others like event streaming, real-time data processing, data analytics and machine learning. These combinations have given rise to the development of integrated and optimized serverless data architectures.
Today, companies are using serverless architecture to reduce costs and improve agility by leveraging cloud infrastructures. Moreover, serverless architectures are gaining popularity because they enable developers to focus on their code instead of managing servers or containers. From a programming perspective, serverless architectures rely on event-driven programming paradigms, where developers write small pieces of code that respond to events, typically HTTP requests. In the scope of the serverless computing paradigm, developers need not worry about provisioning or scaling servers, given that this is taken care by cloud platforms. Likewise, there’s no need to manage the underlying operating system because most serverless platforms run on containers that are executed directly atop an operating system kernel. Hence, serverless architectures provide flexibility and agility by getting rid of infrastructure performance bottlenecks, forking huge monolithic problems, and tackling key development-time challenges.
Serverless data architectures are applicable to any domain – from websites and online services, social media platforms and IoT solutions, to telecom systems. Also, serverless platforms makes software architectures fit for an increasingly complex world where growth is inextricably coupled with increased stress on existing infrastructures. This is the reason why serverless architectures are adopted by many organizations as core elements of their digital transformation. It is also no accident that serverless functions are currently deployed and used in a variety of data driven applications, including Internet of things (IoT), Big Data and social media applications.
Serverless Systems: The Underlying Technical Concepts
Serverless architectures are quickly becoming the preferred method for building modern applications. Most of these architectures are based on two key technical concepts:
- Function-as-a-Service (FaaS), which provides developers with the ability to execute code in response to events or HTTP requests by orchestrating functions.
- Event-Driven Architecture (EDA), which is a software architecture style that can be used to build highly scalable and reliable applications.
The above two concepts can be implemented based on open-source tools and frameworks like OpenFaaS and OpenWhisk. These tools are used to create event-driven serverless functions that process data as it’s being generated, providing real-time insights into business processes and other areas of interest.
The combination of FaaS and EDA in a single data architecture is a key to delivering the benefits of serverless computing in terms of breaking application silos, reducing latency and scaling performance. In this direction, developers and deployers of serverless systems must leverage the technological advantages of serverless architectures to deliver tangible business benefits.
Serverless Architectures: The Technological and Business Benefits
In more detail, the technological advantages and business benefits of serverless computing are as follows:
- Flexibility: Serverless architectures allow companies to deliver business value fast by enabling them to focus on their core competencies. Specifically, serverless architectures enable modern enterprises to scale resources up and down based on the needs of their applications, rather than investing in infrastructure that sits around unused most of the time. This makes it easier for companies to accommodate spikes in traffic or unexpected requirements for new features.
- Real-Time Performance: Serverless data architectures benefit from computing functions that are executed in response to events and can respond in milliseconds. Furthermore, serverless code runs closer to the field (e.g., the end-users), which results in decreased latency when compared to other cloud models. Therefore, serverless functions are a very good choice when it comes to supporting applications that require real-time performance such as real-time control applications in industrial settings. Moreover, serverless architectures support real-time processing because they don’t have to worry about scaling up capacity or down when demand changes. This means that enterprises can process information quickly and efficiently without having to worry about paying for idle resources or waiting for new servers to be provisioned when demand increases. At the same time, most serverless databases offer real-time performance because there’s no latency between requests and responses as they are fully managed by the cloud provider itself. This means that if you have multiple users making requests at once (e.g., during peak times), the system will automatically scale up resources so that each user receives their response as soon as possible.
- Scalability: Since the serverless architecture scales automatically, it’s possible to use it for high-traffic websites or applications without having to worry about scaling issues. Specifically, serverless architectures are designed to scale automatically as demand increases or decreases i.e., they are elastic by nature like most cloud services. As such they automatically adjust to accommodate changes in usage patterns without requiring additional work from developers or operations teams.
- Costs savings and pay-per-use model: Like other cloud paradigms, serverless models are based on a pay-per-use cost model that provides flexibility and potential cost savings. In the case of serverless computing, end-users can pay for the functions they use, which provides greater potential for cost-savings when compared to other cloud models that charge for data transfers and I/O (Input-Output) operations.
Overall, the benefits of serverless architectures are increasingly becoming well-known: You can build and scale applications faster, with more agility and reduced operational overhead, and at a lower cost than traditional infrastructure. Furthermore, with serverless data architectures, you can bring together your data from a variety of sources (e.g., databases, NoSQL stores, cloud storage services and more) into a single place without having to worry about provisioning servers or setting up a complex pipeline. This approach gives you the freedom to focus on building the best possible application rather than worrying about infrastructure or managing cloud providers.
Many application architects believe that data architectures based on serverless functions are the future of cloud computing. This is because they offer a powerful new way to build applications, and they’re already proving their worth in a range of use cases. This is the main reason why modern enterprises must understand serverless architectures and their business benefits.
