What is container orchestration?

Container orchestration tools like Google Kubernetes Engine (GKE) make it easier to deploy and run containerized applications and microservices. Container orchestrators typically apply their own methodologies and offer varying capabilities, but they all enable organizations to automatically coordinate, manage, and monitor containerized applications. 

Let’s take a look at how container orchestration works. 

Container orchestration uses declarative programming, meaning you define the desired output instead of describing the steps needed to make it happen. Developers write a configuration file that defines where container images are, how to establish and secure the network between containers, and provisions container storage and resources. Container orchestration tools use this file to achieve the requested end state automatically. 

When you deploy a new container, the tool or platform automatically schedules your containers and finds the most appropriate host for them based on the predetermined constraints or requirements defined in the configuration file, such as CPU, memory, proximity to other hosts, or even metadata. 

Once the containers are running, container orchestration tools automate life cycle management and operational tasks based on the container definition file, including:

• Provisioning and deployment
• Scaling containers up or down and load balancing
• Allocating resources between containers
• Moving containers to another host to ensure availability if there’s a shortage of resources or an unexpected outage
• Performance and health monitoring of the application
• Allocating resources between containers
• Service discovery

Container orchestration can be used in any computing environment that supports containers, from traditional on-premises servers to public, private, hybrid, and multicloud computing environments. 

Container orchestration platforms provide tools for automating container orchestration and offer the ability to install other open source technologies for event logging, monitoring, and analytics, such as Prometheus.

There are two types of container orchestration platforms: self-built or managed. 

Self-built container orchestrators give you complete control over customization and are typically built from scratch or leveraging an open source platform. However, self-built options also mean you take on the burden of managing and maintaining the platform. 

The most common open source container orchestration platform for cloud-native development is Kubernetes. Sometimes shortened to K8s, it is an open source container orchestration system originally developed by Google based on its internal cluster management system, Borg. Today, it’s considered the de facto choice for deploying and managing containers.

The other option is to use a managed platform or a Containers as a Service (CaaS) offering from a cloud provider, such as Google, Microsoft, Amazon, or IBM. With managed container orchestration platforms or CaaS, the cloud provider is responsible for managing installation and operations. As a result, you can simply consume the capabilities and focus on running your containerized applications. 

So, what are some examples of container orchestration, and why do we need to orchestrate containers in the first place? 

In modern development, containerization has become a primary technology for building cloud-native applications. Rather than large monolithic applications, developers can now use individual, loosely coupled components (commonly known as microservices) to compose applications. 

While containers are generally smaller, more efficient, and provide more portability, they do come with a caveat. The more containers you have, the harder it is to operate and manage them—a single application may contain hundreds or even thousands of individual containers that need to work together to deliver application functions. 

As the number of containerized applications continues to grow, managing them at scale is nearly impossible without the use of automation. This is where container orchestration comes in, performing critical life cycle management tasks in a fraction of the time. 

Let’s imagine that you have 50 containers that you need to upgrade. You could do everything manually, but how much time and effort would your team have to spend to get the job done? With container orchestration, you can write a configuration file, and the container orchestration tool will do everything for you. 

This is just one example of how container orchestration can help reduce operational workloads. Now, consider how long it would take to deploy, scale, and secure those same containers if everything is developed using different operating systems and languages. What about if you had to move them into different environments? 

A declarative approach can simplify numerous repetitive and predictable tasks required to keep containers running smoothly, such as resource allocation, replica management, and networking configurations.