Serverless vs Container vs VM: Choosing the Right Architecture

The choice between Serverless, Containers, and Virtual Machines is a critical decision in the design of applications in the modern era. Each of these models provides different benefits in terms of cost, scalability, and performance. The choice of the model depends on the type of workload, the expertise of the development teams, and the business needs. The knowledge of these models and how they function is essential in the design of efficient and easily manageable systems. In this article, we will see the comparison of Serverless vs Container vs VM and learn how to choose the right architecture.

Understanding Virtual Machines ( VMs)

Virtual Machines, also known as VMs, operate in a manner where they operate on top of a hypervisor that acts as a bridge between the physical hardware or host machine and the virtual machines themselves. The hypervisor, also known as a machine monitor, is software, firmware, or hardware that enables users to operate multiple VMs on a single physical machine.

A Virtual Machine operates on its own operating system, allowing users to operate multiple operating systems on a single machine. This means that users can operate a Linux VM alongside a UNIX VM on a physical machine. Each Virtual Machine also operates independently with its own stack of hardware, including CPU, storage devices, network devices, applications, and libraries, allowing users to operate multiple VMs on a physical machine independently.

Understanding Containers

Containers operate in a different manner compared to Virtual Machines. While Virtual Machines operate using hardware virtualization, Containers operate using operating system-level virtualization. This means that they do not operate on an independent machine but share the operating system of their host machine while operating independently in their own space.

Although it looks similar to Virtual Machines, every container operates independently in its own environment. Each container is able to operate processes, execute commands, mount its own file system, and even have its own network interface and IP address. However, it is important to note that all Containers share a common operating system, making it lightweight.

Each of these Containers has its own user space, which enables multiple Containers to run on the same machine without conflicts. This is because the OS is already shared. Therefore, there is no need to build everything from scratch. Instead, you just need to package the necessary binaries and libraries, and these are normally done through images, such as Docker images. This makes it easier to build, run, and scale Containers.

Containers run on top of a container engine, like Docker, and the engine is running on top of the OS. This is done through the Linux kernel. This enables developers to easily run and manage Containers without having to worry about the underlying infrastructure.

Understanding Serverless Architecture

Serverless architecture allows you to run your code without any hassle. You just need to write your code using languages such as C#, Java, Node.js, or Python. You need to set a few configurations and then upload your code to a cloud platform. AWS Lambda does the rest for you.

The term Serverless is a bit confusing. You might be wondering how you can run your code without a server. But the reality is, you are using a server. You don’t have to manage, set up or take care of your server. You just need to rely on a cloud platform, such as Amazon Web Services.

With this approach, the code you upload is typically referred to as a function. This type of code only runs when triggered, making Serverless computing very efficient for event-based workloads. This approach is called Function-as-a-Service (FaaS), where a function is responsible for a single task and runs on demand.

Serverless computing also plays nicely with Backend-as-a-Service (BaaS). This is typically utilized in modern application development, such as a single-page application or a mobile application, where you use existing cloud-based services for various application components, such as a database or authentication. With Auth0 or Amazon Cognito, for instance, you don’t need to develop your own authentication system.

Serverless vs Container vs VM: Which Is Right for You?

When it’s time to decide between Virtual Machines, Containers, or Serverless, it’s essential to know the differences, especially with regard to costs, performance, and their applications. Virtual Machines are the traditional base on which cloud computing is built. They allow full control over the operating system, runtime, and scaling. This is best suited for applications that are legacy-based, applications that heavily depend on CPU or GPU, or applications that need custom operating system versions.

With full control over the operating system, runtime, and scaling performance is always guaranteed. The only drawback is the associated cost, which is always incurred, irrespective of the actual usage. This makes Virtual Machines the costliest option, in terms of both direct costs and total cost of ownership.

On the other hand, Containers strike a balance between control and efficiency. Containers allow your application and its dependencies to be self-contained so that it can run in any environment. This is also good for microservices, APIs, and high throughput with predictable traffic. This also scales well using container orchestration platforms like Kubernetes. This increases resource usage and minimizes waste compared to VMs.

However, this also comes with its own set of complexities because it requires DevOps or SRE teams to manage clusters and configuration. In terms of cost, this is more efficient than VMs because it allows for reserved capacity and usage optimization for predictable and consistent workloads. Moreover, it may not be as cost-effective as Serverless options for unpredictable workloads.

With Serverless computing, also referred to as Functions as a Service or FaaS, you don’t have to worry about infrastructure at all. You simply deploy your functions, and the service provider takes care of the rest. Serverless computing is best for applications with unpredictable or intermittent traffic, for example, a sudden increase in website traffic, background tasks, or event-driven applications. You’re only billed for the execution of your function, and this can be very cost-effective.

Performance is excellent for short-running functions, but the first call to a cold function, a function not recently run, takes a little longer as the runtime environment starts up. Serverless provides infinite elasticity for your applications since you don’t have to worry about how many requests your server can handle.

In simple terms, VMs are best suited if you need control and consistent availability, Containers are best suited if you need to scale predictable high-volume workloads efficiently, and Serverless is best suited if you need cost efficiency in spiky traffic patterns. Each of them has its pros and cons, and the choice really depends on the nature of the traffic and the nature of the application’s requirements.

Common Mistakes Developers Need to Watch Out For

This is where developers get caught in a bind, trying to implement a single strategy across all their workloads. Selecting either Serverless or Containers exclusively will ultimately be a recipe for disaster, leading to increased complexity or unnecessary costs. The best option is to select a balanced and hybrid approach.

One of the biggest pitfalls is to implement a purely Serverless environment because it’s considered to be cost-effective and easy to manage. The truth is, while a Serverless environment may be cost-effective in a spiky environment, it’s not effective in a steady, high-traffic environment. Moreover, it’s not effective in handling long-running tasks and complex states. An attempt to implement this using a purely Serverless environment will result in a messy, slow, and difficult-to-debug environment.

On the other side, some teams are eager to depend on Kubernetes without really knowing what it takes to run it properly. While Containers can be great, they can also pose their own set of issues. A misconfigured cluster can result in overprovisioning, where you pay for resources you are not using. The container networking is also more complex than traditional VMs, which can make troubleshooting hard if your team is not prepared with the right tools or best practices.

The bottom line is to pick the right tool for the right job, not necessarily the trendiest or the one that everyone is using. Using Serverless for unpredictable, event-driven tasks and Containers or VMs for predictable, heavy tasks will yield a simpler, cheaper solution. Don’t try to force every task to fit your chosen solution, but pick what is best for your specific case.

The Developers.dev Architectural Decision Framework (ADF)

The Developers.dev Architectural Decision Framework (ADF) is a three-step approach to help you select the correct deployment approach for your microservice or application components. This approach helps you avoid hype-based decisions and ensures your workloads get the deployment approach that best fits them.

Step 1: Define the Workload Profile

The first step for developers.dev ADF is to identify your workload profile. This involves examining the behavior of your microservice or application components. Consider your workload’s traffic type. Is it a bursty workload, such as nightly reports or user signups, or a steady workload, such as a core API or a background worker servicing a queue? Next, consider the statefulness of your workload. Is your workload stateless, allowing for an immediate restart, or is it a stateful workload that requires storage or session affinity?

Step 2: Score Against Core Constraints

The next step is to score each of the deployment models, such as VMs, Containers, and Serverless, against your top business priorities, such as cost, speed to market, or security compliance. A simple scoring system using a 1-5 scale, where 5 is the best match, allows you to visualize the deployment model that is the closest match to your needs. For example:

Workload Requirement	VMs (IaaS)	Containers (CaaS)	Serverless (FaaS)
High predictable load (cost priority)	4	5	2
Bursty/unpredictable load (cost)	1	3	5
Low latency/high throughput	4	5	3
Legacy dependency (custom OS/binary)	5	3	1
Portability/multi-cloud strategy	2	5	1
Zero management overhead	1	3	5

 

Step 3: Pragmatic Recommendation

Finally, make a pragmatic recommendation. Modern architectures do not rely on a single model anymore. Use Serverless for non-critical, event-driven, or bursty workloads to cut costs fast. Use Containers like Kubernetes for critical workloads where performance and portability matter most. Use VMs for legacy systems or highly specialized workloads where custom OS/binaries are required.

This framework is useful for balancing costs and performance while reducing management complexities. Developers can also leverage this framework to determine where Kubernetes provides multi-cloud flexibility and where Serverless provides cost optimization benefits. The secret is a hybrid approach that matches technologies to workloads while ensuring they remain efficient, reliable, and scalable without over-engineering management complexities.

Conclusion

It’s not about picking the best among Serverless, Containers, or Virtual Machines. It’s about being aware of your workload and using each approach where it makes the most sense. Serverless is good for event-driven and unpredictable workloads, Containers shine for scalable and consistent workloads, and VMs might still have a place for legacy or special workloads. A balanced approach, also called a hybrid approach, will help you optimize cost, performance, and flexibility without adding unnecessary complexity.

FAQs

1. Which is cheaper: Serverless, Containers, or VMs?

Serverless is the cheapest for bursty traffic, Containers for steady traffic, and VMs for predictable long-term usage with reserved capacity pricing.

2. When should I use Serverless architecture?

Use Serverless for event-driven applications with short execution times, unpredictable traffic, and when you want a low management overhead and quick development cycles.

3. Are Containers better than Virtual Machines?

Yes, Containers are lighter and faster than VMs.

4. Do Containers replace Virtual Machines completely?

No, Containers don’t completely replace VMs. VMs have their own advantages for legacy applications, compliance, and special hardware requirements.

5. Can I use Serverless, Containers, and VMs together?

Yes, you can definitely use a combination of Serverless, Containers, and VMs.