What is Serverless Computing? Definition, Benefit, and Use Case

Axle Networks Blog – Serverless computing is a method of developing and deploying applications that has the potential to fundamentally alter the way we think about infrastructure, resource allocation, and the overall development lifecycle. This approach removes the need for managing servers and infrastructure, so developers can focus on writing code and delivering value to users faster.

However, the term “serverless” can be misleading because it does not imply a complete absence of servers. Rather, it represents a change in the way developers interact with and manage the infrastructure. Serverless computing allows developers to focus solely on application logic by abstracting away the complexities of server management, while the cloud provider handles resource provisioning, scaling, and maintenance.

Today, we’ll look at serverless computing, including its definition, benefits, and use cases.

Let’s get right to it.

Serverless Computing: Definitions

Serverless computing is a cloud-based execution model where the cloud provider is responsible for dynamically allocating and managing the necessary computing resources to run your application.

In a serverless environment, developers simply upload their code, and the cloud provider takes care of provisioning, scaling, and maintaining the underlying infrastructure.

The key distinction of serverless computing is that developers no longer need to worry about provisioning, configuring, or managing servers. Instead, they can focus solely on writing and deploying their application code, while the cloud provider handles the scaling, high availability, and fault tolerance of the infrastructure.

This shift in responsibility allows developers to be more productive, as they can spend less time on infrastructure management and more time on building features that directly benefit their users. Additionally, serverless computing often results in cost savings, as users only pay for the resources they actually consume rather than maintaining a fixed infrastructure.

Serverless computing has emerged as a powerful approach to application development, enabling organisations to focus on their core business logic while the cloud provider handles the underlying infrastructure. As serverless computing continues to gain traction, it has also paved the way for the adoption of other architectural patterns, such as microservices.

If you’re interested in exploring the intersection of serverless computing and microservices architecture, I’d encourage you to check out the following article:

Learn More: What Is Microservices Architecture? Key Characteristics, Technology Used, and Example

How does Serverless Computing Work?

Serverless computing is built on the concept of Functions as a Service (FaaS), where developers upload their application logic in the form of individual functions, or “serverless functions.” It operates on an event-driven basis.

When an event occurs, a function is executed. This is different from traditional Virtual Machines (VMs) or Platform as a Service (PaaS) where the user needs to specify the infrastructure requirements.

Using this approach, developers focus on writing their application code and business logic without worrying about cloud management. Developers can just write the code, and then it is deployed to containers managed by a cloud service provider.

The cloud provider handles provisioning the cloud infrastructure required to run the code and scales the infrastructure up and down on demand as needed.

They are also responsible for routine infrastructure management and maintenance tasks such as operating system updates and patches, security management, capacity planning, and system monitoring.

The cloud provider spins up and provides the required computing resources on demand when the code executes and spins them back down again—called ‘scaling to zero’—when execution stops. The billing starts when execution starts and ends when execution stops; typically, pricing is based on execution time and resources required.

Despite the name, there are servers in serverless computing.

‘Serverless’ describes the developer’s experience with those servers—they are invisible to the developer, who doesn’t see them, manage them, or interact with them in any way.

Today, every leading cloud service provider offers a serverless platform, including Amazon Web Services (AWS Lambda), Microsoft Azure (Azure Functions), Google Cloud (Google Cloud Functions), and IBM Cloud (IBM Cloud Code Engine).

Advantages of Serverless Computing

Serverless computing offers a range of compelling advantages that have made it a popular choice for modern software development teams:

1. Reduced Infrastructure Management: With serverless computing, developers no longer need to provision, configure, or manage servers. The cloud provider handles all the underlying infrastructure, freeing up time and resources for the development team.
2. Scalability and High Availability: Serverless platforms automatically scale computing resources up and down based on demand, ensuring that your application can handle sudden spikes in traffic without any manual intervention.
3. Cost Optimisation: Serverless computing follows a pay-per-use model, where you only pay for the resources you actually consume. This can lead to significant cost savings, as you don’t have to maintain a fixed infrastructure that may be underutilised.
4. Faster Time-to-Market: By abstracting away the infrastructure concerns, serverless computing allows developers to focus solely on writing and deploying their application code, leading to faster development cycles and quicker time-to-market.
5. Improved Developer Productivity: With the reduced burden of infrastructure management, developers can dedicate more time to building features that directly benefit their user, rather than spending time on operational tasks.
6. Simplified Deployment and Monitoring: Serverless platforms often provide built-in tools and services for deployment, monitoring, and logging, making it easier to manage the entire application lifecycle.
7. Increased Reliability: Serverless platforms handle tasks like load balancing, fault tolerance, and high availability, ensuring that your application remains resilient and responsive, even in the face of unexpected spikes in traffic or infrastructure failures.

Serverless Computing Examples

Serverless computing has found widespread adoption across various industries and use cases.

Web and mobile applications are some examples of the utilisation of serverless functions. With serverless computing, web and mobile applications can power their backends, handling tasks like API endpoints, data processing, and real-time updates.

Organisations can utilise serverless functions for data processing and analytics, allowing them to process and analyse large datasets, perform ETL operations, and generate real-time insights. This leverages the scalability and cost-effectiveness of serverless computing for data-intensive workloads.

Serverless functions can also power chatbots and conversational interfaces by processing natural language, recognising intent, and generating responses. This allows for the rapid development and deployment of intelligent conversational experiences.

Finally, serverless functions can be used in the context of the Internet of Things (IoT), processing and responding to data from IoT devices while allowing for real-time monitoring, control, and data analysis. This enables businesses to develop IoT solutions without the burden of managing the underlying infrastructure.

This approach is also used by some of the world’s largest companies. According to AntStack, Coca Cola, Major League Baseball, and iRobot are some of the great examples of serverless computing usage. Here’s how they use it:

1. Coca-Cola’s Serverless Vending Machines: Coca-Cola transformed its vending machines into cloud-based and serverless systems, reducing costs by 66% from $13,000 to $4,500 per machine annually. This change allowed for more efficient inventory management and marketing purposes.
2. Major League Baseball’s Statcast: MLB uses serverless computing to provide real-time and accurate sports statistics to fans. This technology enables complex searches based on variables like player names, season types, and pitch velocity, enhancing the overall fan experience.
3. iRobot’s Roomba Sales: iRobot, a company known for its robotic vacuum cleaners, leveraged serverless computing to handle the sudden surge in sales during Amazon Prime Day. This scalability allowed them to efficiently manage the increased demand without worrying about server management.

Serverless Computing vs Cloud Computing

Serverless computing and cloud computing are two distinct models of computing that differ in how they manage and allocate computing resources. Here’s a summary of the key differences:

Serverless Computing

• Managed Infrastructure: In serverless computing, the cloud provider manages the infrastructure, including servers, storage, and networking. This means that developers do not need to worry about provisioning or managing servers.
• Event-Driven: Serverless computing is event-driven, meaning that applications are triggered by specific events or requests, and the cloud provider dynamically allocates resources to handle these events.
• Scalability: Serverless computing offers automatic scaling, which means that resources are scaled up or down based on demand, eliminating the need for manual scaling and reducing costs.
• Cost Savings: Serverless computing is often more cost-effective because users only pay for the resources used, eliminating the need to pay for idle capacity.
• Focus on Code: Serverless computing allows developers to focus on writing code without worrying about the underlying infrastructure, making it a more efficient and productive way to develop applications.

Cloud Computing

• Managed Infrastructure: In cloud computing, the user or client manages the infrastructure, including servers, storage, and networking. This means that developers need to provision and manage servers, which can be time-consuming and costly.
• On-Demand Access: Cloud computing provides on-demand access to computing resources, allowing users to scale up or down as needed.
• Cost-Effective: Cloud computing can be cost-effective for businesses that need to scale up or down frequently, as they only pay for the resources used.
• Flexibility: Cloud computing offers flexibility in terms of the type of resources and services that can be used, including Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS).

While both serverless computing and traditional cloud computing have their own advantages, the serverless approach has gained significant traction due to its ability to simplify infrastructure management, optimize costs, and improve developer productivity.

Serverless computing simplifies infrastructure management, allowing developers to focus on code rather than hardware. As applications grow, integrating serverless with a microservices architecture can enhance scalability and efficiency. To understand how microservices can transform cloud computing, explore our detailed guide.

Learn More: Microservices in Cloud Computing: Definitions, Advantages, and Challenges

Conclusion

Serverless computing represents a significant shift in our approach to software development and deployment. Serverless platforms free developers from the complexities of infrastructure management, allowing them to focus on writing and deploying application code while the cloud provider handles the underlying scaling, provisioning, and maintenance tasks.

Managing cloud infrastructure efficiently requires expert handling beyond just understanding serverless computing.

Axle Networks IT Managed Services offers reliable cloud management solutions tailored to your specific needs. With our team of experienced professionals, you can rest assured that your cloud-based resources and data will be protected from unauthorised access and potential security threats.