Serverless vs. microservices: Which architecture is best for your business

When enterprises need to build an application, one of the most important decisions their leaders must make is what kind of software development to use. While there are many software architectures to choose from, serverless and microservices architectures are increasingly popular due to their scalability, flexibility and performance. Also, with spending on cloud services expected to double in the next four years, both serverless and microservices instances should grow rapidly since they are widely used in cloud computing environments.

While serverless architectures are generally favored by startups and businesses that need to build fast and scale rapidly, microservices are more popular with organizations that require more hands-on management of backend infrastructure. Serverless and microservices solutions are offered by all the leading cloud computing technology companies, including Microsoft (Azure), Amazon (AWS Lambda), IBM and Google Cloud.

Here's a more in-depth look at what makes serverless and microservices unique and how to choose which one is right for you.

What is serverless?

Serverless, also known as serverless architecture or serverless computing, is an approach to software development that empowers developers to build and run application code without having to worry about managing the underlying infrastructure.

In a serverless environment, routine maintenance tasks like installing operating systems (OS) and software updates, managing security, monitoring, and more are outsourced to a cloud service provider (CSP).

Despite its name, a serverless framework doesn't mean computing without servers. However, in serverless platforms, the CSP (instead of the developer) handles the provisioning of servers, freeing them up to focus on code and business logic. Another advantage of serverless applications is that they allow cloud providers to provision resources on an on-demand model, which is more flexible and cost effective. With serverless, billing starts when code execution starts and ends when it ends. Along with infrastructure as a service (IaaS), and function as a service (FaaS), serverless has become a leading cloud service offering.

What are microservices?

Microservices, also known as microservices architecture, is a cloud computing architectural approach where the entire application is made up of many independent and interconnected smaller parts. Microservices applications often have their own stack that includes a database and database management model.

Microservices communicate using a combination of representational state transfer (REST APIs), event streaming, and message brokers. Typically, microservices are categorized by their business capabilities (e.g., microservices for search engines or online order processing), with a line separating service called a bounded context.

Like serverless, microservices' fortunes are closely linked to that of cloud infrastructure. With cloud infrastructure use cases growing exponentially worldwide, spending on microservices are expected to reach USD 6 billion in the next four years.

While microservices are often talked about in the context of their architectural definition, it can be easier to understand their business value by looking at them through the lens of their most popular enterprise benefits:

• Change or update code without affecting the rest of an application.
• Change stacks and programming languages easily.
• Utilize highly scalable components that are independent of each other.

Serverless vs. microservices: Important differences to consider

Both serverless and microservices architectures share the goal of enhancing the flexibility and scalability of complex applications. While they share many similarities, there are some important differences to consider, including the following:

Scalability

Both serverless and microservices are considered 'highly scalable,' meaning they enable software solutions to add users while still achieving a high level of performance.

The difference comes in the level of control vs. the level of automation the two architectures offer an organization. Serverless technologies enable individual functions to scale automatically based on triggering events, while microservices allow for each service to be scaled independently, on demand. While the microservices approach requires more manual configuration, it also gives developers more control.

Development

Again, when it comes to development, the difference between implementing serverless and microservices comes down to the level of control your organization requires.

Microservices need each service and function to be independently built, tested and deployed using a container like those created by Docker and/or a container orchestration platform like Kubernetes. While this approach offers more customizability than serverless, it also requires more coordination, time and oversight from developers.

On the other hand, serverless is built for rapid development and deployment cycles with high agility and reduced complexity. In a serverless architecture, management of underlying infrastructure-such as installation and configuration of an OS, server management and updating software-is outsourced to a CSP. This allows application functions to be automatically packaged, deployed and scaled.

Infrastructure management

In a serverless architecture, all the provisioning, management and scaling of infrastructure is managed by a third party (typically a CSP), enabling developers to focus exclusively on business logic and writing and deploying code.

Also, in a serverless model, code runs closer to the user, decreasing its latency and improving speed and performance. However, while developers can focus more closely on writing code in a serverless model, they have little or no control over the underlying infrastructure, such as the OS or provisioning of servers.

In a microservices architecture, developers are required to manage the stack that supports each microservice they plan on deploying. This includes any applicable infrastructure, development processes and network configurations. While microservices offers greater control over the development environment, it also requires a higher level of expertise for developers when it comes to DevOps, the methodology that enables application development.

Granularity and monolithic architecture

Granularity refers to how much a system is broken down into smaller parts. Both serverless and microservices are considered more finely grained than their predecessor, monolithic architecture.

Monolithic architecture combines all the functionalities of an application, such as user interface, logic and database operations, that serverless and microservices break apart. The simplicity of monolithic architecture was-and still is-attractive to some enterprises that need to develop simple applications with a singular focus.

Microservices-based architecture is finer-grained than monolithic architecture, but not as finely grained as serverless. Microservices architecture breaks down monolithic applications into smaller, more independent services that can be deployed separately. Serverless architecture is even more finely grained. Serverless models break down each application into individual functions that are even smaller than services. In a serverless architecture, each function represents a fragment of business logic and is only executed when it is triggered by a specific event.

Runtime

In a serverless environment, management of critical infrastructure needed to develop and deploy code is outsourced to a CSP, including runtime-the environment in which an application or service is programmed to run. This means that data being stored while a function is executed is lost the instant the function is complete.

Microservices architectures, on the other hand, are often run on dedicated virtual machines, or VMs, which enables them to store their state.

Cost

Microservices architectures are often less cost-efficient than serverless because of their billing models. While serverless functions are billed according to the number of events that trigger code deployment, microservices require costs to be paid upfront based on the provisioning of infrastructure and other resources.

With a microservices architecture, organizations pay for resources regardless of whether they will be used, while in a serverless architecture, users are only billed per use.

Serverless microservices

Depending on an organization's needs, it is possible to combine the best of both serverless and microservices architectures into a model known as 'serverless microservices.'

Serverless microservices is a hybrid architectural framework where microservices are built as a serverless function. Serverless functions are well suited to microservices because of their high scalability, and they can be easily combined with managed services, sometimes lowering the cost of a microservices operation.

This approach allows developers to concentrate on building more specialized functions than are typical to a serverless environment (but without the headache of managing infrastructure). Combining serverless and microservices architectures yields many of the same benefits as using the architectures independently, including scalability, cost efficiency and flexibility. There are, however, also some challenges worth considering.

Challenges of serverless microservices

1. Function boundaries: Defining function boundaries can be problematic in a serverless microservices environment, and development teams often struggle to define the roles of each function. Sometimes, this causes them to stretch logic across too many functions until it no longer makes sense.
2. Performance: It's difficult to ensure application performance will remain high in any serverless environment due to several issues; most notably, an issue called 'cold starts.' Cold starts occur when a function is triggered after a period of inactivity. It can cause delays of two or three seconds when a new container instance is required and no warm containers are available.
3. Monitoring: It can be hard to monitor applications in serverless microservices architectures and find out where the root cause of a problem is. Applications may be built out of numerous microservices and functions, making tracing requests through the environment-necessary to understanding many common problems-difficult.

Serverless and microservices use cases

As the use of cloud computing continues to grow and businesses look for new ways to leverage the technology to create new business value, both serverless and microservices use cases are expanding.

Serverless use cases

Artificial intelligence (AI) and machine learning (ML)

The last few years have seen massive growth in business use cases for artificial intelligence (AI) and machine learning (ML) applications, especially in generative AI. Specifically, serverless helps enable something called event-driven AI, where a constant flow of intelligence informs real-time decision-making capabilities.

Hybrid cloud

Hybrid cloud combines public cloud, private cloud and on-premises infrastructure to create a single, flexible, cost-optimal IT infrastructure. Serverless helps support enterprises who are adopting a hybrid cloud strategy by providing the agility, flexibility and scalability the technology needs.

Big data analytics

Serverless dramatically reduces the cost and complexity of writing and deploying code for data applications. Serverless environments allow developers to focus on their code and business logic, rather than all the routine tasks of managing infrastructure.

Microservices use cases

Cloud computing

While microservices are not required for cloud computing environments, their architectures make them an excellent fit because of their distributed application components. Microservice architectures enable service and functions to work independently and be deployed to support an application. Additionally, microservices' high scalability means it can run multiple instances on a server, another plus for cloud computing environments.

Real-time data processing

Applications that need data to be processed in near real time, like those that support autonomous vehicles or streaming video, are particularly well-suited to microservices. Microservices enables operations to be executed in real time so they can deliver immediate output, allowing these types of applications to function.

Re-factoring

Re-factoring-when an enterprise decides to redesign its IT capabilities-is a common use case for microservices architectures. Often, IT departments are looking to re-factor from a monolithic model towards something more flexible and efficient, which microservices can deliver.

Serverless or microservices: Which is right for your business?

Choosing the right architecture for your application is one of the most important decisions your business can make. Here are a few questions to help determine if serverless or microservices architectures are a good fit:

• What kind of application are you building?
• How fast does it need to be built?
• How much are you willing to spend?
• How much control do you need to have over your underlying infrastructure?
• How complex do you expect the process to be?
• Do you plan on doing multiple iterations?

While these are just a sample of questions you may want to consider, they should help create a framework for making your decision.

Typically, businesses looking to move fast and iterate often choose a serverless architecture, while businesses with more complex and demanding applications-and who don't mind a longer development cycle-go with microservices. But these are broad generalizations, and you should consider the strengths and weaknesses of both technologies before making your decision.

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