Kubernetes Deployment Strategies

Kubernetes is a platform that enables the development, deployment, and management of applications that run on containers. Kubernetes provides a declarative approach to defining and managing application deployments, focusing on your application requirements and not worrying about the underlying infrastructure. In this post, we take an in-depth look at how you can use Kubernetes to provide continuous delivery for your applications.

How Kubernetes changed the DevOps ecosystem

Kubernetes has changed the face of DevOps. The open-source system has become a leading container orchestration platform and one of the most popular tools for managing distributed applications.

Kubernetes is built with collaboration in mind as an open-source community project. Its design makes it easy for developers to build and deploy applications using containers on any cloud infrastructure.

Kubernetes is also highly scalable and flexible, making it possible to run anywhere from a laptop to a large-scale cloud deployment without sacrificing performance or functionality.

The following are some of the ways Kubernetes changed DevOps:

Orchestration. Before Kubernetes came along, there was no single standard for orchestrating containers across different environments. But now, Kubernetes automates many of these processes through software that runs on top of a cluster of machines. This software allows you to define how your application will run in any environment, including public clouds like AWS or GCP or on-premises private clouds like OpenStack or VMware vSphere.

Containerization: Kubernetes was designed for managing containerized applications, which are becoming increasingly popular as enterprises move toward microservices architectures. Containers allow developers to package up their code and dependencies into an “image” that can run anywhere.

Continuous deployment: Continuous delivery (CD) is a software development practice that aims to automate producing software packages through frequent integration and continuous testing/debugging. By delivering new features as soon as they are ready, companies can ensure that their products remain competitive.

Automation: Automation reduces friction in processes, so workflows can be completed more quickly and efficiently, especially when deploying new applications in production environments. Kubernetes automation also allows teams to focus on other important aspects of development such as testing and quality assurance rather than manual tasks like deploying code manually.

Kubernetes deployment and the need for good strategies 

A Kubernetes deployment strategy is necessary to ensure that you get the most out of Kubernetes. This is why it’s important to understand what Kubernetes deployment strategy types there are, as well as how they’re used in practice. 

Monitoring and Arrays

Monitoring is one of the most important things in a Kubernetes default deployment strategy. You can find many articles online about how to monitor your Kubernetes cluster. But what if you need more than just monitoring? What if you need to get a deeper understanding of how your application is performing? In this case, we recommend using arrays instead of individual metrics.

Flows, Environments, and Deployments

In the monitoring world, we have flows and environments. A flow is a series of steps taken during its life cycle. For example, let’s say that you want to track an image from its creation date until it’s deleted from the registry server. You would create a flow with these steps: “Created on Date X,” “Updated on Date Y,” and “Deleted on Date Z.” You can then create several flows for different types of applications or images that help you understand your application lifecycle better. An environment is similar to a flow, but it has more flexibility — you can specify which type of action triggers it (created/updated/deleted) and which type of object triggers it.

System efficiency and analytics

Your Kubernetes cluster should be as efficient as possible. One of the most important things to consider when deploying containers on Kubernetes is how you will monitor your system. This includes monitoring CPU, memory, disk usage, etc. Make sure that you know what each container is doing so that if one container starts misbehaving, you can take action immediately.

Kubernetes deployment strategies  

Before we start building our deployment strategy, let’s look at some best practices for building applications on Kubernetes. 

First and foremost, know your application inside and out. What does it do? What does it expect from its environment? How does it behave when something goes wrong? Knowing these things will help us create a strategy that will work best for our application.

The second step is to define the application deployment lifecycle. The lifecycle can be broken down into stages like development, testing, staging, production, etc. Each stage has its own set of requirements for deploying applications on Kubernetes.

The third step is to build the desired state. In this stage, you need to decide which workloads should run on each node in your cluster based on their resource usage requirements or availability requirements (e.g., whether they should run as singleton or replicated pods).

The fourth step is to set up a system to create a deployment on demand. This can be done by using a combination of Terraform and Ansible or any other tool that you might find easy for Kubernetes multi-cluster management. You can also use Kubernetes itself to do this, but you prefer using another tool because it makes it easier to maintain and update your infrastructure in the future.

Kubernetes deployment strategy types 

Canary (rolling) – This is the most common deployment model for rolling out Kubernetes. In this model, most users are served by the new version while the remaining users are served by the old version (canary). Once you’re satisfied with how well your new version performs, you can switch all users over to it by gradually increasing the percentage until your updated codebase serves all users.  

Blue/Green (rolling) – This model involves two sets of pods: blue and green. One set serves all traffic while the other is updated behind the scenes. Once the update process is complete, traffic is switched over to the blue pod so that green can be updated at another time point in time.

Use an open-source orchestration platform to create an ‘Environment as a Service.’

A recommended strategy is to use an open-source orchestration platform such as Cloudify to create an Environment as a Service. This approach allows you to use multiple cloud providers and container services, including Kubernetes, Mesos (Marathon), and Docker Swarm.

Cloudify’s multi-cloud capabilities are based on its support for native integration with Amazon Web Services (AWS) API Gateway and Lambda functions via Amazon API Gateway SDK or AWS Lambda Python SDK; Google Cloud Platform Service Broker API; Microsoft Azure AppService API; or any other RESTful web service.


In conclusion, Kubernetes transformed the DevOps ecosystem. It’s one of the most popular open-source tools today and has become an integral part of DevOps. While Kubernetes is often hailed as the solution to all of your deployment woes, it requires a level of planning and thoughtfulness that should not be overlooked. With orchestration platforms taking advantage of its architectural benefits, businesses looking to successfully deploy their applications in production with minimal downtime are now even more options.

You may want to read about:

Kubernetes hybrid cloud

Kubernetes pitfalls and errors

Kubernetes management platform


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