When it comes to application architecture it is not uncommon for the DevOps team to be splitting hair over whether to go serverless or have a containerized solution. From a developer’s perspective, this debate is less about outright taking a party to preferred technology and more about finding the right tool for specific use cases. Is serverless a replacement for containers? Or can we use both the technologies with some degree of isolation? In this article, we will try to find answers to these questions but first things first, let’s get to the basics.
What is Serverless Computing?
In Serverless computing the cloud provider manages the execution of code by dynamically allocating resources. The term “serverless” implies the complexity of managing and scaling servers is abstracted away from the developer.
Serverless functions are usually small, lightweight programmatic functions with a single purpose. This modular approach allows developers to build applications that are scalable and flexible. Each function is independently deployable and is triggered by specific events, such as HTTP requests, file uploads, or database changes. The cloud provider instantaneously allocates resources to execute the function only when needed, and the function is idle when not in use. Most cloud providers offer serverless functions, which they may refer to as functions as a service (FaaS). The leading offerings are AWS Lambda, Azure Functions, and Google Cloud Functions.
As resource provisioning is handled by third-party cloud providers serverless leaves lesser control of the environment at the hands of the developers. Next, we will check about Containers that offer more ownership to the developers.
What are Containers?
Containers are a replacement for traditional VMs (Virtual Machines). They are lighter than VMs as they don’t include a separate OS but use the host OS Kernel. They are self-contained, lightweight virtualization technology that packages an application and its dependencies (libraries, binaries, configuration files) into a single executable unit. This assures developers that the software runs correctly when it is moved from one computing environment to another. As a result, containerization is a popular way to re-engineer an existing monolithic application into the cloud following a microservices-based architecture.
The isolation offered by containers allows each microservice to be developed, managed, and scaled independently. As a result, it is easier to develop an application and test it faster for all the possible errors.
Containers are often deployed to Kubernetes cluster. Deployment is done using services like Amazon’s Elastic Container Service (ECS) or Docker.
Serverless Vs. Container – Key Differences
State Persistency and Caching
Serverless functions are ephemeral or ‘short-lived’ which in turn, makes them stateless. It is easy to put stateless functions together and build something powerful. However, a major con of stateless functions is the unavailability of caching. If you invoke a function after it has died (they are as short-lived as up to 5 minutes or less) it will be a cold start.
Containers on the other hand are always up and running, offering caching benefits. While always being on standby may have cost implications, containers can be spun fast with none of the files to be created again leveraging caching.
Scalability
In serverless architecture, the backend resources are automatically provisioned and scaled by the cloud provider. You pay only for the time a resource was consumed.
Scaling in containers is a guessing game for the developer to estimate beforehand how many containers should be deployed. However, this can become challenging when there is a sudden rush of traffic leading to application crash.
Portability
Vendor lock-in is a real concern for serverless functions. You can easily become tied into a particular ecosystem because of the code needed to integrate with associated services. In contrast, it is easier to stay vendor-neutral using containers. A side effect of this neutrality is that containers support any language, while serverless applications are limited to a small selection of languages. This list of supported languages varies for each provider.
System Control
Dealing with functions such as AWS Lambda eliminates the infrastructure complexity. It significantly reduces the time to market which is not the case with containers. However, there is a long list of things that should not be done while using AWS Lambda.
Container-based microservice architecture imparts you full control over the individual as well as the whole system. This enables you to set policies, allocate, and manage resources. Plus, having fine-grained control over the security and migration services.
Testing
Testing is difficult in serverless-based web applications as it often becomes hard for developers to replicate the backend environment on a local environment.
Since containers run on the same platform where they are deployed, it’s relatively simple to test a container-based application before deploying it to production.
Maintenance
As it is clear from above, maintenance in serverless architecture rests with the cloud provider but in a containerized architecture developers take up the maintenance task.
Cost
In serverless your provider will bill you only for the time your serverless functions spend running. Also, as functions are short-lived in nature you incur some cost only when they are invoked and utilized. In contrast, you spin up container instances and keep at least some of them running 24/7, often leading to a higher cost.
Serverless Vs. Container – When to Choose What?
Serverless Computing: Developers can focus purely on code without worrying about infrastructure, but it might lack flexibility for certain applications.
Containers: They offer greater control over environments but demand more setup and maintenance.
Serverless Computing is an ideal solution for the following scenarios:
- When your traffic patterns fluctuate automatically, serverless computing not only manages these changes but also scales down to zero when there is no traffic.
- If you are concerned about the costs associated with maintaining servers and the resources your application consumes, serverless architecture is a great choice.
- If you prefer not to spend much time worrying about where your code is running and how it operates, serverless offers a streamlined approach.
- With serverless, you can develop and deploy websites and applications without the need to set up infrastructure. This means you can launch a fully functional app or website in just a few days.
- Serverless architecture also enables the creation of performance-enhancing image and video services for any application, allowing you to perform tasks such as dynamically resizing images or adjusting video transcoding for various target devices.
Containers are ideal for application deployment in the following scenarios:
- When you want to choose your preferred operating system and have complete control over the installed programming languages and runtime versions.
- If you need to use software that has specific version requirements, containers are an excellent starting point.
- If you’re willing to invest in larger, traditional servers for tasks such as web APIs, machine learning computations, and long-running processes, containers can be a cost-effective alternative.
- For developing new container-native applications.
- If you need to refactor a large and complex monolithic application, containers are better suited for managing such complexity.
- Some organizations utilize containers to migrate existing applications to more modern environments. Container orchestration tools like Kubernetes come with established best practices that simplify the management of large-scale container setups.
- While container orchestration platforms like Docker can help address issues with unpredictable traffic through auto-scaling, keep in mind that the process of starting or stopping containers may not be instantaneous.
Serverless and Containers Together
The choice between serverless and containers is not merely about selecting one over the other; rather, it can be beneficial to integrate both technologies. For instance, an organization may deploy its core services using containers while utilizing serverless functions for specific tasks like event handling or background processing. This hybrid approach allows businesses to leverage the strengths of both models—achieving agility with serverless while maintaining control and consistency with containers.
Conclusion
Ultimately, the decision hinges on the nature of the application being deployed. Serverless is well-suited for applications that can be broken down into smaller functions with unpredictable load patterns, while containers excel in scenarios requiring stable environments and long-running processes. As your organization continues to navigate this evolving landscape, understanding these differences will be crucial for optimizing your application deployment strategies in the cloud.
