Turbo-charge with Container Orchestration

Published 18.04.2021

Author Hrittik Roy

Categories Engineering

Managing containers while traffic increases or decreases in cost-effective ways round the clock sounds challenging and complex without tools. We, as cloud-native citizens, crave scalability and agility. But our containers going into production without the cloud-native philosophy doesn’t reflect us.

Developers have a particular overview of the system, and most of their time is utilized in writing code and making sure each microservice works with another one. Like the database container must connect to the backend container and share requested information securely. They focus on making things work and forget about numerous scenarios like a container failing in production or a surge in traffic.

Here operations come and make sure systems don’t lack behind the remaining areas.

In this post, we would dive a bit deeper into how to automate the managing and scheduling tasks under different edge scenarios to make reliable systems scale when required by using a key concept call container orchestration.

To understand orchestration as a beginner, read the following post:

Let’s dive in!

What does Container Orchestration mean?

I like to mention the definition that new relic uses:

Container orchestration is all about managing the lifecycles of containers, especially in large, dynamic environments.

– New Relic

This definition might sounds complex, and in simple terms, orchestration helps you deploy, monitor, allocate, and provision containers automatically into the production environment.

Why Container Orchestration?

Over the past several years, containers like Docker containers are everywhere. The containers have all the dependencies and code to be called portable. The containers/microservices are the backbones of modern applications.

Containerization of applications makes it easier to run and scale them in various environments, as Docker Engine is the conceptual “home” of the application.

However, running a production application means more than simply creating and running a container on Docker Engine. In production, you don’t have few services. You need container orchestration to account for the requirements of 1000s of microservices.

A non-containerized application means it will be manually installed and run or delivered via one virtual machine, like a LAMP server running on a VM (virtual machine).

But a containerized application with numerous microservices can’t be managed well with a CLI (command-line interface). You need automation tools to manage all of the containers from birth to death.

This type of container automation is what container orchestration is all about.

How does Container Orchestration work?

Declarative programming is the answer. By very nature, container orchestration tools are declarative. You only need to state what you want to happen, and the platform will make sure it happens.

For declarative definitions, orchestration tools rely on widely available formats such as YAML  (a recursive acronym for “YAML Ain’t Markup Language”) and JSON (JavaScript object notation). These configuration files tell you where to find the container image, how to set up networking, and what hardware resources should be reserved.

When you use a container orchestration tool to deploy a new container, the platform will manage container scheduling based on the best available host that meets any predefined constraints. Containers will be automatically rescheduled on a new host if resources on one host become limited.

So if you want 1000 NGINX containers, the tool would help you get them running without worrying about pulling an image from a local or private registry, creating a container from that image, or provisioning resources to start the container multiple times.

Container Orchestration Technology

Kubernetes by Google

It was developed by Google and then donated to the Cloud Native Computing Foundation (CNCF). The foundation is backed by Google, Amazon Web Services (AWS), Microsoft, IBM, Intel, Cisco, RedHat, and others.

Kubernetes container orchestration tool
Kubernetes Source: OVH

Kubernetes is one of the most popular tools out there and gaining more traction among DevOps professionals because it enables them to provide a self-service Platform-as-a-Service (PaaS) that abstracts the hardware layer for development teams. Kubernetes is also very lightweight. It can be deployed on Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform (GCP), or locally.

You can move workloads to different providers without completely rethinking your infrastructure or redesigning your applications, which helps you standardize on a platform and avoid vendor lock-in. But kubernetes or k8s is quite challenging to set up.

Mesos from Apache

Mesos is a bit advanced than Kubernetes, with a higher barrier to entry for a new user due to its complexity caused due to its modularity. The difficulty to set up mesos is reflected in its slow adoption as an on-premises solution by the major cloud providers, compared to Kubernetes’ rapid adoption.

apace mesos container orchestration tool
Apache Mesos Source: Medium

Twitter, Uber, and Paypal are just a few examples of organizations using mesos. Mesos’ lightweight interface allows it to scale up to 10,000 nodes (or more) with ease and allows frameworks built on top of it to evolve independently.

Docker Swarm by Docker

Swarm is Docker’s own fully integrated container orchestration tool. It’s simple and a good choice for Docker enthusiasts who want an easier and faster path to deploy containers without wanting to mess around with complex tools like k8s. The simplicity comes at the cost of lacking advanced auto-scaling features present in k8s and mesos.

docker swarm container orchestration tool
Docker Swarm Source: Medium

But that’s not a big deal for people trying to learn about orchestration tools.

Advantages of Container Orchestration

The advantages of orchestration could be broken down into few specific categories:


As discussed, you don’t need to deploy your containers running your services manually. Tools do that automatically which simplify the process for human.


Simplification permanently removes the chance of human error and ensures the application stays secure from threats.


The number of containers can be scaled up/down depending upon hardware resources and traffic. For example, if your container is getting a significantly higher load, K8s can help pop up more instances and redirect traffic to them.

Network Redistribution

If your containers are getting uneven traffic, your orchestration tool redistributes traffic to balance the load. You can say they act as a load balancer.


You can have multiple instances of a microservice running. If some service goes down, you can have your orchestration tool recreate an instance without you getting a call from your boss at midnight.


You can plug more tools like Prometheus into your container orchestration system. Now you have valuable insights, data logs and visualize your application in the form of service mesh. Service mesh helps you lay out all the microservices you have on a plane and see how they communicate with each other.

Final Thoughts

I hope you learned something new and exciting by the end of this post. I see a lot of people getting confused about where to start. If you’d like to get your hands dirty with the newly learned concepts, try picking one orchestration tool and understanding it.

And, if you need an optimal solution to satisfy your business needs, we are here to help with a custom solution. Feel free to have a discovery call with our engineering team.

Are we feeling exploratory? We have other awesome blogs to cover your cloud-native journey, and insightful posts delivered to you directly are always a newsletter away. Scroll down 😀

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