We continue our discussion on Kubernetes framework.
Kubernetes can scale up or down the number of pods an instance supports. Functionality such as load-balancing, api gatekeeper, nginx controller and others are important to the applications. These routines are therefore provided out of box from the Kubernetes framework. The only observation here is that this is a constant feedback cycle. The feedback from the applications improves the offerings from the host.
An example of the above cycle can be seen with the help of operator sdk. Originally, the operators were meant to make it easy for applications to be deployed. While there are several tools to facilitate this, Kubernetes proposed the deployment via operators. While applications started out with one operator, today applications tend to write more than one operator. It is a recognition of this fact, that Kubernetes now has new features to support operator dedicated to metrics. These metrics operator are new even for the operator-sdk which as a tool enabled boilerplate code to be generated for most applications
The Kubernetes framework does not need to bundle up all the value additions from routines performed across applications. Instead it can pass through the data to hosts such as the public cloud and leverage the technologies of the host and the cloud. This techniques allows offloading health and performance monitoring to external layers which may already have significant acceptance and consistency
There are no new tools, plugins, add-ons or packages needed by the application when Kubernetes supports these routines. At the same time, applications can choose time to evaluate the necessary conditions for distribution of modules to parts. This frees up the applications and their packages. The packages are increasingly written to be hosted on their own pods.
Separation of the pods also improves modularity and reuse across application clients. This provides the advantage of isolation, troubleshooting and maintenance.
Kubernetes can scale up or down the number of pods an instance supports. Functionality such as load-balancing, api gatekeeper, nginx controller and others are important to the applications. These routines are therefore provided out of box from the Kubernetes framework. The only observation here is that this is a constant feedback cycle. The feedback from the applications improves the offerings from the host.
An example of the above cycle can be seen with the help of operator sdk. Originally, the operators were meant to make it easy for applications to be deployed. While there are several tools to facilitate this, Kubernetes proposed the deployment via operators. While applications started out with one operator, today applications tend to write more than one operator. It is a recognition of this fact, that Kubernetes now has new features to support operator dedicated to metrics. These metrics operator are new even for the operator-sdk which as a tool enabled boilerplate code to be generated for most applications
The Kubernetes framework does not need to bundle up all the value additions from routines performed across applications. Instead it can pass through the data to hosts such as the public cloud and leverage the technologies of the host and the cloud. This techniques allows offloading health and performance monitoring to external layers which may already have significant acceptance and consistency
There are no new tools, plugins, add-ons or packages needed by the application when Kubernetes supports these routines. At the same time, applications can choose time to evaluate the necessary conditions for distribution of modules to parts. This frees up the applications and their packages. The packages are increasingly written to be hosted on their own pods.
Separation of the pods also improves modularity and reuse across application clients. This provides the advantage of isolation, troubleshooting and maintenance.
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