Containerizing a REST API and Deploying to Kubernetes

Kubernetes seems to be the biggest buzz word currently in the DevOps world. The Google designed container orchestrator based in their 10+ years of experience running production applications using containers seems to have positioned as the market leader. Open source, available in both Google Cloud and Azure container platforms or as a custom installation, it is ready to receive production loads. During this talk we will discover how does Kubernetes works, its architecture, what components compose a Kubernetes cluster. We will also learn what objects can a developer use to deploy its applications on a Kubernetes cluster. We will see a live demo where we will deploy an application and then introduce changes to it without any downtime.

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 microservices and containers. It provides an overview of microservices architecture compared to monolithic architecture, highlighting that microservices are composed of many small, independent services with separate deployments and databases. It then discusses containers and how Docker is used to package and run applications in isolated containers. Finally, it introduces Kubernetes as a container orchestration system to manage and scale multiple containerized applications across a cluster of machines.

The document discusses the architecture of Apache Stratos 4.1.0, including its load balancer architecture, use of Kubernetes resources, and composite application model. Stratos uses Kubernetes services to load balance traffic to pods, which contain Docker containers for each application instance. It also leverages Kubernetes to dynamically manage and scale applications deployed as composite applications.

Containerising your applications with Docker gets more and more attraction. While managing your Docker containers on your developer machine or on a single server is not a big hassle, it can get uncomfortable very quickly when you want to deploy your containers in a cluster, no matter if in the cloud or on premises. How do you provide high availability, scaling and monitoring? Fortunately there is a rapidly growing ecosystem around docker, and there are tools available which support you with this. In this session I want to introduce you to Kubernetes, the Docker orchestration tool started and open sourced by Google. Based on the experience with their data centers, Google uses some interesting declarative concepts like pods, replication controllers and services in Kubernetes, which I will explain to you. While Kubernetes still is a quite young project, it reached its first stable version this summer, thanks to many contributions by Red Hat, Microsoft, IBM and many more.

Kubernetes, Docker, CoreOS, and OpenStack for container workload management. No audio, but there are annotations to follow along with the workload. A video accompanies a Microservices Meetup talk that I presented on February 18, 2015 at https://www.youtube.com/watch?v=RfyIYhOzyPY Acknowledgements to Kelsey Hightower for the workflow that I used, and Google for the example application shown.

KubeCon 2015 talk about SoundCloud's container runtime environment history and a few highlighted reasons to migrate to Kubernetes.

This document provides an introduction and overview of Kubernetes for deploying and managing containerized applications at scale. It discusses Kubernetes' key features like self-healing, dynamic scaling, networking and efficient resource usage. It then demonstrates setting up a Kubernetes cluster on AWS and deploying a sample application using pods, deployments and services. While Kubernetes provides many benefits, the document notes it requires battle-testing to be production-ready and other topics like logging, monitoring and custom autoscaling solutions would need separate discussions.

Docker and Kubernetes provide tools for deploying and managing applications in containers. Docker allows packaging applications into containers that can be run on any Linux machine. Kubernetes provides a platform for automating deployment, scaling, and management of containerized applications. It groups related containers that make up an application into logical units called pods and provides mechanisms for service discovery, load balancing, and configuration management across a cluster. Many cloud providers now offer managed Kubernetes services to deploy and run containerized applications on their infrastructure.

This was a demo of deploying a Koop (https://koopjs.github.io) onto Kubernetes using a Docker container.

inovex Meetup: Let´s talk about docker! Speaker: Johannes Scheuermann, inovex GmbH Karlsruhe, 18.12.2014 Mehr Meetups: http://www.meetup.com/inovex-karlsruhe http://www.meetup.com/inovex-cologne http://www.meetup.com/inovex-munich

Docker's lightweight containers can quickly launch more containers when needed and then shut them down easily when they're no longer needed. Also it gets easier to make lots of small changes instead of huge, big bang updates that leads to reduced risk but more uptime. Saying that huge number of micro services leads to increase in complexity of the application deployment, orchestration and monitoring in production. Apache Stratos is a Platform as a Service (PaaS) integrated with Docker, CoreOS, Kubernetes gives more powerful single tool kit for container orchestration, monitoring, autoscaling and auto healing support. Smart policies and IaaS agnostic support provide capability of runs containers in almost every popular public and private clouds. This session included installing and deploying sample applications using Docker,CoreOS and Kubernetes and a demonstration of app deployment, provisioning, auto-scaling, and more.

Kubernetes can run application containers on clusters of physical or virtual machines. It can also do much more than that. Kubernetes satisfies a number of common needs of applications running in production, such as co-locating helper processes, mounting storage systems, distributing secrets, application health checking, replicating application instances, horizontal auto-scaling, load balancing, rolling updates, and resource monitoring. However, even though Kubernetes provides a lot of functionality, there are always new scenarios that would benefit from new features. Ad hoc orchestration that is acceptable initially often requires robust automation at scale. Application-specific workflows can be streamlined to accelerate developer velocity. This is why Kubernetes was also designed to serve as a platform for building an ecosystem of components and tools to make it easier to deploy, scale, and manage applications. The Kubernetes control plane is built upon the same APIs that are available to developers and users, implementing resilient control loops that continuously drive the current state towards the desired state. This design has enabled Apache Stratos and a number of other Platform as a Service and Continuous Integration and Deployment systems to build atop Kubernetes. This presentation introduces Kubernetes’s core primitives, shows how some of its better known features are built on them, and introduces some of the new capabilities that are being added.

Big companies like Google containerize theirs environments for easier maintaining, scaling, and reliability. This talk gives an introduction how to build such an environment and maintain applications written in distinct programming languages. The container orchestration is done with Kubernetes by Google and Docker containers. For mass deployment CoreOS is used.

Since last DockerCon, Kubernetes has been integrated into both the Desktop and Enterprise editions of the Docker Platform. In this deep dive session, we’ll showcase live demos and explore where Kubernetes fits in the architecture of both the Desktop and the Enterprise editions and which community tools make this integration possible. We’ll be covering topics ranging from hypervisor control, storage and networking all the way to the integration of a custom RBAC system, native Compose file support and providing a rich user interface for Kubernetes.

A Basic knowledge and Introduction to orchestration schema using kubernetes. Follow me on http://engeniir.com

This document discusses deploying WSO2 middleware on Kubernetes. It provides an overview of Kubernetes architecture and components, and how various Kubernetes features like pods, replication controllers, services, and overlay networking are used. It also describes WSO2 Docker images, Carbon reference architectures for Kubernetes, and the deployment workflow. Monitoring of Kubernetes cluster health using tools like cAdvisor, Heapster, Grafana and InfluxDB is also covered briefly.

Docker has extracted its core container runtime component into a new open source project called containerd. This will allow other container systems besides Docker to use containerd as their core runtime. Containerd provides the basic functionality to manage containers on Linux and Windows hosts and uses the OCI standard. Docker has been using containerd internally since 2016 and it will continue to use containerd going forward. Docker aims to donate containerd to a neutral open foundation in Q1 2017 to ensure its open governance.

We will setup Kubernetes using tectonic in AWS. More details here: http://blog.infracloud.io/setting-kubernetes-tectonic

Презентация про интеграцию GitLab, Prometheus, Grafana и Kubernetes

The presentation was made at the first Serverless Pune meetup on 4th Feb 2017 https://www.meetup.com/Serverless-Pune In the first Meetup, we covered most of the basics & a simple demos. Upcoming meetups will dive deeper into technical implementation and various real world use cases

Christian Posta is a principal middleware specialist and architect who has worked with large microservices architectures. He discusses why companies are moving to microservices and cloud platforms like Kubernetes and OpenShift. He covers characteristics of microservices like small autonomous teams and decentralized decision making. Posta also discusses breaking applications into independent services, shedding dependencies between teams, and using contracts and APIs for communication between services.

Kubernetes is an open-source platform for automating deployment, scaling, and operations of containerized applications. It provides tools to deploy containers across clusters of hosts, provide mechanisms for load-balancing, monitor health, and update containers. Kubernetes adds functionality to Docker by managing Docker hosts and containers at scale. It uses abstractions like pods, replica sets, deployments, services and ingresses to declaratively define application components and expose them using NodePorts, LoadBalancers or Ingresses. Users can interact with Kubernetes using kubectl to deploy and manage applications on the cluster.

RackN is a software company based in Austin, TX that provides a unified operational control platform for hybrid cloud and infrastructure. Their platform aims to help operations teams improve productivity and automate lifecycle management of complex technology stacks at scale across multiple platforms like Mesos, Kubernetes, OpenStack, and tools like Terraform. RackN uses intelligent template-based workflows to compose and simplify operations across physical, cloud and platform infrastructures and APIs.