Basic info about Kubernetes and Minikube setup

Here we see the trimmed down version of Kubernetes information. It doesn’t contain everything but the mostly interacted concepts. If you want a full information, you should refer to Kubernetes documentation.

Architecture

• Cluster: A Cluster is formed of Nodes for running containerised applications.

• Node: A Node is either a virtual or a physical machine that runs in Kubernetes Cluster.

• Pod: A Pod is a single instance of a process in Kubernetes Cluster. It contains one or many containers such as Docker.

Concepts

• Deployments manage their ReplicaSets.

• ReplicaSets manage their Pods.

• Pods manage their Containers.

• Containers contain your applications.

Responsibilities

• Ingress: An Ingress is responsible for handling HTTPS/HTTP requests before routing to Kubernetes Services. It makes sure that the Services are not directly exposed to outside.

• Deployment: A Deployment is responsible for running one or multiple replicas of an application and automatically replaces any instances that fail or become unresponsive. Deployments make sure that the application is always available to serve requests.

• ReplicaSet: A ReplicaSet is responsible for maintaining a stable set of Pods running at any given time. ReplicaSets make sure that a specified number of identical Pods are always up and running.

• Service: A Service is responsible for organising a deployed group of Pods in a Cluster. Services make sure that the Pods they manage have a name and unique Cluster IP.

• Pod: A Pod is responsible for running one or multiple containers within such as Docker. Pods represent a single instance of a running process in a Kubernetes Cluster.

• Volume: A Volume is a directory which is accessible by containers in a Pod. Similar to Docker volumes.

• ConfigMap: A ConfigMap is responsible for binding configuration files, environment variables, port numbers and last but not least some other configuration data to containers in Pods at runtime. ConfigMaps come in handy when keeping/sharing non-sensitive/plain configuration information.

• Secret: A Secret is responsible for storing and managing any sensitive information such as passwords, OAuth tokens, ssh keys etc.

• Namespace: A Namespace is responsible for organising Clusters into virtual sub-clusters. Namespaces come in hand when multiple teams or projects share the same Kubernetes Cluster. There can be many logically defined Namespaces in a Cluster and they all can communicate with each other.

#kubernetes

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50+ Useful Kubernetes Tools for 2020 - Part 2

Introduction

Last year, we provided a list of Kubernetes tools that proved so popular we have decided to curate another list of some useful additions for working with the platform—among which are many tools that we personally use here at Caylent. Check out the original tools list here in case you missed it.

According to a recent survey done by Stackrox, the dominance Kubernetes enjoys in the market continues to be reinforced, with 86% of respondents using it for container orchestration.

(State of Kubernetes and Container Security, 2020)

And as you can see below, more and more companies are jumping into containerization for their apps. If you’re among them, here are some tools to aid you going forward as Kubernetes continues its rapid growth.

(State of Kubernetes and Container Security, 2020)

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Kubernetes in the Cloud: Strategies for Effective Multi Cloud Implementations

Kubernetes is a highly popular container orchestration platform. Multi cloud is a strategy that leverages cloud resources from multiple vendors. Multi cloud strategies have become popular because they help prevent vendor lock-in and enable you to leverage a wide variety of cloud resources. However, multi cloud ecosystems are notoriously difficult to configure and maintain.

This article explains how you can leverage Kubernetes to reduce multi cloud complexities and improve stability, scalability, and velocity.

Kubernetes: Your Multi Cloud Strategy

Maintaining standardized application deployments becomes more challenging as your number of applications and the technologies they are based on increase. As environments, operating systems, and dependencies differ, management and operations require more effort and extensive documentation.

In the past, teams tried to get around these difficulties by creating isolated projects in the data center. Each project, including its configurations and requirements were managed independently. This required accurately predicting performance and the number of users before deployment and taking down applications to update operating systems or applications. There were many chances for error.

Kubernetes can provide an alternative to the old method, enabling teams to deploy applications independent of the environment in containers. This eliminates the need to create resource partitions and enables teams to operate infrastructure as a unified whole.

In particular, Kubernetes makes it easier to deploy a multi cloud strategy since it enables you to abstract away service differences. With Kubernetes deployments you can work from a consistent platform and optimize services and applications according to your business needs.

The Compelling Attributes of Multi Cloud Kubernetes

Multi cloud Kubernetes can provide multiple benefits beyond a single cloud deployment. Below are some of the most notable advantages.

Stability

In addition to the built-in scalability, fault tolerance, and auto-healing features of Kubernetes, multi cloud deployments can provide service redundancy. For example, you can mirror applications or split microservices across vendors. This reduces the risk of a vendor-related outage and enables you to create failovers.

#kubernetes #multicloud-strategy #kubernetes-cluster #kubernetes-top-story #kubernetes-cluster-install #kubernetes-explained #kubernetes-infrastructure #cloud

Microsoft Announces General Availability Of Bridge To Kubernetes

Recently, Microsoft announced the general availability of Bridge to Kubernetes, formerly known as Local Process with Kubernetes. It is an iterative development tool offered in Visual Studio and VS Code, which allows developers to write, test as well as debug microservice code on their development workstations while consuming dependencies and inheriting the existing configuration from a Kubernetes environment.

Nick Greenfield, Program Manager, Bridge to Kubernetes stated in an official blog post, “Bridge to Kubernetes is expanding support to any Kubernetes. Whether you’re connecting to your development cluster running in the cloud, or to your local Kubernetes cluster, Bridge to Kubernetes is available for your end-to-end debugging scenarios.”

Bridge to Kubernetes provides a number of compelling features. Some of them are mentioned below-

#news #bridge to kubernetes #developer tools #kubernetes #kubernetes platform #kubernetes tools #local process with kubernetes #microsoft

Did Google Open Sourcing Kubernetes Backfired?

Over the last few years, Kubernetes have become the de-facto standard for container orchestration and has also won the race against Docker for being the most loved platforms among developers. Released in 2014, Kubernetes has come a long way with currently being used across the entire cloudscape platforms. In fact, recent reports state that out of 109 tools to manage containers, 89% of them are leveraging Kubernetes versions.

Although inspired by Borg, Kubernetes, is an open-source project by Google, and has been donated to a vendor-neutral firm — The Cloud Native Computing Foundation. This could be attributed to Google’s vision of creating a platform that can be used by every firm of the world, including the large tech companies and can host multiple cloud platforms and data centres. The entire reason for handing over the control to CNCF is to develop the platform in the best interest of its users without vendor lock-in.

#opinions #google open source #google open source tools #google opening kubernetes #kubernetes #kubernetes platform #kubernetes tools #open source kubernetes backfired

Kubernetes: Monitoring, Reducing, and Optimizing Your Costs

Over the past two years at Magalix, we have focused on building our system, introducing new features, and scaling our infrastructure and microservices. During this time, we had a look at our Kubernetes clusters utilization and found it to be very low. We were paying for resources we didn’t use, so we started a cost-saving practice to increase cluster utilization, use the resources we already had and pay less to run our cluster.

In this article, I will discuss the top five techniques we used to better utilize our Kubernetes clusters on the cloud and eliminate wasted resources, thus saving money. In the end, we were able to cut our monthly bill by more than 50%!

• Applying Workload Right-Sizing
• Choosing The Right Worker Nodes
• Autoscaling Workloads
• Autoscaling Worker Nodes
• Purchasing Commitment/Saving Plans

#cloud-native #kubernetes #optimization #kubecost #kubernetes-cost-savings #kubernetes-cost-monitoring #kubernetes-reduce-cost #kubernetes-cost-analysis