Serverless: An Emerging Software Architecture

Backend infrastructure management and maintenance are significant responsibilities and cost-incurring factors in application development. Traditionally, organizations depended on dedicated servers, virtual machines, or containers to host their applications, which required significant time and effort. The rise of cloud computing has provided a solution to streamline this process. It has transformed application hosting by offering on-demand access to the required computing resources without investing in expensive physical infrastructure. As a result,  software development companies can grow rapidly by leveraging cloud services.

However, cloud computing often results in inefficient resource utilization, leading to both overuse and underuse of resources. Serverless architecture has surfaced as a groundbreaking paradigm that overcomes the limitations of traditional cloud computing service models. It lets developers write code without the operational overhead of managing backend services. This approach speeds up the application development process, enabling businesses to quickly adapt to changing demands.

In this blog, we’ll explore serverless architecture, how it works, the role of FaaS, its benefits and drawbacks, real-world use cases, and a comparison with other cloud models.

What is Serverless Architecture?

Serverless architecture is a modern approach to building applications where you do not have to manage the servers that run your code. There are cloud providers responsible for tasks such as maintaining infrastructure, handling updates, adjusting resources, and keeping applications available. You can thus spend more time working on the actual features and logic of your applications. Serverless computing mainly includes two models, i.e., Backend as a Service (BaaS) and Function as a Service (FaaS). 

BaaS provides ready-to-use backend services, such as databases, storage, and authentication, so you can avoid building and maintaining these systems yourself. FaaS works differently by running small pieces of code when a particular event occurs, such as a user request or a data update. Popular examples include AWS Lambda, Azure Functions, and Google Cloud Functions. Serverless should not be confused with Platform as a Service (PaaS). PaaS still requires you to manage parts of the application environment, while FaaS automatically responds to individual events and adjusts resources as needed.

Components of Serverless Architecture

The following are the four primary components of serverless architecture:

1. Function-as-a-Service (FaaS)

Function as a Service (FaaS) is a cloud computing model that allows you to run specific pieces of code whenever a particular event occurs. The cloud provider manages the servers, resources, and scaling, so you can concentrate on writing and improving your functions. Each function is usually designed to perform one focused task and does not depend on previous executions. This makes FaaS useful for building microservices, processing data quickly, and handling applications that respond to user or system events 

2. Backend as a Service (BaaS)

Backend as a Service (BaaS) is a cloud-based approach that gives you ready-made tools for handling the backend of an application. Instead of building and maintaining servers, databases, authentication systems, storage, and APIs from scratch, you can use services provided by the BaaS platform. Therefore, you can spend more time designing the user interface and improving the main features of your application. BaaS can make development faster, simpler, and more affordable, especially for small teams and new projects.

3. API Gateways

An API gateway acts as a communication point between external applications and serverless functions. It receives incoming requests, checks whether they are allowed, and then sends them to the appropriate function or service. This helps protect backend resources while also making it easier to control how applications communicate with each other. API gateways can handle tasks such as authentication, authorization, request routing, and modifying requests when needed. Major cloud providers offer their own solutions, including Amazon API Gateway, Azure API Management, and Google Cloud Endpoints.

4. Event-Driven Architecture

Event-driven architecture allows serverless applications to respond automatically when something happens. Instead of running continuously, functions start when they receive a specific trigger. For example, a function may run after a user sends an HTTP request, a file is uploaded, a database record changes, or a scheduled task occurs. This approach helps applications react quickly while using resources only when needed.

How Does Serverless Architecture Work?

We’ve now understood FaaS (Function as a Service), the basic concept of serverless computing. However, to understand the dynamics and functioning of serverless applications, you also need to be familiar with the following fundamental terms associated with serverless architecture:

Below is the step-by-step process of how serverless architecture operates, as depicted in the figure above.

1. Writing function code: Programmers first write the app code as a set of independent functions packaged in a container. A function’s underlying code determines how the app responds to specific user actions. 
2. Uploading to FaaS: Once developed, functions are uploaded to a reliable FaaS platform such as AWS Lambda. They are your typical cloud providers responsible for managing your application in the cloud and ensuring efficient code execution. 
3. Managed infrastructure: The cloud provider handles all aspects of the underlying infrastructure, including server provisioning, scaling, availability, patching, and operating system maintenance. The developer has no role in this. 
4. Event-driven execution: The cloud provider executes the function triggered by an event in ephemeral containers. It decides whether the function must run on an active server or requires a new server.
5. Task performance: The functions perform their respective roles, such as integrating with third-party services.
6. Ephemeral containers: A temporary container that gets triggered during invocation and destroyed after the execution completes. The cloud provider handles its creation and destruction automatically.
7. Compute time billing: Companies using serverless services pay according to the time consumed while executing the serverless functions.

Benefits and Drawbacks of Serverless Architecture

Let’s take a look at the pros and cons of the serverless architecture:

Advantages of Serverless Architecture

The following are the reasons that are driving the software industry toward serverless computing:

• Cost-efficient: You pay only for the resources you require at the time of need. This saves licensing fees, hardware expenses, and maintenance costs associated with the cloud architecture.
• Increased scalability: Resources can be easily scaled up or down according to varying requirements. Serverless platforms automatically create or delete function instances in response to varying traffic without any manual configuration.
• Faster time-to-market: Serverless environments increase the deployment speed because developers are freed from managing traditional server intricacies and can focus on building and testing the business logic. Therefore, serverless apps reach the production stage by following fewer steps.
• Flexibility: Applications built using managed services are easy to adapt to emerging needs, thus increasing agility in development.
• Speedy code execution: The vendor can run the code on servers near the end user; hence, users receive fast responses to their requests. No origin server is involved here for hosting the application; this reduces delays.

Limitations of Serverless Architecture

• Vendor lock-in: You may be unable to switch between multiple cloud providers when necessary, as you rely on a particular provider for all the managed services.
• Not suitable for long-running processes: Since you are charged based on computation time, long-running workloads can become costly in serverless computing.
• Cold start latency: Functions invoked after a period of inactivity take longer to execute because initializing a serverless environment requires time.
• Limited control: The use of a serverless platform is subject to the provider’s terms and conditions; thus, very little or no control over the server hardware infrastructure.

Serverless Architecture vs. Container Architecture

Both Serverless and Container architectures hide the complexities of the physical infrastructure and let you focus only on writing code. However, they exhibit certain major differences that you must know.

• Serverless architecture: With this architecture, you can run code without managing servers or operating systems. The cloud provider takes care of infrastructure, maintenance, and automatic scaling. Applications are usually divided into small functions that perform specific tasks when an event occurs. This is best suited for applications where you cannot predict the traffic, such as payment processing, notifications, and event-driven workflows. However, it may create stronger dependence on a cloud provider and offer less control over the underlying environment.
• Container architecture: Here, the application is packaged in a container with all its required libraries, dependencies, and configurations for operation. Therefore, you can exercise greater control over the application environment and can use containers for long-running services, complex applications, and workloads that require consistent performance. Containers are highly portable as they can run across multiple cloud platforms, but your team has to manage the container images, updates, dependencies, and scaling.

Serverless Architecture vs. Microservices — What’s the Difference?

Serverless architecture and microservices architecture seem to be closely related due to multiple similarities. However, they differ in some aspects that you must know before planning to implement either of them or taking a hybrid approach:

• Serverless architecture: It lets you develop applications without worrying about the underlying servers. There’s a dedicated cloud provider responsible for managing the underlying infrastructure, including provisioning, scaling, maintenance, and security. You mainly need to write small functions that perform specific tasks when an event or request occurs. This approach is an effective way to reduce operational work and costs because the resources are used only when needed. This architecture is best suited for event-based applications that need to adapt to changing needs. However, functions usually have limits on execution time and resources. It can also create extra delay for some requests and may increase dependence on the chosen cloud provider. 
• Microservices architecture: Microservices architecture divides a large application into smaller, independent services. Each service handles a particular business function and can be developed, deployed, monitored, and scaled separately. This structure gives you greater control over your applications and works well for complex systems that need continuous operation or long-running processes. However, building and managing multiple services requires great development effort and technical expertise. Therefore, it may cost more and require stronger DevOps practices. When compared to serverless, you have greater control over resources and less dependence on a single cloud provider.

Comparison of Serverless with other Cloud Backend Models: BaaS vs PaaS vs IaaS

Let us now compare FaaS with similar cloud computing service models: BaaS, PaaS, and IaaS. Though these cloud backend models share similarities with the serverless or FaaS model, they do not qualify as serverless architecture.

1. Backend-as-a-Service (BaaS): The BaaS model is for mobile and web app development. The development team writes and maintains the front-end code, whereas the third-party cloud provider handles storage systems, hosting, APIs, databases, security updates, etc., backend services. Firebase (by Google), AWS Amplify, Parse (by Facebook), etc., are some of the major BaaS providers.
2. Platform as a Service (PaaS): PaaS providers give their cloud platform on rent to organizations to develop, deploy, and manage applications, thus freeing them from infrastructure setup and management. However, scaling requires manual intervention. It even follows a pay-as-you-go or fixed pricing model, unlike FaaS, which follows a pay-per-use pricing structure. Heroku, Google App Engine, Microsoft Azure App Service, and AWS Elastic Beanstalk are major PaaS providers.
3. Infrastructure-as-a-service (IaaS): The IaaS model delivers on-demand cloud infrastructure resources to developers such as virtual machines, servers, hard drives, middleware, etc, via the Internet. Here, buyers have higher control over the underlying infrastructure, like the traditional on-premises infrastructure. Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform (GCP), IBM Cloud, etc., are major IaaS providers.

Comparing the Top Supporting Tools for Implementing Serverless Architecture

You’ll get a complete understanding of serverless architecture only when you apply the theoretical understanding properly during implementation. The implementation depends on the serverless platforms you’re opting for. 

The following is a list of some of the best serverless platforms you can consider:

AWS Lambda

AWS Lambda is a serverless computing service from Amazon Web Services that allows you to run code without dealing with setting up and managing the server infrastructure. You just write and upload functions and connect them to events or requests. AWS automatically provides the required resources, runs the code, and adjusts capacity according to demand. Lambda supports several programming languages and works closely with services such as Amazon S3, DynamoDB, API Gateway, and CloudWatch. 

Azure Functions

Azure Functions is a serverless platform from Microsoft Azure that lets you run code without managing servers. A function starts when a particular event occurs, such as a file upload, database change, or incoming request. You can develop applications in several programming languages, including Python, C#, Java, JavaScript, and TypeScript, as it supports all of them. You don’t even need to bother about planning server capacity in advance when demand changes, as it adjusts itself automatically. Some of its amazing features are usage-based pricing and integration with services like Blob Storage, Cosmos DB, and Event Hubs. 

Google Cloud Functions

Google Cloud Functions is a serverless service that runs small pieces of code when an event or HTTP request occurs. You can use it to perform tasks such as building APIs, processing data, handling IoT events, and creating chatbots. The platform supports languages such as Node.js, Python, and Go. Google Cloud also provides Cloud Run, which allows applications and services to run without direct infrastructure management. It provides you with flexibility because resources can increase or decrease according to demand, and services can even scale down when they are not being used. 

Use Cases of Serverless Architecture

Serverless applications are meeting the needs of different industries owing to their flexibility and scalability. The following are the prominent use cases of serverless architecture:

• Data processing pipelines: Serverless functions can process huge volumes of real-time data; therefore, they are suitable for building data processing pipelines. Such pipelines will process data, analyze patterns, and store the results for other uses.
• Asynchronous processing: Serverless functions often run in the background without blocking or delaying the user’s actions on the front-end part of the application.
• Chatbots and Virtual Assistants: Event-driven, stateless serverless functions treat every interaction as an isolated event, where each question triggers an invocation, resulting in no delay in response.
• Cron jobs: Developers can schedule tasks to run at specific times without managing the underlying infrastructure. The serverless functions scale automatically according to traffic and run even if they fail, as they are fault-tolerant.
• Authentication and authorization: The serverless approach executes user verification only when needed, rather than keeping a dedicated authentication server running continuously.
• Machine learning Inference – ML models can be deployed without dedicated infrastructure, as the functions get triggered only when an inference request is made.

Best Practices for Serverless Architecture

We studied the various advantages of serverless architecture that can help you develop applications with fewer resources and at a lower cost. However, it’s important to implement the serverless architecture by following the industry-accepted practices to achieve the desired results. 

The following are some of the most popular best practices you must implement for serverless applications:

1. Manage Code Repositories

It becomes easy to manage Serverless applications when you divide their functionality into small, independent services by using frameworks such as AWS SAM and Azure Functions. You can keep separate code repositories for individual functions or related services. This would make updates and deployment simpler as the project grows. Use managed services for databases, messaging, and authentication to reduce the operational overhead.

2. Do Not Use Too Many Libraries

Keep serverless functions lightweight and remove unnecessary dependencies to improve their startup speed and overall performance. When a function depends on many libraries, it takes a long time to load everything before execution begins. You should therefore include only the libraries that are actually needed. 

3. Maximize Performance

It requires thorough testing and careful resource choices to improve a Lambda function’s performance. You should try different memory settings because memory allocation also affects processing power and network performance. Keep the code package small and avoid unnecessary initialization to easily start the functions. Reuse existing database or HTTP connections to reduce delays between requests, and use tools such as AWS X-Ray to identify slow parts of an application and know the places requiring performance improvements. 

4. Perform Extensive Monitoring and Logging

Monitoring and logging help you understand how well serverless functions are working and quickly find problems. Cloud platforms provide tools that can record errors, execution times, usage levels, and other important details. You can control the amount of information recorded by using environment settings, such as a log-level option. Keep an eye on key metrics like invocation count and execution duration, and set suitable alerts for these measurements to notice unusual behavior early and take action before it affects users.

When to Use a Serverless Architecture?

It’s not necessary that serverless architecture will benefit every kind of application development, despite its increasing popularity. You must know the scenarios suitable for implementing the serverless approach. 

The following are some of the most common scenarios where you should go for the serverless architecture:

• To develop event-driven IoT applications and lightweight IoT gateways that perform protocol conversion and data filtering. 
• To build real-time data processing applications where the incoming data streams trigger the functions. 
• You can write serverless functions to process data, train and deploy machine learning models, and generate personalized recommendations 
• If you want to develop chatbots and voice assistants where serverless functions will process user requests and provide appropriate responses. 
• To implement CI/CD pipelines to automatically build, test, and deploy code using event triggers.

Real-Life Examples of Serverless Architecture

Let’s get an idea of how some of the major technology providers use serverless architecture to increase the efficiency of their existing products and services:

Coca-Cola Vending Machine

Coca-Cola’s vending machine, called Freestyle, is a serverless smart vending machine. Customers can order and pay for their drinks online and receive them with a confirmation message on their mobile phones. The adoption of serverless computing has decreased their operating costs by almost sixty percent.

Netflix Scalable On-demand Media Delivery

Netflix adopted the serverless platform AWS Lambda in 2017. The Dynamic Scripting Platform handles real-time platform modifications, provisioning, and end-user delivery.

Slack Chatbots

Chatbots have become an integral part of Slack’s value proposition by enhancing user productivity, collaboration, and task automation. These bots can respond to queries, integrate with third-party services, automate repetitive tasks, and trigger workflows based on certain events.

Final Thoughts

Serverless architecture is a modern and effective way to develop scalable and cost-effective applications. Businesses now have the opportunity to focus mainly on developing innovative applications rather than worrying about physical infrastructure management. You just need to select a suitable cloud provider as per your specific requirements, and they will handle the resource allocation and scaling up and down of the application. However, do take the important considerations and limitations of the serverless model in mind while adopting the serverless architecture. 

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