Table of Contents
Table of Contents
Serverless and Containers have always been at loggerheads as both are machine-agnostic. Going serverless can save organizations money and time, whereas, containers are easy to move around and can be run anywhere.
The interesting thing is that Serverless is pretty new compared to its counterpart, containers. Containerization was introduced back in the day in 1979, while Serverless came into existence around 2014-15. Given that they have almost a 40-year gap, it’s worth knowing that they both hold a promising market share. The serverless market share exceeded USD 9 billion in 2022 and is set to grow at 25% CAGR from 2023 to 2032. In contrast, container architecture is expected to reach USD 4.98 billion by 2023 but has a better CAGR of 32.9%.
For the same reason, some software enthusiasts claim that serverless can replace containers. While others believe that containerization is the future. However, when deployed independently, they can bring a massive change in the organization’s processes. The former brings ease in managing unpredictable workloads, and the latter allows smooth application deployment when split into small parts.
This blog highlights the most significant debate on choosing the right architecture for your software application: Serverless vs Containers.
Let’s talk about how Coca-Cola functioned earlier and how going serverless was the right architecture for them.
They communicated with their customers through an integrated system of vending machines in different locations linked to their headquarters. When a customer buys a drink, it sends an API rest request to the payment gateway.
In 2016, Coca-Cola decided to avail the benefits of cloud deployment models by going serverless by integrating AWS Lambda. It helped them handle all the requests easily by adding the push notification feature when customers transact on the mobile app.
The migration to the cloud brought a massive reduction in costs. How? Earlier, they were using 6 EC2 T2 machines which cost them almost $13k annually. The transition to serverless architecture increased their savings to $8,500 on each machine. And they have around 3 million vending machines around the world. Going serverless brought their costs down to $4,500 per year.
Imagine the amount of savings they made by changing the course of their functions.
Beat unpredictable workloads without maintaining host environments regularly.
The above story brings us to explain the first section of this blog.
Serverless computing is a type of architecture providing back-end services on demand. It uses managed services so that you can avoid rebuilding the existing cloud infrastructure.
Sometimes, many software organizations use a multi-cloud strategy and want to migrate their infrastructure from one to another. In such scenarios, serverless architecture can prove highly advantageous. The serverless provider they chose maintains all the underlying infrastructure, and development teams can focus only on deploying the code.
Simply put, the concept of serverless emerges from the fact that users are unaware of the existence of physical servers. Serverless computing is ideal for teams to write and release applications quickly without maintaining and managing servers or underlying infrastructure. You should also consider serverless functions in cases of unpredictable workloads.
The biggest advantage of going serverless is that the users can execute code as per their needs. They don’t have to maintain a host environment regularly. Eventually, it helps save money when resource-intensive coding is a priority.
However, deploying applications on servers comes with considerable responsibility for resource management and provisioning. Hence, it also brings some issues with it:
Serverless computing functions behind the scenes, but it’s not managed by a developer. The cloud development services and functions performed in serverless computing are usually lightweight. They all have a single purpose – finding a customer’s details or sending a notification from the database. Hence, cloud deployment models fall under the Functions-as-a-Service (FaaS) category. Some notable leading cloud providers with serverless functionality include Azure, AWS Lambda, Google Cloud, Heroku, PubNub, and Firebase.
Coca-Cola’s story gave an insight into how big corporations dealing with APIs need a serverless architecture to smoothen their transactions. Like Coca-Cola, some other companies that went serverless include Shamrock Trading Corporation, Netflix, Nordstrom, and Figma.
Organizations should invest in serverless architecture in the following scenarios when:
Now that we have explained serverless computing, let’s familiarize ourselves with how VISA transformed its monolithic applications by choosing containers as its architecture.
VISA overlooks almost 130 billion transactions, which puts pressure on them to scale up and maximize the utilization of existing data centers. In 2020, it embraced containerization architecture by moving its legacy monolithic applications to microservices-based architecture.
Since splitting services brought challenges of monitoring and protection from attacks, VISA’s security team developed their project, Micro-services based Adaptive Security Hardening and Usage Platform (MASHUP). They also moved to Docker Containers-as-a-Service architecture, which raised their scalability potential by 10 times.
The migration brought ease in maintaining, updating, and deploying services on the cloud. It earned them a business excellence award due to the advantage it brings over native capabilities of orchestrated environments and has open-source tool libraries. By introducing two key technologies of cloud development services, they can now reduce the time teams spend on refreshing hardware and patching.
Smoothly run your applications when you migrate from one environment to another.
Containerization transformed the VISA working process. Let’s understand how.
Containers are lightweight, allowing you to quickly deploy your applications even when you have a multi-cloud strategy. You can package all the dependencies necessary to run your application. They are like cargo transporting an application and its elements. It moves all the elements required to run the application correctly on an OS, including libraries, settings, and other system components.
Even though they are similar to Virtual Machines, they don’t virtualize entire computers. Instead, it only virtualizes the Operating System (OS), making it easier to set up. However, containers work most effectively when the application is split into small parts.
Containers divide a machine into separate environments. Each environment then runs its application without interacting with any other section. The foundation of each OS, i.e. kernel, is present in each container and is shareable across others. However, they run as an independent system on the machine.
In organizations where development teams follow Agile and DevOps structures, containerization solves one crucial problem. It ensures developers don’t worry about where their applications will deploy. Containers facilitate the smooth running of applications when migrating from one environment to another. It simplifies the microservices architecture and brings ease to developing and testing a software application. Further, development teams can work independently on different parts of the application.
Docker and Kubernetes are two highly prevalent orchestration platforms for managing containers. Developers use them to push out to different machines ensuring they run smoothly. They simplify handling the underlying infrastructure by automating, scheduling, networking, monitoring, and scaling.
The story of VISA is an example of how containerization can provide agility, flexibility, and portability for effective development and reduction of overall costs. Like VISA, some other giants using containerization for their cloud cost optimization include Citizens Bank, Pinterest, and BetaLabs.
Containerization is the ideal architecture when:
Even though Serverless architecture and containerization are two distinct approaches to cloud consulting services, they have some similarities. In both systems, the hosting environment abstracts the applications, which makes them more efficient than a virtual machine. Though they require scaling tools, they primarily aim to deploy the application code.
| Similarities | Differences |
| In both cases, developers don’t need to worry about underlying infrastructure or servers. | Serverless: FaaS (serverless) provides scalability out of the box. |
| Containers: They require containerization software like Kubernetes for scaling up or down. | |
| They both compartmentalize the host OS away from the guest OS. | Serverless: Serverless functions are small, short-lived, and self-contained with a single responsibility. |
| Containers: Containers are extensive and long-running with multiple responsibilities. | |
| Both options provide high scalability with better hardware like powerful CPUs, memory, and networking. | Serverless: The prices for serverless functions are billed only for the time they run. |
| Containers: If you keep running some container instances 24×7, it will generate a higher bill. Exception – AWS Fargate. | |
| Both can also scale on demand-specific cases, like more traffic, and based on metrics, too, like the number of routed requests. | Serverless: Serverless functions have the disadvantage of tying you up with a single vendor. |
| Containers: Vendor lock-in is not an issue with containers and is neutral. | |
| Both have high compatibility with continuous integration (CI) platforms | Serverless: The supported languages are limited to serverless applications, |
| Containers: Containers can support any language. |
Choose the most suitable architecture whether you have a small or complex application.
While choosing the architecture for building your application, it’s essential to consider some factors that influence these cloud development services. However, the architecture’s structure and size should be the primary considerations. If you are deploying a small application, serverless is ideal to split it into microservices. In contrast, if you have a larger and more complex application, containerized architecture is more suitable. Let’s take a look at how different factors affect each of the applications:
While developing an application, developers work under a high-pressure environment to produce quality code. It becomes even more challenging when they are working with new technology and need to learn how it works. Development ability depends on how quickly they can set it up and running, ease in making changes, and finding errors.
Unlike containerized counterparts, serverless applications are easier to develop, test, and deploy. These applications use one programming language to write code but aren’t compiled in a binary. Instead, developers package them into a function. You don’t have to worry about setting up and managing the servers because the cloud development service provider oversees that. It enables you to direct all your focus on developing code and testing even in a local environment.
Container-based applications allow faster development because developers can use a programming language or framework they choose. Container applications then compile it into a binary to run on any environment with the same dependencies. They are easier to move, enabling you to speed up the process that matches the production environment.
Scalability is a measurement of a system’s ability to perform when there’s an increase in traffic or the number of users. Many organizations also try the hybrid approach, where serverless and containers work together using serverless functions to trigger container applications.
For example, developers use a simple serverless function like a file upload to trigger the containers for data processing. Going hybrid increases scalability, cost-effectiveness, and custom library usage, providing more control over the underlying infrastructure.
A serverless platform allows developers to maintain scalability and performance when the load increases incrementally. However, it’s not a suitable solution for applications requiring quick responses. Compared to dedicated servers, you might experience some slowness in running applications with serverless. This is because a cloud development services provider executes them on demand.
Container-based applications are comparatively more scalable than their serverless counterparts. Why? Because they enable them to add or remove containers to meet scaling needs quickly. Moreover, they provide more isolated environments – which means if a container fails to perform, it won’t impact other containers. This gives containerized applications an edge over serverless applications.
As explained earlier, the architecture you choose heavily impacts the deployment. Serverless architecture manages computing resources behind the scenes, focusing more on writing code. It packages the code as a serverless function, and the runtime invokes it every time it receives an incoming request. In containers, applications are packaged, which separates them from their underlying infrastructure. Deploying both types of architecture is different for each application.
Serverless applications work on Infrastructure as a Service (IaaS) model. In this, the cloud provider offers a virtual machine (VM), billed for the time used. It puts all the responsibility on the customer to add workloads, run the VM and scale it as per the requirements. However, the customer is not aware of the computing resources. The serverless runtime automatically provisions the resources to bill the customer based on the duration and number of times they run.
Containerized applications can be deployed in metal servers, VMs, specialized container instances, or managed services. Their engines run on image-based containers specifying the configuration and data should include a container. They can also create container images with multiple dependencies like web servers, databases, and application servers. However, containers are stateless – they lose all their data once shut down. But the advantage is that they are useful for stateful applications, i.e., storing and using data for external storage.
Portability is an essential factor to consider when choosing an architecture type. When using multiple services, it becomes vital to facilitate faster integration and accessibility with each service.
If you don’t want vendor lock-in, you can map all endpoints and URLs through a domain to eliminate unnecessary service. Fitting FaaS into the DevOps framework is still dodgy when migrating your infrastructure. It’s also highly possible that your development teams might forget which functions they wrote and which are still in use.
Moving container-based applications is easier because they are easy to package and deploy the code as a standalone. Hence, they provide high portability and require minimal time and effort. Plus, when there is a shortage of time-to-market and innovation is the highest priority, containers allow you to spin up new app versions. If you’re just starting, microservices are a good option for moving monolithic applications. However, running a container involves many interdependencies where you have to orchestrate planning upgrades for container hosts, images, and engines.
At Moon Technolabs, we utilize cloud development services to scale your business with IaaS, SaaS, and PaaS app development. We ensure infrastructure and pricing flexibility by using the latest cloud technologies and partnering with AWS, Azure, and Google Cloud.
We offer a smooth transition of your infrastructure by maintaining the business logic and identifying core dependencies. Our cloud consulting services with Kubernetes automate the orchestration and streamline daily operations. Growing scalability needs across operations compels organizations to invest in serverless.
Does the debate ever end with a winner? We think not. The arguments for serverless and container application architecture stand corrected at their corners. Choosing one between the both will depend on the type of application you want to develop and the goals you’re looking to achieve:
Similarly, if you’re looking for short-lived functionality like building an API server, going serverless would cut the deal because it’s event-driven. For example, an AI application only requires on-demand computing resources. In contrast, container architecture is ideal for building multi-tier applications which need regular maintenance and all-time availability for runtime.
Jayanti Katariya is the CEO of Moon Technolabs, a fast-growing IT solutions provider, with 18+ years of experience in the industry. Passionate about developing creative apps from a young age, he pursued an engineering degree to further this interest. Under his leadership, Moon Technolabs has helped numerous brands establish their online presence and he has also launched an invoicing software that assists businesses to streamline their financial operations.
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