than a set of application-specific custom controllers. • the Operator monitors and analyzes the cluster, and based on a set of parameters, trigger a series of actions to achieve the desired state. https://coreos.com/operators/
in the Kubernetes API that stores a collection of API objects of a certain kind. ex: Pod. • A custom resource is an extension of the Kubernetes API that is not necessarily available on every Kubernetes cluster. • Kubernetes provides two ways to add custom resources to your cluster: • CRDs • API Aggregation(custom apiserver)
important feature called Custom Controllers. • It enables developers to extend and add new functionalities, replace existent ones (like replacing kube-proxy for instance). • And of course, automate administration tasks as if they were a native Kubernetes component.
project that provides developer and runtime Kubernetes tools, enabling you to accelerate the development of an Operator. • Operator SDK • Operator Lifecycle Management • Operator Metering https://github.com/operator-framework/operator-sdk
machine learning (ML) workflows on Kubernetes simple, portable and scalable. • Kubeflow’s goal is not to recreate other services, but to provide a straightforward way to deploy best-of-breed open-source systems for ML to diverse infrastructures. • Anywhere you are running Kubernetes, you should be able to run Kubeflow. Kubeflow
(laptop <-> ML rig <-> training cluster <-> production cluster). • Deploying and managing loosely-coupled microservices. • Scaling based on demand. The Kubeflow mission + https://www.kubeflow.org/
that developers need to create modern, source-centric, container-based, cloud- native applications. Knative “Developed in close partnership with Pivotal, IBM, Red Hat, and SAP, Knative pushes Kubernetes-based computing forward by providing the building blocks you need to build and deploy modern, container- based serverless applications.”
tasks such as: • Deploying a container. • Orchestrating source-to-URL workflows on Kubernetes. • Routing and managing traffic with blue/green deployment. • Automatic scaling and sizing workloads based on demand • Binding running services to eventing ecosystems. Knative Goals
Source-to-container build orchestration. • Serving: Request-driven compute that can scale to zero. • Eventing: Management and delivery of events. Knative Core Concepts
native containerized application orchestration and device management to hosts at Edge. • It is built upon Kubernetes and provides core infrastructure support for network, app. • Deployment and metadata sychronization between cloud and edge. https://kubeedge.io/
for getting work done on Kubernetes. Argo is implemented as a Kubernetes CRD (Custom Resource Definition). • Define workflows where each step in the workflow is a container. • Run CI/CD pipelines natively on Kubernetes without configuring complex software development products. https://argoproj.github.io/argo
allows domain experts to define application-specific data management workflows through Kubernetes API extensions. https://github.com/kanisterio/kanister
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