CCICI CIP 1.0 Testbed - Security access implementation and reference - v1.0

An Operator is an application that encodes the domain knowledge of the application and extends the Kubernetes API through custom resources. They enable users to create, configure, and manage their applications. Operators have been around for a while now, and that has allowed for patterns and best practices to be developed. In this talk, Lili will explain what operators are in the context of Kubernetes and present the different tools out there to create and maintain operators over time. She will end by demoing the building of an operator from scratch, and also using the helper tools available out there.

Kubernetes Helm makes application deployment easy, standardized and reusable. Use of Kubernetes Helm leads to better developer productivity, reduced Kubernetes deployment complexity and enhanced enterprise production readiness. Enterprises using Kubernetes Helm can speed up the adoption of cloud native applications. These applications can be sourced from open-source community provided repositories, or from an organization’s internal repository of customized application blueprints. Developers can use Kubernetes Helm as a vehicle for packaging their applications and sharing them with the Kubernetes community. Kubernetes Helm also allows software vendors to offer their containerized applications at “the push of a button.” Through a single command or a few mouse clicks, users can install Kubernetes apps for dev-test or production environments.

Sebastien Thomas, System Architect at Coyote Amerique, gave a presentation on operator frameworks. His talk covered how Operator SDK can be used to create Kubernetes Operators with Go.

Thanks to tools like kubeadm, Terraform or Ansible setting up a Kubernetes cluster on a dedicated environment is getting reachable, but what’s about setting up a bunch of cluster in multiple clouds in automatic way? This is still a challenge. Also if you want to do same in your own datacenter. In this talk we will take a look to the approach to orchestrate and manage a whole set of k8s cluster by the Cluster API project of kubernetes (a subproject of sig-cluster-lifecycle). The main idea behind it is to use the Kubernetes API itself to manage multiple clusters with there master and worker nodes in same way you would manage your PODs - define the needed resources and the responsible controller will take care for providing it. After an overview about the concepts of cluster API, I will show what’s needed to implement a cluster API conform machine class/deployment. There I will see that adding your own provider isn’t that hard as you may aspect. At the end of the day it just requires a simple interface to implement. The corresponding kubermatic controllers we implemented at Loodse are available as open source, so its possible to play around with it. A live demo will show how easy it is to spin up and maintain multiple Kubernetes cluster at different public and on-premise cloud providers over one managing cluster. A final wrap up will summarize the current state of the Cluster API project and the advantages of managing clusters as cattles instead of pets.

Helm is a package manager for Kubernetes. It helps streamline installing and managing applications. This session covers prerequisites for Helm, which include a basic understanding of containers and Kubernetes along with its architecture. It also covers the limitations that come with running deployments using the kubectl binary, Helm's architecture, templating with it and finally ends on a note highlighting the difference between versions 2 and 3.

** Kubernetes Certification Training: https://www.edureka.co/kubernetes-certification ** This Edureka tutorial on "Kubernetes Architecture" will give you an introduction to popular DevOps tool - Kubernetes, and will deep dive into Kubernetes Architecture and its working. The following topics are covered in this training session: 1. What is Kubernetes 2. Features of Kubernetes 3. Kubernetes Architecture and Its Components 4. Components of Master Node and Worker Node 5. ETCD 6. Network Setup Requirements ​DevOps Tutorial Blog Series: https://goo.gl/P0zAfF

In this session, we will discuss the architecture of a Kubernetes cluster. we will go through all the master and worker components of a kubernetes cluster. We will also discuss the basic terminology of Kubernetes cluster such as Pods, Deployments, Service etc. We will also cover networking inside Kuberneets. In the end, we will discuss options available for the setup of a Kubernetes cluster.

This document discusses building cloud-native applications with Kubernetes, Helm, and Kubeless. It introduces cloud-native concepts like containers and microservices. It then explains how Kubernetes provides container orchestration and Helm provides application packaging. Finally, it discusses how Kubeless enables serverless functionality on Kubernetes.

The document discusses Cluster API, an open source project that provides a Kubernetes cluster management API for provisioning and managing Kubernetes clusters across multiple cloud providers and on-premises. It introduces key Cluster API concepts like Machines, MachineClasses, and MachineSets that allow users to declaratively manage Kubernetes node lifecycles and scaling. The document also advertises an early bird discount code for an upcoming conference.

Operator pattern is pioneered by CoreOS, and it is embraced by the Kubernetes community. The Operator framework from CoreOS/Red Hat is also getting adoption. Operator Lifecycle Management (OLM) is part of the Operator framework. This talk walks you through testing Kubernetes operator with Operator Lifecycle Management (OLM).

The document provides an overview of the Aura framework: - Aura is Salesforce's framework for building UI components that are reusable, high performing, and support events. It allows for faster development through out-of-box components. - Components are the building blocks of Aura apps and can encapsulate HTML, CSS, JavaScript and other code. They represent reusable sections of the UI. - Aura uses an event-driven programming model where components can fire and handle events to respond to user interactions.

Kubernetes has become the defacto standard as a platform for container orchestration. Its ease of extending and many integrations has paved the way for a wide variety of data science and research tooling to be built on top of it. From all encompassing tools like Kubeflow that make it easy for researchers to build end-to-end Machine Learning pipelines to specific orchestration of analytics engines such as Spark; Kubernetes has made the deployment and management of these things easy. This presentation will showcase some of the larger research tools in the ecosystem and go into how Kubernetes has enabled this easy form of application management.

Kubernetes began as Google's internal container orchestration system called Borg and was open sourced as Kubernetes in 2014. It uses a declarative model where users describe their application components and infrastructure as code to manage the desired state. Key principles include being extensible through custom resources and controllers, meeting users where they are through integration with applications, and decoupling applications from infrastructure. Common extension points allow customizing authorization, scheduling, resources, and controllers. Operators help manage custom applications and Prometheus is a widely used monitoring operator. Best practices for day 2 operations focus on cluster design, application patterns, and security. A rich ecosystem of tools has grown around Kubernetes.

This document provides instructions for developing an API plug-in for CloudStack version 4.5 using SolidFire as an example. It outlines the steps to create a new Maven project called "abc123" by copying the existing "solidfire" project template. It describes updating files and dependencies to reference the new "abc123" project instead of "solidfire". The document then explains how to create the key classes needed to implement the plug-in, map it to API commands, and deploy the final JAR file. The goal is to extend CloudStack's API with new commands that can invoke functionality from a third-party product via the plug-in.

This document introduces Kubernetes operators and discusses how they can automate operations for stateful applications running on Kubernetes clusters. It explains that operators use custom resource definitions (CRDs) and custom controllers to make stateful applications declarative and enable automating tasks like backups, upgrades, and data redistribution. The operator pattern works by having a controller watch for the desired state defined by CRDs and take actions to maintain that state. The document demonstrates how operators can add new functionality to Kubernetes clusters and operate as "SRE as a service." It also introduces the Operator Framework for easily building new operators with the Operator SDK.