When to use serverless computing

CoffeeBeans_BrewingInnovations
5 min readMay 3, 2023

Serverless computing has been gaining popularity as a powerful and efficient solution for building and deploying applications. With serverless computing, developers can focus on writing code without worrying about managing servers or infrastructure. In this blog post, we’ll take a deep dive into the architecture and capabilities of serverless computing, exploring how it works, its benefits and drawbacks, and its potential applications.

serverless computing

What is Serverless Computing?

Serverless computing is a cloud computing model where the cloud provider manages the infrastructure and automatically provisions resources as needed to execute code. This means that developers don’t have to worry about managing servers, scaling, or infrastructure maintenance. Instead, they can focus on writing code and building applications. Serverless computing is often used for building event-driven applications or microservices, where functions are triggered by events and execute specific tasks.

How Serverless Computing Works

In serverless computing, applications are broken down into small, independent functions that are triggered by specific events. These functions are stateless, meaning they don’t retain information between executions. When an event occurs, the cloud provider automatically provisions the necessary resources and executes the function. Once the function is complete, the resources are de-provisioned, making serverless computing highly scalable and cost-efficient.

Serverless Computing Architecture

The architecture of serverless computing typically involves four components: the client, the API Gateway, the compute service, and the data store. The client sends requests to the API Gateway, which acts as a front-end to the compute service. The compute service executes the functions in response to events and may interact with the data store to retrieve or store data. The API Gateway then returns the results to the client.

Benefits of Serverless Computing

Serverless computing offers several benefits over traditional server-based computing, including:

Reduced costs: Serverless computing allows organizations to pay only for the resources they use, rather than paying for dedicated servers or infrastructure.

Improved scalability: Serverless computing can automatically scale up or down depending on demand, making it highly scalable and efficient.

Reduced maintenance: Since the cloud provider manages the infrastructure, organizations don’t need to worry about maintaining servers or infrastructure.

Faster time to market: Serverless computing allows developers to focus on writing code and building applications, reducing the time to market new products and services.

Drawbacks of Serverless Computing

While serverless computing has several benefits, it also has some drawbacks, including:

Limited control: Since the cloud provider manages the infrastructure, developers have limited control over the environment and resources.

Cold start times: When a function is executed for the first time, it may take longer to start up, leading to slower response times.

Vendor lock-in: Organizations may be tied to a specific cloud provider, making it difficult to switch providers or migrate to a different environment.

Some facts about serverless computing

Serverless computing is often referred to as Functions-as-a-Service (FaaS) because it allows developers to write and deploy individual functions rather than entire applications.

Serverless computing is often used in microservices architectures, where applications are broken down into smaller, independent components that can be developed, deployed, and scaled independently.

Serverless computing can result in significant cost savings for organizations because they only pay for the resources they use. This can be especially beneficial for applications with unpredictable traffic patterns or occasional bursts of computing power.

One of the biggest drawbacks of serverless computing is the “cold start” problem, where a function may take several seconds to start up if it hasn’t been used recently. However, this problem can be mitigated through various optimization techniques.

Serverless computing is often used in event-driven architectures, where functions are triggered by specific events such as user interactions, changes to a database, or changes to a file system. This can make it easier to build highly scalable and efficient applications.

Now, let’s explore some other serverless computing frameworks that can be used in addition to Google Cloud Functions.

AWS Lambda: AWS Lambda is a serverless compute service from Amazon Web Services (AWS). It allows developers to run code in response to events without worrying about managing servers or infrastructure.

Microsoft Azure Functions: Microsoft Azure Functions is a serverless compute service from Microsoft Azure. It allows developers to run code in response to events and supports a wide range of programming languages.

IBM Cloud Functions: IBM Cloud Functions is a serverless compute service from IBM Cloud. It allows developers to run code in response to events and supports a wide range of programming languages.

OpenFaaS: OpenFaaS is an open-source serverless framework that allows developers to run functions on any cloud or on-premises infrastructure.

Apache OpenWhisk: Apache OpenWhisk is an open-source serverless platform that allows developers to run functions in response to events. It supports a wide range of programming languages and can be deployed on any cloud or on-premises infrastructure.

Kubeless: Kubeless is a Kubernetes-native serverless framework that allows developers to run functions on Kubernetes clusters. It supports a wide range of programming languages and can be deployed on any Kubernetes cluster.

IronFunctions: IronFunctions is an open-source serverless platform that allows developers to run functions on any cloud or on-premises infrastructure. It supports a wide range of programming languages and can be deployed on any container orchestrator.

These serverless computing frameworks offer developers a range of options for building and deploying serverless applications. Each framework has its own strengths and weaknesses, so developers should choose the one that best fits their needs.

Real-time examples

Coca-Cola: Coca-Cola uses serverless computing to power its Freestyle soda machines, which allow customers to mix and match different soda flavors. The machines use AWS Lambda functions to process customer requests and make recommendations based on their preferences.

iRobot: iRobot uses serverless computing to power its Roomba robot vacuums, which use computer vision and machine learning to navigate homes and clean floors. The Roomba vacuums use AWS Lambda functions to process data from their sensors and decide where to go next.

Capital One: Capital One uses serverless computing to power its mobile banking app, which allows customers to manage their accounts, transfer money, and pay bills. The app uses AWS Lambda functions to process requests and deliver real-time information to users.

Fender: Fender uses serverless computing to power its Fender Play platform, which provides online guitar lessons to users around the world. The platform uses AWS Lambda functions to process user data and generate personalized lesson plans.

Netflix: Netflix uses serverless computing to power its video encoding and transcoding workflows, which are used to prepare video content for streaming on various devices. The workflows use AWS Lambda functions to process video files and convert them into the appropriate format for each device.

Conclusion

Serverless computing is a powerful and efficient solution for building and deploying applications. It offers several benefits, including reduced costs, improved scalability, reduced maintenance, and faster time to market. However, it also has some drawbacks, including limited control, cold start times, and vendor lock-in. Despite these drawbacks, serverless computing will likely become an increasingly popular solution for building event-driven applications and microservices.

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