Hello connection , who is reading this blog

First of all in this ,technical era we have many huge and worlds great technologies , which is creating a new world for humans where they do not need to work . They only need to instruct the technologies and it will work for us.

Just like other technologies here we have a new technology which is going to be very famous in this technical world which is KUBERNETES.

KUBERNETES is an open source for automating the containers ,computer systems , software , scaling and management. It was designed by GOOGLE and is now maintained by the CLOUD NATIVE GOOGLE FOUNDATION.

Basically it works with docker technology. Docker is an open platform for developing, shipping, and running applications. Docker enables you to separate your applications from your infrastructure so you can deliver software quickly. With Docker, you can manage your infrastructure in the same ways you manage your applications.


  • The ability to automatically place containers according to your resource requirements, without affecting availability.
  • Service discovery and load balancing: no need to use an external mechanism for service discovery as Kubernetes assigns containers their own IP addresses and a unique DNS name for a set of containers and can balance the load on them.
  • Planning: it is in charge of deciding in which node each container will run according to the resources it requires and other restrictions. It mixes critical and best-effort workloads to enhance resource utilization and savings.
  • Enable storage orchestration: automatically set up the storage system as a public cloud provider. Or an on-premise networked storage system such as NFS, iSCSI, Gluster, Ceph, Cinder and others.
  • Batch execution: in addition to services, Kubernetes can manage batch and IC workloads, replacing failed containers.
  • Configuration and secret management: sensitive information such as passwords or ssh keys are stored in Kubernetes hidden in ‘secrets’. Both the application’s configuration and secrets are deployed and updated without having to rebuild the image or expose sensitive information.
  • Self-repair: restart failed containers, replace and re-program them when nodes die. Also remove unresponsive containers and do not publish them until they are ready.
  • Execution of automated deployments where changes to the application or its configuration are progressively implemented, while its status is monitored. This ensures that you do not delete all your instances at once. If something goes wrong, Kubernetes will reverse the change.

Kubernetes and Docker are two of the words you hear most in conversations about DevOps today. Docker is a tool that allows you to contain and run applications, and Kubernetes provides a platform to orchestrate or manage these containers, since managing thousands of containers manually with Docker CLI is a very costly task.

Companies are looking to develop applications, and containers and open source are becoming very important, as they realize that Kubernetes is the first step to create modern scalable applications.

Multi-cloud flexibility: As more enterprises run on multi-cloud platforms, they benefit from Kubernetes, as it easily runs any application on any public cloud service or a combination of public and private clouds.

Faster time to market: Because Kubernetes can help the development team break down into smaller units to focus on single, targeted, smaller micro-services, these smaller teams tend to be more agile.

IT cost optimization: Kubernetes can help a company reduce infrastructure costs quite dramatically if it is operating on a large scale.

CASE STUDY — — — —


How OpenAI using Kubernetes in its company for better enhancement in buisness?

OpenAI is an AI research and deployment
company. Our mission is to ensure that artificial
general intelligence benefits all of humanity.


An artificial intelligence research lab, OpenAI needed infrastructure for deep learning that would allow experiments to be run either in the cloud or in its own data center, and to easily scale. Portability, speed, and cost were the main drivers.


OpenAI began running Kubernetes on top of AWS in 2016 , and in early 2017 migrated to Azure. OpenAI runs key experiments in fields including robotics and gaming both in Azure and in its own data centers, depending on which cluster has free capacity. “We use Kubernetes mainly as a batch scheduling system and rely on our autoscale to dynamically scale up and down our cluster,” says Christopher Berner, Head of Infrastructure. “This lets us significantly reduce costs for idle nodes, while still providing low latency and rapid iteration.”

OpenAI’s experiments take advantage of Kubernetes’ benefits, including portability. “Because Kubernetes provides a consistent API, we can move our research experiments very easily between clusters…”

OpenAI is also benefiting from other technologies in the CNCF cloud-native ecosystem. gRPC is used by many of its systems for communications between different services, and Prometheus is in place “as a debugging tool if things go wrong,” says Berner. “We actually haven’t had any real problems in our Kubernetes clusters recently, so I don’t think anyone has looked at our Prometheus monitoring in a while. If something breaks, it will be there.”

One of the things Berner continues to focus on is Kubernetes’ ability to scale, which is essential to deep learning experiments. OpenAI has been able to push one of its Kubernetes clusters on Azure up to more than 2,500 nodes. “I think we’ll probably hit the 5,000-machine number that Kubernetes has been tested at before too long,” says Berner, adding, “We’re definitely hiring if you’re excited about working on these things!”