Kubernetes is a fantastic foundation for modern platforms, but as is the case when learning anything complicated, you need a safe playground that rewards experimentation and structured learning while minimizing the potential for any negative consequences.
Depending on a team’s experience, Kubernetes can either be a steep learning curve or refreshingly simple. Regardless of a team’s background, being able to rapidly and safely experiment within a Kubernetes playground is the key to becoming productive quickly.
If a development team is used to building and releasing applications via a platform-as-a-service (PaaS) such as Heroku or Cloud Foundry, the additional complexity that comes with Kubernetes can be troublesome. Gone are the simple abstractions, and deploying code is no longer an easy “git push heroku master.” I’ve heard some engineers use an analogy that moving from a PaaS to Kubernetes was like moving from traveling via train to driving yourself in a kit car that you have to assemble yourself from parts.
Teams with this type of experience need to be able to experiment with an application-ready Kubernetes cluster that they can quickly and repeatedly deploy services to and test and observe how user traffic will be handled. A key early goal here will be to establish the build pipeline deployment mechanisms and understand how the local developer experience maps to the remote deployment experience.
Our original Kubernetes tool list was so popular that we've curated another great list of tools to help you improve your functionality with the platform.
This article explains how you can leverage Kubernetes to reduce multi cloud complexities and improve stability, scalability, and velocity.
Get Hands-on experience on Kubernetes and the best comparison of Kubernetes over the DevOps at your place at Kubernetes training
Get Hands-on experience on Kubernetes and the best comparison of Kubernetes over the DevOps at your place at Kubernetes training
Microsoft announced the general availability of Bridge to Kubernetes, formerly known as Local Process with Kubernetes.