Serverless Architecture: What It Is & How It Works

Serverless architecture is a method for designing software that allows a user to build a service without implementing an underlying infrastructure. Developers are capable of writing code and deploying it, while Cloud Provider provides a host for a wide variety of applications, databases and storage services. In this post we will talk about servers-free architectures'benefits and disadvantages, as well as some ways of going serverless.


The era of digital transformation has pushed the boundaries of technology far beyond traditional methods. Today, we stand at a juncture where serverless architecture is reshaping the way we approach software development. Here we delve into the intricacies of serverless computing and try to understand what it is and how it works.

How Serverless Architecture Works

Understanding serverless architecture requires us to first comprehend the traditional model of server-based applications. Traditional server applications allow users to interact with a system and employ its business logic, however, managing these servers demands considerable time and effort. Teams must maintain computer systems, administer software updates, fortify security, and make backup copies as necessary.

In contrast, when using serverless architecture, developers are emancipated from this responsibility. They can focus on writing application code instead of managing servers, thereby enhancing developer productivity. They can leverage third-party cloud providers, like AWS Lambda, Google Cloud Functions, or IBM Cloud Functions, to handle the routine infrastructure management.

Serverless architecture is primarily centered around Function as a Service (FaaS), operating system where developers write application code utilizing specific sets of separate functions. It enables developers to compose, deploy, and manage application code effectively, paving the way for an efficient and robust application development cycle.

How Serverless Computing Works

The crux of serverless computing is the elimination of the need to manage instances in the cloud. Developers can deploy code directly to the cloud without any configuration. Pricing for serverless environments is based on the resources consumed and not on pre-purchased capacity, which optimizes resource utilization.

Typically, developers host their applications on the cloud by installing and managing virtual machines, setting up operating systems, using server components, and continuously updating the software. With serverless computing, developers can write their own functions in any programmatic language and publish them on serverless platforms. This serverless approach promotes rapid provisioning, efficient system monitoring, and improved scalability.

Serverless Architecture vs. Container Architecture

Both the serverless platform and container architectures empower developers to deploy a project using abstractions. However, developers who deploy a container-based application must track all the configuration settings in their environment, system configurations, and dependencies. In comparison, server maintenance on serverless platforms is majorly managed by the underlying cloud provider.

Serverless apps run code and functions scale automatically, whereas containers need orchestration platforms like Kubernetes. By eliminating the need for dedicated server management, serverless computing enables developers to concentrate on crafting the application code, enhancing developer productivity, and accelerating the time-to-market for applications.

Cloud-native meets Hybrid Cloud

Serverless architecture can be implemented as a cloud-based model, offering significant performance gains. Incorporating a cloud-native strategy allows businesses to leverage the scalability and flexibility of public cloud environments like AWS, Google Cloud, and Azure.

In the upcoming part of the article, we will look into the different use-cases of serverless computing, the role of a cloud provider in this model, and how stream processing workloads can be efficiently managed in a serverless environment.

The Role of Cloud Providers in Serverless Computing and Its Use-Cases

Role of Cloud Providers in Serverless Architecture

As previously noted, serverless computing enables developers to focus on their application's core functionality rather than server management. To facilitate this, cloud service providers offer a serverless environment that executes, scales, and manages the application code. AWS Lambda, Google Cloud Functions, IBM Cloud Functions, and Azure Functions are among the top five serverless application platforms.

Each cloud vendor offers a unique set of features that allows developers to make code runs operate in a serverless environment. AWS Lambda, for example, is highly praised for its automatic scaling capabilities, ease of use, and robust support for a variety of programming languages. Google Cloud Functions, on the other hand, is highly integrated with Google services and allows developers to create functions that respond to events raised by Google Cloud Services.

Serverless platforms not only manage the routine infrastructure management tasks but also enable automatic scaling and resource provisioning. These services allow developers to deploy code directly to virtual machines, without worrying about the underlying infrastructure, thereby increasing developer productivity.

Use-cases for Serverless Computing

Serverless computing has various use-cases, owing to its flexibility and scalability. Here are a few popular examples: Web apps: Serverless architecture can be leveraged to build robust web applications, without worrying about the infrastructure. It allows developers to focus on the frontend while the various cloud platform providers handle the backend. Microservices architectures: Serverless computing is a perfect match for supporting microservices architectures. It allows developers to create, deploy, and scale individual services independently, offering increased agility and resilience. Real-time file processing: Serverless functions can be triggered in response to file uploads, enabling real-time data processing tasks such as video transcoding or image optimization. Analytics services: Real-time, analytics service is another compelling use case for serverless computing. It enables instant processing and analysis of large data volumes by automatically scaling resources as needed. Edge computing: With the growing prominence of edge computing, serverless functions can be utilized to process data at the edge of the network, improving performance and reducing latency.

Dealing with Vendor Lock-In

One potential challenge with serverless computing is the risk of vendor lock-in. Vendor lock-in happens when an organization becomes too dependent on a single, cloud computing provider's tools and services, making it difficult to switch to another vendor without significant cost and disruption.

However, the use of open-source serverless frameworks like the Open Source Fn Project can help mitigate vendor lock-in by providing a polyglot environment to run your code on any cloud provider. These frameworks enable the development of serverless applications that are not tied to a single vendor cloud service provider, offering more freedom and flexibility.

In the next section, we will delve deeper into serverless computing's benefits and drawbacks, with an emphasis on how it enhances developer productivity and enables businesses to focus on core competencies rather than routine infrastructure management.

Advantages and Disadvantages of Serverless Computing

How Serverless Computing Enhances Developer Productivity

The adoption of a serverless model of computing has been shown to significantly increase developer productivity. One of the reasons for this is the serverless model's nature, which removes the need for managing servers and allows developers to focus on writing and improving application code.

Serverless platforms are designed to simplify the deployment process, making it quicker and easier for development teams to push their changes and bug fixes. Automated tests, system monitoring, and rapid provisioning are all handled by the cloud provider, giving developers more time to work on the application's business logic and improve its overall quality.

In addition, the automatic scaling capability of serverless platforms eliminates the need for manual resource management. This means that applications can instantly and automatically scale in response to changes in traffic, reducing the time and effort required to manage scaling operations.

The Benefits of Serverless Computing

Serverless computing brings numerous benefits to the table:

Cost-efficiency: With serverless computing, you're only charged for the resources consumed by your functions, making it a cost-effective option, especially for applications with fluctuating or unpredictable workloads.

Scalability: Serverless architectures can automatically scale up and down to match the application's demand, without any manual intervention. This makes it ideal for handling peak traffic periods or sudden increases in workload.

Faster time to market: By eliminating the need for server management and infrastructure setup, serverless computing enables faster application development and deployment, reducing the time to market.

Challenges and Disadvantages of Serverless Computing

Despite its many benefits, serverless computing is not without its challenges:

Cold starts: When a serverless function is invoked after being idle, it may take some time to start, leading to increased latency. This phenomenon, known as a cold start, can affect application performance.

Monitoring and debugging: Traditional monitoring and debugging tools may not be fully compatible with serverless architectures, making it difficult to track and troubleshoot issues.

Resource limits: Serverless platforms impose certain limits on the resources that can be allocated to a function, which could impact the performance of resource-intensive applications.

In the final part of our article, we'll look into how companies are utilizing serverless computing for batch processing, what serverless workflows are, and explore some of the top serverless apps and services in the market today.

Serverless Computing in Action and The Future of Serverless

Use Cases of Serverless Computing

Serverless computing is versatile and caters to a broad spectrum of applications. Here are a few notable use cases of serverless framework:

Batch Processing: Serverless functions are perfect for batch processing tasks, such as data transformation and analytics services. The ability to scale automatically makes a serverless function an ideal environment for these tasks.

Video Transcoding: Companies dealing with multimedia content frequently use serverless computing. Services like AWS Lambda can quickly transcode videos uploaded by users, thereby reducing the need for dedicated server resources.

Microservices Architectures: Microservices can greatly benefit from serverless functions due to their event-driven nature. Individual microservices can be encapsulated within serverless functions, simplifying the architecture and improving resource utilization.

Popular Serverless Services

Many cloud service providers offer serverless platforms:

AWS Lambda: Amazon Web Services offers Lambda, one of the earliest and most popular Function as a Service (FaaS) platforms. AWS Lambda functions run your code in response to events such as changes to data in an Amazon S3 bucket or updates in a DynamoDB table.

Google Cloud Functions: Google's serverless platform allows developers to execute their code in response to HTTP requests or specific Google Cloud events, with automatic scaling to handle traffic.

Azure Functions: Microsoft's Azure platform provides serverless capabilities that support a range of programming languages and integrate seamlessly with other Azure services.

IBM Cloud Functions: Based on the open-source Apache OpenWhisk project, IBM Cloud Functions allows developers to execute code in response to a range of events, including HTTP requests, database changes, and message queue updates.

The Future of Serverless Computing

Serverless computing is no longer a buzzword; it has established its place in modern application development and deployment processes. The trend towards serverless is part of a larger movement towards abstraction, with the focus shifting from infrastructure management to the application's business logic.

Serverless workflows are becoming more complex and rich, supporting microservices architectures, integrating with serverless databases, and enabling developers to create robust, scalable applications. The emerging concept of edge computing, wherein computations are performed close to the data source, is also opening new possibilities for serverless computing.

Although challenges exist, such as vendor lock-in and cold start times, continuous advancements are being made to address these issues. As technology continues to evolve, serverless computing is poised to become an increasingly integral part of cloud computing, offering unparalleled benefits in terms of cost, scalability, and developer productivity.

In conclusion, serverless computing has revolutionized the way developers think about writing and deploying code. With its many benefits, it is clear that serverless is not just a trend, but a significant shift in how applications are built and managed in the cloud.