Everyone is talking about containers and serverless, but when should you use each in your projects?

Anyone who has worked with containers and orchestration much will tell you how much more complex they can make your application’s infrastructure. But the cloud keeps abstracting details away from us so we can focus on creating our solutions and less on the overhead tasks.

In fact, there is where the cloud-native technology called “serverless” that provides a PaaS (platform-as-a-service) option for creating highly scalable applications without having to think so much about the hosting details as you do with Docker and Kubernetes.

Serverless technologies and container technologies are just similar enough that I often see teams confused about which to use. In this blog post, I will walk you through some questions that will help you decide whether you should create your application using Kubernetes and Docker or a serverless technology like Azure Functions or AWS Lambda.

Containers and Orchestration

Containers and orchestrators allow you to build scalable cross-platform applications, but can be complex to manage. The primary technologies used for this today are Docker and Kubernetes. 

Docker

Docker is an open-source platform that enables the creation, deployment, and management of containerized applications. It provides a lightweight and portable runtime environment for applications by utilizing containerization technology. With Docker, developers can package their applications and dependencies into containers, which are isolated and can run consistently on any system that supports Docker.

Kubernetes

Kubernetes (often abbreviated as K8s) is an open-source container orchestration platform that automates the deployment, scaling, and management of containerized applications. It was originally developed by Google and is now maintained by the Cloud Native Computing Foundation (CNCF). Kubernetes provides a robust and scalable framework for managing containerized workloads across clusters of nodes.

Serverless

If you want a similar scalability to using containers and orchestration, but don’t want to have to think about all the infrastructure, then serverless might be a good fit for you. There are many serverless platforms, but by far the two most popular are AWS Lambda and Azure Functions. 

AWS Lambda

AWS Lambda is provided by Amazon Web Services (AWS). It allows you to run your code without provisioning or managing servers. Lambda supports multiple programming languages and integrates well with other AWS services, enabling event-driven, scalable, and cost-efficient applications.

Azure Functions

Azure Functions is the serverless computing offering provided by Microsoft Azure. It enables you to build and deploy event-driven functions that automatically scale based on demand. Azure Functions supports multiple programming languages and integrates seamlessly with other Azure services, making it suitable for developing cloud-native applications.

When to Use Serverless vs Containers

Below are several areas you should evaluate to decide if a serverless or containerized application architecture is better for your needs:

1. Workload Characteristics

Start by assessing the nature of your workload. If your application is event-driven, short-lived, and stateless, then serverless technologies like Azure Functions or AWS Lambda may be a good fit. 

On the other hand, if your workload is long-running, resource-intensive, or requires a custom runtime environment, containerization and orchestration might be more appropriate.

2. Scalability Requirements 

You should also consider the scalability needs of your application. Serverless platforms automatically scale based on incoming requests or events, allowing you to handle spikes in demand without manual intervention. If your workload experiences frequent fluctuations or unpredictable scaling requirements, serverless can be advantageous. 

However, if you have more predictable or consistent scaling patterns, containerization with orchestration platforms like Kubernetes can provide more control over scaling and resource allocation.

3. Operational Overhead

Consider the level of operational overhead you are willing to handle. Serverless platforms manage infrastructure and automatically handle tasks like scaling, patching, and fault tolerance. This can reduce operational burden, particularly for small teams or organizations with limited resources. If you prefer a hands-off approach to infrastructure management, serverless can be a good choice. 

Containerization and orchestration, however, require more operational effort to manage and maintain the container infrastructure, including scaling, networking, and upgrades.

4. Cost Considerations

Evaluate the cost implications. Serverless platforms offer a pay-per-use model, charging you only for the actual execution time of your functions or lambdas. This can be cost-effective for sporadic or low-traffic workloads. However, as your workload scales up or requires long-running execution, the cost may increase compared to a container-based approach where you have more control over resource allocation.

5. Ecosystem and Integration

Assess the ecosystem and integration options available for each technology. Serverless platforms provide a wide range of integrations, services, and managed offerings specific to their respective cloud providers. If you heavily rely on the services and integrations provided by a particular serverless platform, it may be beneficial to leverage that ecosystem. 

Containers and orchestration, on the other hand, offer a more agnostic approach, allowing you to deploy across different cloud providers or on-premises environments.

Summing Up

Azure Functions and AWS Lambda are advantageous for event-driven, stateless, and bursty workloads, offering faster development cycles, scalability, and cost optimization benefits. 

When dealing with long-running tasks, resource-intensive workloads, custom runtime requirements, advanced networking needs, or stateful processing, container-based solutions with Kubernetes or similar orchestration systems may be a better choice. 

It’s important to evaluate all of these trade-offs before deciding on the appropriate architecture for your project. If you aren’t sure where to get started, you can contract the experts at Trailhead for some guidance.