Serverless architecture is a method of creating software that enables developers to develop and operate services without having to deal with the underlying infrastructure. This approach allows developers to code and release their applications while a cloud provider provides servers to execute their programs, databases, and storage systems at any size.
In this article, we’ll explain how serverless architecture operates, its advantages and disadvantages, and various tools that can assist you in going serverless.
How Serverless Architecture Works?
Servers enable users to interact with an application and utilize its business logic. However, managing servers requires a significant amount of time and resources. Teams are responsible for maintaining server hardware, ensuring software and security updates are up-to-date and creating backups in case of failure.
By embracing serverless architecture, developers can delegate these duties to a third-party provider, freeing them up to concentrate on developing application code. Function as a Service (FaaS) is a commonly used serverless architecture where developers create their application code as separate functions that are triggered by events such as an incoming email or an HTTP request.
Once the functions are written and tested, they are deployed along with their triggers to a cloud provider account. When a function is invoked, the cloud provider handles the execution process by either running it on an existing server or creating a new one if needed. This abstraction of the execution process allows developers to concentrate on creating and deploying their application code without worrying about the underlying infrastructure.
Although serverless architecture has existed for over ten years, it wasn’t until 2014 that Amazon released the first widely-used FaaS (Function as a Service) platform, AWS Lambda. Presently, most developers still use AWS Lambda to create serverless applications, but Google and Microsoft also have their own FaaS options called Google Cloud Functions (GCF) and Azure Functions, respectively.
Important concepts in Serverless Architecture
The serverless architecture eliminates the need for managing servers, but it still requires a significant learning curve, especially when multiple functions are combined to create complex workflows within an application. It’s useful to become familiar with some essential serverless terms, including invocation (a single function execution), duration (the time it takes for a serverless function to execute), cold start (the latency that occurs when a function is triggered for the first time or after a period of inactivity), concurrency limit (the maximum number of function instances that can run at the same time in a region as determined by the cloud provider), and timeout (the maximum time allowed for a function to run before the cloud provider terminates it). It’s important to note that cloud providers may use different terminology and set distinct limits on serverless functions, but the concepts outlined above are fundamental.
Serverless and container architectures provide developers with the ability to deploy their application code without needing to deal with the underlying host environment. However, there are significant differences between these two approaches. With container architecture, developers need to maintain and update each container they deploy, including its system settings and dependencies.
In contrast, serverless architectures handle all server maintenance tasks on behalf of developers. Additionally, serverless apps automatically scale, while container architectures require an orchestration platform such as Kubernetes for scaling. Containers enable developers to manage the underlying operating system and runtime environment, which makes them a suitable choice for applications that frequently experience high traffic or as a starting point in cloud migration. On the other hand, serverless functions are better suited for trigger-based events like payment processing.
Pros and Cons of Serverless Architecture
Serverless adoption has grown significantly in recent times, with almost 40 percent of companies around the world utilizing it in some way. Businesses of all sizes, from small startups to large corporations, are utilizing serverless architectures due to the following reasons:
- Cost: Cloud providers charge based on the number of invocations, which means companies don’t have to pay for unused servers or virtual machines.
- Scalability: Function instances are automatically created or removed based on traffic changes within concurrency limits.
- Productivity: Developers using serverless architectures can easily deploy their code without managing servers, leading to quicker delivery cycles and company growth.
Serverless architectures come with certain difficulties that include:
- Reduced Control: When operating in a serverless environment, you have limited control over the software stack that your code runs on. In case of any problems such as a hardware fault or data center outage, you depend on the cloud provider to address the issue.
- Security Risks: A cloud provider may host multiple customers’ codes on the same server simultaneously. If the server isn’t properly configured, there’s a risk that your application data might be compromised.
- Impact on Performance: When serverless functions are invoked after being idle for a while, it’s common to experience a delay of several seconds before they start executing, which is known as a “cold start.”
- Testing: While developers can test individual functions, it’s challenging to perform integration testing in a serverless environment because it’s hard to evaluate how different components interact with each other, especially between the frontend and backend.
- Lock-In with Cloud Provider: Major cloud providers like AWS provide a variety of services, including databases, messaging queues, and APIs, that work together seamlessly for running serverless applications. While you can use different services from different providers, it’s more challenging to integrate them, and sticking with one provider may offer better integration.
Businesses aiming to reduce their time to market and develop easily expandable, lightweight applications can derive significant advantages from utilizing serverless computing. However, for applications that involve a high volume of prolonged, ongoing operations, virtual machines or containers may be the more suitable option.
In a mixed infrastructure setting, software developers could opt to employ containers or virtual machines to handle the majority of requests, while transferring certain brief, intermittent tasks, such as database storage, to serverless functions.
Serverless architecture is most effective when utilized for performing tasks that have a short duration and managing workloads that don’t have a consistent or predictable amount of traffic. The primary situations where serverless is applicable include:
Tasks that are initiated by a user action can be effectively executed using serverless architecture. For example, when a user signs up on a website, this action can trigger a database change, which in turn can trigger an email notification. The backend tasks required for this process can be performed using a sequence of serverless functions.
To create scalable RESTful APIs, you can use serverless functions in combination with Amazon API Gateway. Serverless functions can be used for background processing of application tasks such as rendering product information or converting video files, without impacting the user experience or causing delays in application response time.
Before a new container is started, it’s possible to use a function to check for any errors or weaknesses that could be exploited. Additionally, functions can offer a safer alternative to SSH verification and two-factor authentication.
In a serverless architecture, various steps in the CI/CD process can be automated. For instance, when a new code is committed, a function can be triggered to build it, while pull requests can trigger automated tests.
Many developers adopt a gradual approach when transitioning to serverless, where they gradually transfer some components of their application to serverless while keeping the rest on traditional servers. Because serverless architectures are highly flexible, developers can continue to add more functions as new opportunities arise.