What is Container Orchestration? How Can it Scale Demand?

Unless you’re a software developer or system administrator, chances are you haven’t heard of the term ‘container orchestration.’ But that doesn’t mean it’s not important.

In fact, you’ve almost certainly enjoyed the benefits of container orchestration before, especially if you use cloud-service applications. Some of the most mainstream apps to use this technology include Netflix, Uber, Spotify, and social media giant Twitter.

So, if you don’t know what container orchestration is and how it can scale with your business, now’s a better time than ever to learn about it.

Looking for answers to those confusing questions? You’ve come to the right place—as this page will explain container orchestration in detail, how it works, benefits, and why you should be using it. Let’s dive in!

What is Container Orchestration?

Container orchestration is what lets software developers build highly complex programs out of many smaller, basic applications. It keeps all of these processes working together in sync across a cluster of machines, and lets you add more pieces to the puzzle should you ever want to expand your development.

It’s really useful for software-as-a-service applications, because users can pick and choose exactly what functionalities and features they want as part of their package (and remove the ones they don’t want).

The orchestration framework also has other benefits, like load balancing and resource optimization between multiple machines or instances of the same container—making it perfect for deployment of macro-scale cloud services. It also helps you stick to regulations on the handling of data and pass tests such as a compliance audit.

We’ll explore all of this and more in the following sections.

Free to use image from Unsplash

How Container Orchestration Works

Container orchestration isn’t too difficult to get your head around once you’re familiar with all the terminology, but some find it easier to understand with a metaphor:

Imagine that you want to watch a movie that’s been released in 10 different languages. Now, there’s no need for you to download all of those extra audio and subtitle files, when the English track is the only one that you’ll be watching.

So, the video platform has helpfully split the download file into 11 sections—1 for the video, and 10 separate audio folders for the languages. When it comes to downloading the film, it means you can just select which languages you want, rather than the whole thing. This results in a faster installation that takes up less storage space, making everything more efficient.

Now, let’s take this idea and apply it to the realm of computing.

Since the 1970s, software developers have been packing applications into small ‘containers’. Each container is meant to include everything needed to operate a piece of software from the moment you click Run, including:

• Code: All of the application’s source code and executable files are included in the container.
• Runtime: The container includes a runtime environment that ensures the code can execute, which works as a sort of bridge between the hardware of a computer and the software applications that run on it.
• System Tools: Within the runtime environment, system tools are included that ensure everything connects to other operations on the computer. For instance, it’s common to see pre-loaded tools for process management, network configuration, and system monitoring.
• Libraries: The runtime environment also includes custom code and routines in the form of libraries. This might help connect the software to an API, for example.
• Settings: Finally, containers contain configuration settings that define how the application behaves. For instance, environment variables and application parameters tell the program when it should launch, shut down, or send a message to another place on your computer.

So, that’s what containers are, and they exploded onto the scene in 2008 when Linux implemented container functionality into its kernel (the core part of LinuxOS). Their rise in popularity was largely thanks to the portability and accessibility of such a simple package of code—compared to its bulkier cousin, the virtual machine.

Soon enough, someone had the bright idea of letting developers combine multiple containers into one “orchestration framework”—and thus, the idea of container orchestration was born. By the way, the first platform to achieve this was Docker Swarm back in 2013, and the name “Docker containers” is now almost used synonymously with ‘containers.’

In practice, container orchestration allows developers to build highly bespoke and complex applications that can be deployed en masse. It’s like having a massive library of software applications, each available in multiple versions and configurations. Instead of having to download the entire library, you can pick and choose precisely what you need for a custom development to suit your needs.

Let’s explain this with an example. Imagine you’re building a communications platform that will let you video call anyone in the world, no matter the type of device they are using. You could create separate containers that handle how to conference call on Android, one for iPhones, one for Windows, Linux, MacOS, and so on.

When it comes to selling your software-as-a-service, your customers might not want to download all of those features. For instance, let’s say they want to use your app for internal calling between company laptops, which all run on WindowsOS. They could simply choose that module and have a perfectly fine application without all of the extra bells and whistles. And if at any point, they wanted to upgrade, it would be a simple case of installing the other files.

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Benefits of Container Orchestration: Why Do You Need it?

The primary benefit of container orchestration is that it’s efficient. It allows developers to copy-paste the building blocks of complex applications and easily cut out the parts they don’t need. This means more lightweight apps, fewer errors, less bandwidth used… you get the picture.

But it doesn’t stop there—container orchestration comes with several other key benefits that make it a very attractive option for software development:

• Scalability: Once it’s up and running, the containerized nature of the applications means you can easily install your software onto multiple devices—otherwise known as a cluster.
• Consistency: You can be sure that each device on your cluster will be running the same configuration. This means a lower chance of system errors and the ability to change settings on the entire cluster from one device.
• Reliability: Containers can be run on multiple devices at the same time, which means applications stay online if one fails. Load bearing capabilities share the computing power amongst the most well-suited devices.
• Self-Healing Capabilities: Orchestration frameworks automatically compare container health across different versions and replace failed containers. This means that errors often fix themselves without the need for human intervention.
• Faster Deployment: Container orchestration removes much of the burden from systems administrators when setting up new applications. Let’s say you work in a fast-paced environment like a sales call center. Having access to new product features quickly means your business can be more responsive to changing market conditions.

What Are Examples of Container Orchestration Tools?

Kubernetes

Kubernetes, also known as K8s, is an open-source container orchestration framework developed by Google in 2014. They named it after the Ancient Greek word for ‘pilot’, which gives you an idea of its general purpose. Anyway, Google donated the Kubernetes project to the Cloud Native Computing Foundation in 2015, and it thereafter became the most widely used platform of its kind.

It’s especially good at managing resource-intensive applications by spreading workloads across clusters of devices. This makes it an ideal pick for microservices-based applications that market their products as having ’99.9% uptime’ or some other promise to that effect.

Kubernetes is also well-suited for running ETL (Extract, Transform, Load) jobs in containers. For instance, a data processing pipeline can be orchestrated using Kubernetes, with containers responsible for extracting data from various sources, transforming it, and loading it into a central data warehouse.

It’s thanks to Kubernetes that you can enjoy apps like Netflix and Spotify—and how they (usually) don’t go offline! So, try to think of this process running in the background next time you settle down to watch a movie or listen to your latest groove.

Docker Swarm

Remember Docker? It’s the OG container orchestration platform built by Docker, Inc back in 2013, and it’s still widely used in software development to this day. That said, it plays a slightly

different role in the container ecosystem—catering more to a developmental environment.

Its user-friendly interface makes it relatively straightforward to containerize apps and test them out on a single machine (or small group of machines), as a single developer might want to do. But in terms of scalability, it lacks the advanced networking features of Kubernetes’ orchestration environment.

By all means use Docker to test out your program, but you may want to go for its feature-rich cousin Kubernetes when it’s time for production. That said, some mainstream apps like eBay, PayPal, and Shopify still use Docker Swarm, so it’s still a good fit for certain use cases in the world of cloud-native application development.

Final Thoughts: How Container Orchestration Scales Demand

To wrap up, container orchestration has become a truly essential tool for developing, deploying, and ultimately managing containerized applications. It’s especially critical for distributed environments where multiple instances of the same program are running on different machines, but they need to be kept in sync.

If you’ve read this far and decided that container orchestration is the right choice for you, remember that Kubernetes and Docker occupy slightly different roles in the containerization process. You should decide which one best fits your scalability needs and budget, as usually, developing a program in Docker will be the far simpler and cheaper task.