Containers

Comparing Serverless Computing vs Containers

Applications hosted on traditional virtual machines and servers are less flexible and involve a higher overhead cost. Containers and Serverless computing solves these weaknesses. They allow developers to build more flexible applications at low overhead costs.  A developer may choose a container or serverless architecture depending on the needs of the application. The features of these two architectures overlap in some aspects, but they are not interchangeable technologies.

Each of these works better in specific environments, as we will discuss later in this article. We will also look at the key differences between serverless computing and containers.

Why we need serverless computing

In the recent past, applications used to be deployed over big servers. The responsibility to manage and provision the resources lied upon the users.

Users associated this with several drawbacks since they had to:

Cover the costs for keeping the server up running even when not consuming any resources.
Maintain the server.
Apply the relevant security updates to the server.
Manage the scaling up of their server as usage scales up and manage to scale it down when they did not have much usage.

Serverless computing came as a solution to these problems. This computing technology provides users with an execution model, where a cloud provider executes a code by dynamically allocating resources.

Google Cloud, Azure, and AWS are examples of such cloud providers. This way, you only pay for the number of resources you used to run the application code.

As a result, you cut costs that you would have otherwise incurred when using traditional servers. The overall computing experience is 'serverless' because the cost of managing server resources is less.

Why we need containers

If you are planning to move software from one computing environment to another, your biggest concern is probably whether the software will run correctly after all this is done.

Containerization comes in to solve this problem. With containerization, different teams can work on different parts of the application independently. This allows faster software development as well as faster testing (of the code) for possible errors.

Organizations are creating more agile work environments to ensure more productivity in their workforce. DevOps, for example, brings software developers and IT operators together to provide continuous delivery and shorten the system development life-cycle.

Such teams need containers to solve application conflicts that may arise because of differences between these two environments.

Containers also enable microservices applications. The lightweight nature of containers means they take up less space and are easier to boot up.

Similarities between serverless computing and containers

Both containers and serverless are famous today because they take up infrastructure management to allow developers to focus their attention on creating and running their code.

This increases app development speed. The two technologies are suitable for component-based as well as microservices architectures. Deployment and scaling are quicker and more cost-effective when using these architectures compared to using classic monolithic architecture.

This is because component-based and microservices architectures allow developers to manipulate small parts of the app instead of the whole thing.

Differences between serverless and containers

Scalability

Scaling is slower in containers compared to serverless. With serverless, you leave the scaling work to the cloud provider. You do not have to configure anything, as the application team does the scaling work. With containers, you must define how you need scaling to be done in terms of load scaling, resource scaling, and much more.

Serverless has restrictions in terms of memory and size. However, there are no limits on how much you want to scale your application with container technology.

Ease of deployment

Deployment in serverless is so straightforward. You only need to write the code, and the vendor takes care of the rest. Infrastructure administration is not required, you just upload your functions, and you're ready.

Containers require Kubernetes and Dockerfile configurations. With this additional work, you'll need to build the image and move it to the registry.

Cost

Serverless is cheaper when compared to containers. You pay per function execution, meaning that you are not charged when your application is not running.

With containers, you pay for the space your containerized app takes on the vendor's space. The amount you pay keeps the container up and running all the time, including during idle time.

Longevity limitations

Serverless operates based on functions. These functions have a short lifespan of five minutes or less. With such a temporary nature, the execution of these functions means that the container running them lives only once. A shorter lifespan provides the agility that gives DevOps the flexibility and freedom to push apps into production.

Containers are always running, meaning that they continue to live even after their execution. This is important to leverage the benefit of caching.

Latency and start-up time

Serverless provides a decreased start-up time and latency when compared to containers. With serverless, apps are not running on a server, allowing you to run the code from anywhere. This also allows developers to use servers that are closer to the users. Such an arrangement means that requests no longer travel to far away severs, therefore reducing latency.

When to use serverless and when to use containers

Containers are suitable for enterprise applications requiring thorough debugging, scaling, and testing in different environments.Containers are also the best bet when you need to migrate legacy services or looking for flexibility.

Serverless handles simpler tasks with high computing power well. If you are looking for automatic scaling, a high speed of development, and a significantly reduced runtime, then serverless is the way to go.

A combination of the two models is a game-changer in the cloud computing arena. It allows you to run functions as serverless services in the cloud triggered by an app in a container.

Conclusion

Organizations are no longer thinking of serverless and containers as two competing technologies. Instead, they have realized that containers and serverless can work together by complementing each other's weaknesses. As such, they are appreciating the need to use these two architectures together.

Happy learning!