From SCALE13 session on 2015-02-22. Overview of Docker, swarm, and demonstration of docker-machine for easily bootstrapping container environments and swarm clusters.
Using Docker with OpenStack - Hands On!Adrian Otto
This document outlines an agenda for a hands-on Docker workshop. It includes 3 lessons and 3 hands-on labs. Lesson 1 provides an introduction to Docker concepts like Docker images, containers, and Dockerfiles. Lab 1 guides students on using docker-machine to spin up containers and get shells on Docker hosts. Lesson 2 covers writing Dockerfiles. Lab 2 involves writing Dockerfiles. Lesson 3 discusses linking and networking containers, while Lab 3 demonstrates linking containers on the same and different hosts.
OpenStack Magnum, Containers-as-a-Service for OpenStack clouds. This talk explains how Magnum fits among other OpenStack projects, and what abstracts are available in the Magnum API. Learn how Magnum is different from other Container management software.
Magnum is an OpenStack service that simplifies the deployment and management of container orchestration systems, such as Kubernetes and Docker Swarm, as first-class objects on OpenStack. It allows users to easily deploy and manage multiple container clusters on OpenStack that are isolated by tenant and project. Magnum uses Heat orchestration templates to deploy container clusters and integrates with other OpenStack services like Nova, Neutron, Keystone, and Cinder.
Slides from Docker Austin Meetup on 2016-08-04 with an overview of OpenStack Magnum, how we use it in Carina on private clouds, an overview of the Container Orchestration Engines Magnum supports, and an overview of how to manage your COEs with Magnum (v1). Includes a link to a video demo.
Cloud native applications are popular these days – applications that run in the cloud reliably und scale almost arbitrarily. They follow three key principles: they are built and composed as micro services. They are packaged and distributed in containers. The containers are executed dynamically in the cloud. Kubernetes is an open-source cluster manager for the automated deployment, scaling and management of cloud native applications. In this hands-on session we will introduce the core concepts of Kubernetes and then show how to build, package and operate a cloud native showcase application on top of Kubernetes step-by-step. Throughout this session we will be using an off-the-shelf MIDI controller to demonstrate and visualize the concepts and to remote control Kubernetes. This session has been presented at the ContainerCon Europe 2016 in Berlin. #qaware #cloudnativenerd #LinuxCon #ContainerCon
What's really the difference between a VM and a Container?Adrian Otto
Docker, Kubernetes, Mesos, and the container buzzword bingo game leaves us all asking this same question at some point. We know VMs are great, so why all this fuss now about containers? Are they the same thing, but better? This talk will go deep into the technical details of the fundamental differences between the technology, explaining in depth how each of them works, and where each of them shine and why businesses choose one over the other. You will also get a good sense of where the warts are too, so you know when to pick the right one (or the right combination of them) depending on what’s important for each of your various workloads.
The Nova driver for Docker has been maturing rapidly since its mainline removal in Icehouse. During the Juno cycle, substantial improvements have been made to the driver, and greater parity has been reached with other virtualization drivers. We will explore these improvements and what they mean to deployers. Eric will additionally showcase deployment scenarios for the deployment of OpenStack itself inside and underneath of Docker for powering traditional VM-based computing, storage, and other cloud services. Finally, users should expect a preview of the planned integration with the new OpenStack Containers Service effort to provide automation of advanced containers functionality and Docker-API semantics inside of an OpenStack cloud.
Note that the included Heat templates are NOT usable. See the linked Heat resources for viable templates and examples.
Docker allows building portable software that can run anywhere by packaging an application and its dependencies in a standardized unit called a container. Kubernetes is an open-source system for automating deployment, scaling, and management of containerized applications. It groups containers that make up an application into logical units for easy management and discovery. Kubernetes can replicate containers, provide load balancing, coordinate updates between containers, and ensure availability. Defining applications as Kubernetes resources allows them to be deployed and updated easily across a cluster.
Webinar container management in OpenStackCREATE-NET
This webinar covers the topics of Containers in OpenStack and, in particular it offers an overview of what containers are, LXC, Docker and Kubernetes. It also includes the topic of Containers in OpenStack and the specific examples of Nova docker, Murano and Magnum. In the final part there are live Demos about the elements covered earlier.
Scaling Docker Containers using Kubernetes and Azure Container ServiceBen Hall
This document discusses scaling Docker containers using Kubernetes and Azure Container Service. It begins with an introduction to containers and Docker, including how containers improve dependency and configuration management. It then demonstrates building and deploying containerized applications using Docker and discusses how to optimize Docker images. Finally, it introduces Kubernetes as a tool for orchestrating containers at scale and provides an example of deploying a containerized application on Kubernetes in Azure.
This document provides an introduction to Kubernetes and Container Network Interface (CNI). It begins with an introduction to the presenter and their background. It then discusses the differences between VMs and containers before explaining why Kubernetes is needed for container orchestration. The rest of the document details the architecture of Kubernetes, including the master node, worker nodes, pods, labels, replica sets, deployments, services, and how to build a Kubernetes cluster. It concludes with a brief introduction to CNI and a call for questions.
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 document provides an overview of using Kubernetes to scale microservices. It discusses the challenges of scaling, monitoring, and discovery for microservices. Kubernetes provides a solution to these challenges through its automation of deployment, scaling, and management of containerized applications. The document then describes Kubernetes architecture and components like the master, nodes, pods, services, deployments and secrets which allow Kubernetes to provide portability, self-healing and a declarative way to manage the desired state of applications.
This document provides an overview of the OpenStack Magnum project, which aims to provide Container as a Service (CaaS) functionality. It discusses alternatives like Nova, Heat, and Magnum's advantages. Key features of Magnum include simplified multi-tenant containers, integration with OpenStack services, and out-of-box support for Kubernetes, Docker Swarm, and Mesos. The architecture and operation of Magnum are explained, along with its integration points within OpenStack.
Practical Docker for OpenStack (Juno Summit - May 15th, 2014)Erica Windisch
This document discusses using Docker containers with OpenStack. It describes installing the Nova Docker compute driver plugin to enable launching and managing Docker containers via the OpenStack Nova API. The plugin allows spawning Docker containers from images in Glance and supports basic container operations. However, some Nova features like live migration and advanced Docker capabilities are not yet supported. Using Docker with Nova provides an alternative to Heat for container orchestration with OpenStack.
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.
This document provides an overview of Kubernetes 101. It begins with asking why Kubernetes is needed and provides a brief history of the project. It describes containers and container orchestration tools. It then covers the main components of Kubernetes architecture including pods, replica sets, deployments, services, and ingress. It provides examples of common Kubernetes manifest files and discusses basic Kubernetes primitives. It concludes with discussing DevOps practices after adopting Kubernetes and potential next steps to learn more advanced Kubernetes topics.
Kubespray and Ansible can be used to automate the installation of Kubernetes in a production-ready environment. Kubespray provides tools to configure highly available Kubernetes clusters across multiple Linux distributions. Ansible is an IT automation tool that can deploy software and configure systems. The document then provides a 6 step guide for installing Kubernetes on Ubuntu using kubeadm, including installing Docker, kubeadm, kubelet and kubectl, disabling swap, configuring system parameters, initializing the cluster with kubeadm, and joining nodes. It also briefly explains Kubernetes architecture including the master node, worker nodes, addons, CNI, CRI, CSI and key concepts like pods, deployments, networking,
This document provides an overview of Docker and Kubernetes concepts and demonstrates how to create and run Docker containers and Kubernetes pods and deployments. It begins with an introduction to virtual machines and containers before demonstrating how to build a Docker image and container. It then introduces Kubernetes concepts like masters, nodes, pods and deployments. The document walks through running example containers and pods using commands like docker run, kubectl run, kubectl get and kubectl delete. It also shows how to create pods and deployments from configuration files and set resource limits.
Clustree runs about 30 microservices on Google Kubernetes Engine (GKE) with ~280 pods across 15 nodes. They use Kubernetes for all stateless applications across environments and some stateful ones. Key aspects of their infrastructure include Docker, Elasticsearch, RabbitMQ, Prometheus for metrics, Fluentd and Logstash for logging to Elasticsearch, and Influxdb with Grafana. They have experienced some issues but find Kubernetes provides great benefits like easy rolling upgrades and declarative infrastructure.
Overview of kubernetes and its use as a DevOps cluster management framework.
Problems with deployment via kube-up.sh and improving kubernetes on AWS via custom cloud formation template.
A small introduction to get started on Kubernetes as a user. This explains the main concepts like pod, deployment and services and gives some hints to help you use kubectl command.
These slides were presented in Grenoble Docker meetup in November 2017.
In this overview presented to a gathering of directors for a large network equipment manufacturer, Chris discusses Docker, DevOps workflows, considerations for containers in production, and the extended Docker technology ecosystem.
Kubernetes Architecture and Introduction – Paris Kubernetes MeetupStefan Schimanski
The document provides an overview of Kubernetes architecture and introduces how to deploy Kubernetes clusters on different platforms like Mesosphere's DCOS, Google Container Engine, and Mesos/Docker. It discusses the core components of Kubernetes including the API server, scheduler, controller manager and kubelet. It also demonstrates how to interact with Kubernetes using kubectl and view cluster state.
This document provides steps to deploy a WordPress application with a MySQL database on Kubernetes. It demonstrates creating secrets for database credentials, persistent volumes for database storage, services for external access, and deploying the WordPress and MySQL containers. Various Kubernetes objects like deployments, services, secrets and persistent volumes are defined in YAML files and applied to set up the WordPress application on Kubernetes.
Kubernetes is a great tool to run (Docker) containers in a clustered production environment. When deploying often to production we need fully automated blue-green deployments, which makes it possible to deploy without any downtime. We also need to handle external HTTP requests and SSL offloading. This requires integration with a load balancer like Ha-Proxy. Another concern is (semi) auto scaling of the Kubernetes cluster itself when running in a cloud environment. E.g. partially scale down the cluster at night.
In this technical deep dive you will learn how to setup Kubernetes together with other open source components to achieve a production ready environment that takes code from git commit to production without downtime.
Orchestration tool roundup kubernetes vs. docker vs. heat vs. terra form vs...Nati Shalom
Video recording: https://www.youtube.com/watch?v=tGlIgUeoGz8
It’s no news that containers represent a portable unit of deployment, and OpenStack has proven an ideal environment for running container workloads. However, where it usually becomes more complex is that many times an application is often built out of multiple containers. What’s more, setting up a cluster of container images can be fairly cumbersome because you need to make one container aware of another and expose intimate details that are required for them to communicate which is not trivial especially if they’re not on the same host.
These scenarios have instigated the demand for some kind of orchestrator. The list of container orchestrators is growing fairly fast. This session will compare the different orchestation projects out there - from Heat to Kubernetes to TOSCA - and help you choose the right tool for the job.
Session link from teh summit: https://openstacksummitmay2015vancouver.sched.org/event/abd484e0dedcb9774edda1548ad47518#.VV5eh5NViko
Monitoring Docker at Scale - Docker San Francisco Meetup - August 11, 2015Datadog
In this session I showed building a multi-container app from beginning to end, using Docker, Docker-Machine, Docker-Compose and everything in between. You can even try it out yourself using the link in the deck to a repo on GitHub.
This document provides an introduction to Docker and discusses:
- The challenges of managing applications across different environments which Docker aims to solve through lightweight containers.
- An overview of Docker concepts including images, containers, the Docker workflow and networking.
- How Docker Compose allows defining and running multi-container applications and Docker Swarm enables orchestrating containers across a cluster.
- The open container ecosystem including the Open Container Initiative for standardization.
Webinar container management in OpenStackCREATE-NET
This webinar covers the topics of Containers in OpenStack and, in particular it offers an overview of what containers are, LXC, Docker and Kubernetes. It also includes the topic of Containers in OpenStack and the specific examples of Nova docker, Murano and Magnum. In the final part there are live Demos about the elements covered earlier.
Scaling Docker Containers using Kubernetes and Azure Container ServiceBen Hall
This document discusses scaling Docker containers using Kubernetes and Azure Container Service. It begins with an introduction to containers and Docker, including how containers improve dependency and configuration management. It then demonstrates building and deploying containerized applications using Docker and discusses how to optimize Docker images. Finally, it introduces Kubernetes as a tool for orchestrating containers at scale and provides an example of deploying a containerized application on Kubernetes in Azure.
This document provides an introduction to Kubernetes and Container Network Interface (CNI). It begins with an introduction to the presenter and their background. It then discusses the differences between VMs and containers before explaining why Kubernetes is needed for container orchestration. The rest of the document details the architecture of Kubernetes, including the master node, worker nodes, pods, labels, replica sets, deployments, services, and how to build a Kubernetes cluster. It concludes with a brief introduction to CNI and a call for questions.
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 document provides an overview of using Kubernetes to scale microservices. It discusses the challenges of scaling, monitoring, and discovery for microservices. Kubernetes provides a solution to these challenges through its automation of deployment, scaling, and management of containerized applications. The document then describes Kubernetes architecture and components like the master, nodes, pods, services, deployments and secrets which allow Kubernetes to provide portability, self-healing and a declarative way to manage the desired state of applications.
This document provides an overview of the OpenStack Magnum project, which aims to provide Container as a Service (CaaS) functionality. It discusses alternatives like Nova, Heat, and Magnum's advantages. Key features of Magnum include simplified multi-tenant containers, integration with OpenStack services, and out-of-box support for Kubernetes, Docker Swarm, and Mesos. The architecture and operation of Magnum are explained, along with its integration points within OpenStack.
Practical Docker for OpenStack (Juno Summit - May 15th, 2014)Erica Windisch
This document discusses using Docker containers with OpenStack. It describes installing the Nova Docker compute driver plugin to enable launching and managing Docker containers via the OpenStack Nova API. The plugin allows spawning Docker containers from images in Glance and supports basic container operations. However, some Nova features like live migration and advanced Docker capabilities are not yet supported. Using Docker with Nova provides an alternative to Heat for container orchestration with OpenStack.
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.
This document provides an overview of Kubernetes 101. It begins with asking why Kubernetes is needed and provides a brief history of the project. It describes containers and container orchestration tools. It then covers the main components of Kubernetes architecture including pods, replica sets, deployments, services, and ingress. It provides examples of common Kubernetes manifest files and discusses basic Kubernetes primitives. It concludes with discussing DevOps practices after adopting Kubernetes and potential next steps to learn more advanced Kubernetes topics.
Kubespray and Ansible can be used to automate the installation of Kubernetes in a production-ready environment. Kubespray provides tools to configure highly available Kubernetes clusters across multiple Linux distributions. Ansible is an IT automation tool that can deploy software and configure systems. The document then provides a 6 step guide for installing Kubernetes on Ubuntu using kubeadm, including installing Docker, kubeadm, kubelet and kubectl, disabling swap, configuring system parameters, initializing the cluster with kubeadm, and joining nodes. It also briefly explains Kubernetes architecture including the master node, worker nodes, addons, CNI, CRI, CSI and key concepts like pods, deployments, networking,
This document provides an overview of Docker and Kubernetes concepts and demonstrates how to create and run Docker containers and Kubernetes pods and deployments. It begins with an introduction to virtual machines and containers before demonstrating how to build a Docker image and container. It then introduces Kubernetes concepts like masters, nodes, pods and deployments. The document walks through running example containers and pods using commands like docker run, kubectl run, kubectl get and kubectl delete. It also shows how to create pods and deployments from configuration files and set resource limits.
Clustree runs about 30 microservices on Google Kubernetes Engine (GKE) with ~280 pods across 15 nodes. They use Kubernetes for all stateless applications across environments and some stateful ones. Key aspects of their infrastructure include Docker, Elasticsearch, RabbitMQ, Prometheus for metrics, Fluentd and Logstash for logging to Elasticsearch, and Influxdb with Grafana. They have experienced some issues but find Kubernetes provides great benefits like easy rolling upgrades and declarative infrastructure.
Overview of kubernetes and its use as a DevOps cluster management framework.
Problems with deployment via kube-up.sh and improving kubernetes on AWS via custom cloud formation template.
A small introduction to get started on Kubernetes as a user. This explains the main concepts like pod, deployment and services and gives some hints to help you use kubectl command.
These slides were presented in Grenoble Docker meetup in November 2017.
In this overview presented to a gathering of directors for a large network equipment manufacturer, Chris discusses Docker, DevOps workflows, considerations for containers in production, and the extended Docker technology ecosystem.
Kubernetes Architecture and Introduction – Paris Kubernetes MeetupStefan Schimanski
The document provides an overview of Kubernetes architecture and introduces how to deploy Kubernetes clusters on different platforms like Mesosphere's DCOS, Google Container Engine, and Mesos/Docker. It discusses the core components of Kubernetes including the API server, scheduler, controller manager and kubelet. It also demonstrates how to interact with Kubernetes using kubectl and view cluster state.
This document provides steps to deploy a WordPress application with a MySQL database on Kubernetes. It demonstrates creating secrets for database credentials, persistent volumes for database storage, services for external access, and deploying the WordPress and MySQL containers. Various Kubernetes objects like deployments, services, secrets and persistent volumes are defined in YAML files and applied to set up the WordPress application on Kubernetes.
Kubernetes is a great tool to run (Docker) containers in a clustered production environment. When deploying often to production we need fully automated blue-green deployments, which makes it possible to deploy without any downtime. We also need to handle external HTTP requests and SSL offloading. This requires integration with a load balancer like Ha-Proxy. Another concern is (semi) auto scaling of the Kubernetes cluster itself when running in a cloud environment. E.g. partially scale down the cluster at night.
In this technical deep dive you will learn how to setup Kubernetes together with other open source components to achieve a production ready environment that takes code from git commit to production without downtime.
Orchestration tool roundup kubernetes vs. docker vs. heat vs. terra form vs...Nati Shalom
Video recording: https://www.youtube.com/watch?v=tGlIgUeoGz8
It’s no news that containers represent a portable unit of deployment, and OpenStack has proven an ideal environment for running container workloads. However, where it usually becomes more complex is that many times an application is often built out of multiple containers. What’s more, setting up a cluster of container images can be fairly cumbersome because you need to make one container aware of another and expose intimate details that are required for them to communicate which is not trivial especially if they’re not on the same host.
These scenarios have instigated the demand for some kind of orchestrator. The list of container orchestrators is growing fairly fast. This session will compare the different orchestation projects out there - from Heat to Kubernetes to TOSCA - and help you choose the right tool for the job.
Session link from teh summit: https://openstacksummitmay2015vancouver.sched.org/event/abd484e0dedcb9774edda1548ad47518#.VV5eh5NViko
Monitoring Docker at Scale - Docker San Francisco Meetup - August 11, 2015Datadog
In this session I showed building a multi-container app from beginning to end, using Docker, Docker-Machine, Docker-Compose and everything in between. You can even try it out yourself using the link in the deck to a repo on GitHub.
This document provides an introduction to Docker and discusses:
- The challenges of managing applications across different environments which Docker aims to solve through lightweight containers.
- An overview of Docker concepts including images, containers, the Docker workflow and networking.
- How Docker Compose allows defining and running multi-container applications and Docker Swarm enables orchestrating containers across a cluster.
- The open container ecosystem including the Open Container Initiative for standardization.
Docker-Hanoi @DKT , Presentation about Docker EcosystemVan Phuc
The document provides an overview of Docker Platform and Ecosystem. It begins with introductions and background on Docker, explaining how Docker solves the problem of dependency hell and portability issues by allowing applications to run in isolated containers that package code and dependencies. It then discusses key components of Docker including Engine, Registry, Machine, Swarm, Compose and tools like Toolbox and Cloud. The document concludes with examples of using Docker for continuous integration pipelines and microservices architectures.
We talk about docker, what it is, why it matters, and how it can benefit us. This presentation is an introduction and delivered to local meetup in Indonesia.
Presentation on Pesantren Kilat Code Security
Tangerang, 2016-06-06
We talk about docker. What it is? Why it matters? and how it can benefit us?
This presentation is an introduction and delivered to local meetup in Indonesia.
This document provides an introduction to Docker, including why it was created, how it works, and its growing ecosystem. Docker allows applications to be packaged with all their dependencies and run consistently across any Linux server by using lightweight virtual containers rather than full virtual machines. It solves the problem of differences between development, testing, and production environments. The document outlines the technical details and advantages of Docker, examples of how companies are using it, and the growing support in tools and platforms.
What is this Docker and Microservice thing that everyone is talking about? A primer to Docker and Microservice and how the two concepts complement each other.
Write Once and REALLY Run Anywhere | OpenStack Summit HK 2013dotCloud
The document outlines the agenda for the OpenStack Summit in November 2013. The agenda includes sessions on Docker and its ecosystem, using Docker with OpenStack and Rackspace, and a cross-cloud deployment demo. Docker is presented as a solution for developing and deploying applications across multiple environments by encapsulating code and dependencies in portable containers. It can help eliminate inconsistencies between development, testing, and production environments.
The document outlines the agenda for the OpenStack Summit in November 2013, including presentations on Docker and its ecosystem, how Docker can be used with OpenStack and Rackspace, and a demonstration of cross-cloud application deployment using Docker. Docker is presented as a solution to the "matrix from hell" of running applications across different environments by providing lightweight, portable containers that can run anywhere regardless of the operating system. The summit aims to educate attendees on Docker and showcase its integration with OpenStack for simplified and efficient application deployment and management across multiple clouds.
Docker Seattle Meetup April 2015 - The Docker Orchestration Ecosystem on AzurePatrick Chanezon
This document discusses the Docker ecosystem and provides an overview of containerization technologies. It covers the history of containerization from mainframes in the 1960s to Docker in 2013. It discusses Docker's success due to cloud adoption, portability, and hybrid environments. It outlines the Docker ecosystem including Docker Engine, Docker Hub, Docker Machine, Docker Compose, Docker Swarm, and Kitematic. It also discusses companies in the Docker ecosystem like Docker Inc., CoreOS, Deis, Kubernetes, Cloud Foundry/IBM Bluemix, and others.
Docker containers have been making inroads into Windows and Azure world. Docker has now replaced the traditional Azure IaaS & PaaS services, offering superior container versions which are more responsive, cost effective, and agile. In this session for Charlotte Azure User Group, we will take an in-depth look at the intersection of Docker and Azure, and how Docker is empowering next gen Azure services.
Here's the link to CAG meetup for the event - https://www.meetup.com/Charlotte-Microsoft-Azure/events/fpftgmyxjbjb/
This document provides an introduction to Docker, including:
- Docker allows developers to package applications with all dependencies into standardized units called containers that can run on any infrastructure.
- Docker uses namespaces and control groups to provide isolation and security between containers while allowing for more efficient use of resources than virtual machines.
- The Docker architecture includes images which are templates for creating containers, a Dockerfile to automate image builds, and Docker Hub for sharing images.
- Kubernetes is an open-source platform for automating deployment and management of containerized applications across clusters of hosts.
Getting Started with MariaDB with DockerMariaDB plc
This document discusses deploying MariaDB databases with Docker from development to production. It recommends using Docker containers to encapsulate dependencies and isolate processes for easy deployment on-premise, in the cloud, or in hybrid environments. It highlights challenges like orchestration complexity and outlines requirements for data durability, self-discovery, self-healing, and application discovery of database clusters. It demonstrates building a Python/Flask app in Docker, deploying it to a Swarm cluster, and scaling the web tier behind HAProxy. It also shows deploying a 3-node Galera MariaDB cluster and 2-node MaxScale proxy for high availability.
The document provides an introduction to Docker, containers, and the problems they aim to solve. It discusses:
- Why Docker was created - to address the "matrix from hell" of developing and deploying applications across different environments and platforms.
- How Docker works at a high level, using lightweight containers that package code and dependencies to run consistently on any infrastructure.
- Some key Docker concepts like images, containers, the Dockerfile for building images, and common Docker commands.
- Benefits of Docker for developers and operations in simplifying deployment, reducing inconsistencies, and improving portability of applications.
Presentation about docker from Java User Group in Ostrava CZ (23th of November 2015). Presented by Martin Damovsky (@damovsky).
Demos are available at https://github.com/damovsky/jug-ostrava-docker
Docker New York Meetup May 2015 - The Docker Orchestration Ecosystem on Azure Patrick Chanezon
Docker Inc. provides products and services for managing containers. The Docker ecosystem includes open source tools for building, shipping, and running applications packaged into containers. Key components include Docker Engine for building containers, Docker Hub for sharing container images, and orchestration tools like Docker Swarm and Kubernetes for deploying containers across multiple hosts. Many companies are developing technologies that work with Docker to provide additional container management capabilities.
This document summarizes Docker, an open-source containerization platform. It discusses Docker's rapid growth since its launch 1 year prior, with over 370 contributors and 1 million downloads. Docker addresses the challenge of running applications across different environments by allowing applications and their dependencies to run in isolated containers that can be moved between servers. This eliminates inconsistencies between development and production environments. The document outlines benefits of Docker for developers, operations teams, and its role in microservices architecture.
This document provides an overview of Docker containers and developer workflows using Docker. It defines containers and images, and explains how Docker abstracts machine-specific settings to allow containers to run on different machines. Popular Docker images are listed, and benefits of using Docker for development are outlined. Common Docker commands are also described.
What's really the difference between a VM and a Container?Adrian Otto
Slides for my SCaLE 15x Presentation for 2017-03-04:
What's really the difference between a VM and a Container?
Docker, Kubernetes, Mesos, and the container buzzword bingo game leaves us all asking this same question at some point. We know VMs are great, so why all this fuss now about containers? Are they the same thing, but better? This talk will go deep into the technical details of the fundamental differences between the technology, explaining in depth how each of them works, and where each of them shine and why businesses choose one over the other. You will also get a good sense of where the warts are too, so you know when to pick the right one (or the right combination of them) depending on what’s important for each of your various workloads.
https://www.socallinuxexpo.org/scale/15x/presentations/whats-really-difference-between-vm-and-container
OpenStack is the prevailing open source cloud software. It includes numerous API services for programmatic management of all sorts of IaaS and SaaS services. VMs, Containers, Bare Metal, Multi-tenancy. Use this platform to strike the right balance between developer self-service to your infrastructure and a well defined platform for next generation containerized microservice applications that your IT department feels happy to support and your CFO would be happy to pay for.
This document provides an introduction to Docker presented by Adrian Otto. It defines Docker components like the Docker Engine (CLI and daemon), images, containers and registries. It explains how containers combine cgroups, namespaces and images. It demonstrates building images with Dockerfiles, committing container changes to new images, and the full container lifecycle. Finally, it lists Docker CLI commands and promises a demo of building/running containers.
7 Habits of Highly Effective ContirbutorsAdrian Otto
In this session, I share a formula for becoming a highly valued contributor to an Openstack community project. As the founder and PTL of both Solum and Magnum, I have had the freedom to try a bunch of things to run projects, and to on-board new contributors. You will learn all of the things you can do to quickly become a valued and respected member of your favorite project. This is proven, and guaranteed to work!
Adrian Otto from Rackspace will present "Docker 102", This includes a summary of Docker 101 as a refresher from the August session, and builds upon that by discussing who should use a registry, and what options are available for keeping them private. We will discuss best practices for keeping your production environments evergreen with updated operating system environments, library dependencies, and maintaining an immutable infrastructure.
Adrian Otto from Rackspace will present his perspective of "Docker 101", for Docker novices. Learn the difference between Dockerfiles, containers, running containers, terminated containers, container images, Docker Registry, and a demo of the Docker CLI that goes beyond what you learn from the online simulator.
Technology Trends in 2025: AI and Big Data AnalyticsInData Labs
At InData Labs, we have been keeping an ear to the ground, looking out for AI-enabled digital transformation trends coming our way in 2025. Our report will provide a look into the technology landscape of the future, including:
-Artificial Intelligence Market Overview
-Strategies for AI Adoption in 2025
-Anticipated drivers of AI adoption and transformative technologies
-Benefits of AI and Big data for your business
-Tips on how to prepare your business for innovation
-AI and data privacy: Strategies for securing data privacy in AI models, etc.
Download your free copy nowand implement the key findings to improve your business.
Dev Dives: Automate and orchestrate your processes with UiPath MaestroUiPathCommunity
This session is designed to equip developers with the skills needed to build mission-critical, end-to-end processes that seamlessly orchestrate agents, people, and robots.
📕 Here's what you can expect:
- Modeling: Build end-to-end processes using BPMN.
- Implementing: Integrate agentic tasks, RPA, APIs, and advanced decisioning into processes.
- Operating: Control process instances with rewind, replay, pause, and stop functions.
- Monitoring: Use dashboards and embedded analytics for real-time insights into process instances.
This webinar is a must-attend for developers looking to enhance their agentic automation skills and orchestrate robust, mission-critical processes.
👨🏫 Speaker:
Andrei Vintila, Principal Product Manager @UiPath
This session streamed live on April 29, 2025, 16:00 CET.
Check out all our upcoming Dev Dives sessions at https://community.uipath.com/dev-dives-automation-developer-2025/.
Quantum Computing Quick Research Guide by Arthur MorganArthur Morgan
This is a Quick Research Guide (QRG).
QRGs include the following:
- A brief, high-level overview of the QRG topic.
- A milestone timeline for the QRG topic.
- Links to various free online resource materials to provide a deeper dive into the QRG topic.
- Conclusion and a recommendation for at least two books available in the SJPL system on the QRG topic.
QRGs planned for the series:
- Artificial Intelligence QRG
- Quantum Computing QRG
- Big Data Analytics QRG
- Spacecraft Guidance, Navigation & Control QRG (coming 2026)
- UK Home Computing & The Birth of ARM QRG (coming 2027)
Any questions or comments?
- Please contact Arthur Morgan at [email protected].
100% human made.
AI and Data Privacy in 2025: Global TrendsInData Labs
In this infographic, we explore how businesses can implement effective governance frameworks to address AI data privacy. Understanding it is crucial for developing effective strategies that ensure compliance, safeguard customer trust, and leverage AI responsibly. Equip yourself with insights that can drive informed decision-making and position your organization for success in the future of data privacy.
This infographic contains:
-AI and data privacy: Key findings
-Statistics on AI data privacy in the today’s world
-Tips on how to overcome data privacy challenges
-Benefits of AI data security investments.
Keep up-to-date on how AI is reshaping privacy standards and what this entails for both individuals and organizations.
Andrew Marnell: Transforming Business Strategy Through Data-Driven InsightsAndrew Marnell
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The Evolution of Meme Coins A New Era for Digital Currency ppt.pdfAbi john
Analyze the growth of meme coins from mere online jokes to potential assets in the digital economy. Explore the community, culture, and utility as they elevate themselves to a new era in cryptocurrency.
What is Model Context Protocol(MCP) - The new technology for communication bw...Vishnu Singh Chundawat
The MCP (Model Context Protocol) is a framework designed to manage context and interaction within complex systems. This SlideShare presentation will provide a detailed overview of the MCP Model, its applications, and how it plays a crucial role in improving communication and decision-making in distributed systems. We will explore the key concepts behind the protocol, including the importance of context, data management, and how this model enhances system adaptability and responsiveness. Ideal for software developers, system architects, and IT professionals, this presentation will offer valuable insights into how the MCP Model can streamline workflows, improve efficiency, and create more intuitive systems for a wide range of use cases.
HCL Nomad Web – Best Practices and Managing Multiuser Environmentspanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-nomad-web-best-practices-and-managing-multiuser-environments/
HCL Nomad Web is heralded as the next generation of the HCL Notes client, offering numerous advantages such as eliminating the need for packaging, distribution, and installation. Nomad Web client upgrades will be installed “automatically” in the background. This significantly reduces the administrative footprint compared to traditional HCL Notes clients. However, troubleshooting issues in Nomad Web present unique challenges compared to the Notes client.
Join Christoph and Marc as they demonstrate how to simplify the troubleshooting process in HCL Nomad Web, ensuring a smoother and more efficient user experience.
In this webinar, we will explore effective strategies for diagnosing and resolving common problems in HCL Nomad Web, including
- Accessing the console
- Locating and interpreting log files
- Accessing the data folder within the browser’s cache (using OPFS)
- Understand the difference between single- and multi-user scenarios
- Utilizing Client Clocking
Designing Low-Latency Systems with Rust and ScyllaDB: An Architectural Deep DiveScyllaDB
Want to learn practical tips for designing systems that can scale efficiently without compromising speed?
Join us for a workshop where we’ll address these challenges head-on and explore how to architect low-latency systems using Rust. During this free interactive workshop oriented for developers, engineers, and architects, we’ll cover how Rust’s unique language features and the Tokio async runtime enable high-performance application development.
As you explore key principles of designing low-latency systems with Rust, you will learn how to:
- Create and compile a real-world app with Rust
- Connect the application to ScyllaDB (NoSQL data store)
- Negotiate tradeoffs related to data modeling and querying
- Manage and monitor the database for consistently low latencies
Generative Artificial Intelligence (GenAI) in BusinessDr. Tathagat Varma
My talk for the Indian School of Business (ISB) Emerging Leaders Program Cohort 9. In this talk, I discussed key issues around adoption of GenAI in business - benefits, opportunities and limitations. I also discussed how my research on Theory of Cognitive Chasms helps address some of these issues
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Linux Support for SMARC: How Toradex Empowers Embedded DevelopersToradex
Toradex brings robust Linux support to SMARC (Smart Mobility Architecture), ensuring high performance and long-term reliability for embedded applications. Here’s how:
• Optimized Torizon OS & Yocto Support – Toradex provides Torizon OS, a Debian-based easy-to-use platform, and Yocto BSPs for customized Linux images on SMARC modules.
• Seamless Integration with i.MX 8M Plus and i.MX 95 – Toradex SMARC solutions leverage NXP’s i.MX 8 M Plus and i.MX 95 SoCs, delivering power efficiency and AI-ready performance.
• Secure and Reliable – With Secure Boot, over-the-air (OTA) updates, and LTS kernel support, Toradex ensures industrial-grade security and longevity.
• Containerized Workflows for AI & IoT – Support for Docker, ROS, and real-time Linux enables scalable AI, ML, and IoT applications.
• Strong Ecosystem & Developer Support – Toradex offers comprehensive documentation, developer tools, and dedicated support, accelerating time-to-market.
With Toradex’s Linux support for SMARC, developers get a scalable, secure, and high-performance solution for industrial, medical, and AI-driven applications.
Do you have a specific project or application in mind where you're considering SMARC? We can help with Free Compatibility Check and help you with quick time-to-market
For more information: https://www.toradex.com/computer-on-modules/smarc-arm-family
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Precision in data labeling = Precision on the production floor.
2. Adrian Otto
•Principal Architect, Rackspace
•Chair of OpenStack Containers Team
•PTL of Magnum (Containers-as-a-Service for OpenStack)
•PTL of Solum (CI/CD for OpenStack)
•Co-Chair of OASIS CAMP TC (Cloud Standards)
7. Handling Existing Apps - Overview
• Containerize
– Use a Dockerfile to create a container image
– Store the image in a repository
• Run Docker on your cloud servers
• Back up your data to storage in the target cloud
• Load your app image from the repo to run it
• Load your data from your backup
9. I have a *lot* of
cloud servers
I have a *lot* of
data!
My app needs a
separate database
server
What’s Docker?
What’s an image
repository?
What’s a
Dockerfile?
11. What’s Docker?
• Allows for simplified management of containers
– CLI, API
– Example: docker run -p 80:80 web:latest
• Docker container is an amalgam
Cgroups Namespaces Image
Docker
Container
13. What’s an image repository?
• A place to store Docker container images
• Works just like a Git repository
– docker pull <name>
– docker push <name>[:<tag>]
14. I have a *lot* of cloud servers
•You need a utility with a resource scheduler
–Nova, Magnum, Kubernetes, Mesos, Swarm, etc.
•Treat application servers like cattle
–Create them from container images using automation
15. My app needs a separate database server
• Your database is also an app
• Bind mount your data volume from the host
–Example:
•docker run -v /data/my_app:/my_app –p 3306:3306 mysql:latest
• All prevailing orchestration systems allow you to define prerequisites.
• Using Heat
–Output of one resource can be the input to another.
16. Example HOT File with Dependency
resources:
server1:
type: OS::Nova::Server
depends_on: database_server
database_server:
type: OS::Trove::Instance
properties: …
17. I have a *lot* of data
•Don’t put “data” in containers
•Replicate your data in each target cloud
•Use prevailing techniques for incrementally streaming
changes to your replicas
•Bind mount your data volume(s) to your container(s)
18. Swarm - https://github.com/docker/swarm
• Exposes a cluster of Docker hosts as one virtual host
• Provides a Docker API
• Includes Resource Scheduling
– Filters: Constraint, Affinity, Port, Health
– Strategies: Bin Packing, Random
• A swarm agent runs on each Docker host
19. Swarm == Cool.
• Combined view of multiple cloud hosts
• Ability to selectively run containers on any of them
CLI Swarmd 2
1
N
21. How do I make cattle?
• Have a Dockerfile for each app
• Create Docker Images
• Deploy applications in containers
• Use scripted orchestration for app deployment
– Heat, Ansible, Chef, Puppet, etc.
• Use a centralized log scheme
– Logstash, Greylog, Kibana, etc.
22. Best Practice: Immutable Infrastructure
•Run the same artifacts everywhere
–Test
–Staging
–Production
•Rationale
–Less chance of environmental drift
–Helps you to bridge the gap from pets to cattle
24. •Do it by hand
•Use a VM image with a docker daemon in it
•docker-machine - https://github.com/docker/machine
– Start machines on Cloud Servers
•AWS, Azure, Digital Ocean, GCE, Hyper V, Softlayer, Rackspace, OpenStack,
VMWare vCloud Air, VMWare vSphere, Microsoft Windows (+caveat)
– Start machines on bare metal (OnMetal Flavors from Rackspace)
•But wait… there’s MORE!!!
24
Where do babies come from?
www.rackspace.com
25. $ export OS_REGION_NAME=IAD
$ export OS_USERNAME=jdoe
$ export OS_API_KEY=735590eaa1646e3ae79e6babbb7fd29f
$ docker-machine create -d rackspace demo
…
$ $(docker-machine env demo)
$ docker run -d centos:centos7 sleep 1d
…
873f3fa9e2924a4ef1de114628491af4026837f6cc2be8813f9515e532ad2c74
$
25
Use docker-machine to create VMs with Docker
www.rackspace.com