This document provides an overview of Docker for developers. It discusses Docker's capabilities for solving portability issues, its advantages over traditional virtualization through operating system-level virtualization using containers that share the same kernel, and how it addresses challenges like slow development times and inefficient resource usage. It also covers Docker concepts like images, containers, registries, networking, security best practices using tools like Docker Bench Security, and cluster management using Docker Swarm.
Docker is an open platform for building, shipping and running containers. It provides lightweight virtualization that allows applications to run reliably from one computing environment to another. Some key benefits of Docker include guaranteed consistency through isolation of applications and their dependencies into lightweight executable packages called containers.
This document provides instructions on installing and using Docker on Linux (Ubuntu) and Windows. It discusses installing Docker on Ubuntu, basic Docker commands like images, ps, pull, run options for ports, volumes, and other commands. For Windows, it recommends using Docker Toolbox which includes Docker Machine, Engine, Compose and Kitematic GUI. It also covers installing the newer Docker for Windows which requires Windows 10 Pro/Enterprise with Hyper-V enabled.
Docker from A to Z, including Swarm and OCCSFrank Munz
This document provides an overview of Docker from A to Z including using Docker with Oracle Container Cloud Service. It discusses basics of Docker including how it provides isolation using Linux namespaces and cgroups. It compares Docker containers to virtual machines and covers Docker images, containers, limitations, networking, security concerns and suggestions. It also discusses using Docker with Oracle technologies including Dockerfiles on GitHub, the Oracle Container Registry, and Oracle Container Cloud Service.
This document summarizes a presentation about using Docker for development. It discusses installing Docker, running a "Hello World" Docker image, building a custom Python Docker image, and composing a more complex Docker application with PHP, MySQL, and Apache. The benefits of Docker like lightweight containers, easy environment setup, and scalability are highlighted. Some challenges with scaling and orchestration are also mentioned, along with solutions like Docker Swarm and Kubernetes.
Shipping Applications to Production in Containers with DockerJérôme Petazzoni
This document provides an overview and introduction to using Docker in production environments. It discusses how Docker can help with "solved" problems like installing, building, and distributing applications. It also covers important areas for production Docker usage, such as service discovery, orchestration, performance, configuration management, and sysadmin tasks. The document outlines various approaches in each area and notes that there are often multiple valid solutions to consider.
Docker is a tool that makes it easier to use Linux containers (LXC) to deploy applications. It allows applications to run consistently across servers by including dependencies within containers. Containers are more lightweight than virtual machines and use less resources. Docker containers start faster than VMs and allow for easy sharing of application components. The Docker registry stores container images and metadata for easy sharing between developers and production environments.
Docker has created enormous buzz in the last few years. Docker is a open-source software containerization platform. It provides an ability to package software into standardised units on Docker for software development. In this hands-on introductory session, I introduce the concept of containers, provide an overview of Docker, and take the participants through the steps for installing Docker. The main session involves using Docker CLI (Command Line Interface) - all the concepts such as images, managing containers, and getting useful work done is illustrated step-by-step by running commands.
This document summarizes Docker security features as of release 1.12. It discusses key security modules like namespaces, cgroups, capabilities, seccomp, AppArmor/SELinux that provide access control and isolation in Docker containers. It also covers multi-tenant security, image signing, TLS for daemon access, and best practices like using official images and regular updates.
The ABC of Docker: The Absolute Best Compendium of DockerAniekan Akpaffiong
Containers provide a lightweight virtualization approach compared to virtual machines. Containers share the host operating system kernel and isolate applications at the process level, while virtual machines run a full guest operating system and require hypervisor software. Containers have a smaller footprint and overhead than virtual machines since they share resources more efficiently. Both containers and virtual machines provide portability and isolation benefits for applications.
Docker is a system for running applications in isolated containers. It addresses issues with traditional virtual machines by providing lightweight containers that share resources and allow applications to run consistently across different environments. Docker eliminates inconsistencies in development, testing and production environments. It allows applications and their dependencies to be packaged into a standardized unit called a container that can run on any Linux server. This makes applications highly portable and improves efficiency across the entire development lifecycle.
Real-World Docker: 10 Things We've Learned RightScale
Docker has taken the world of software by storm, offering the promise of a portable way to build and ship software - including software running in the cloud. The RightScale development team has been diving into Docker for several projects, and we'll share our lessons learned on using Docker for our cloud-based applications.
Docker is an open platform for developing, shipping, and running applications. It allows separating applications from infrastructure and treating infrastructure like code. Docker provides lightweight containers that package code and dependencies together. The Docker architecture includes images that act as templates for containers, a client-server model with a daemon, and registries for storing images. Key components that enable containers are namespaces, cgroups, and capabilities. The Docker ecosystem includes services like Docker Hub, Docker Swarm for clustering, and Docker Compose for orchestration.
Introduction to docker. Docker is open source framework that provides "container virtualization". This does not need hypervisor rather works directly with Kernel. It needs x64 Linux and kernel 3.8+ to provide virtualization
MIT Licensed - Reuse freely, but attribute "Hamilton Turner"
An introduction to the Docker container engine. Focuses on how to use Docker and implications of Docker for Cloud-based services. Shows multiple examples of rapidly starting complex environments using Docker. Very minor discussion on how Docker works technically.
Presentation source is available at https://github.com/hamiltont/intro-to-docker
Docker is a system for running applications securely isolated in a container to provide a consistent deployment environment. The document introduces Docker, discusses the challenges of deploying applications ("the matrix from hell"), and how Docker addresses these challenges by allowing applications and their dependencies to be packaged into lightweight executable containers that can run on any infrastructure. It also summarizes key Docker tools like Docker Compose for defining and running multi-container apps, Docker Machine for provisioning remote Docker hosts in various clouds, and Docker Swarm for clustering Docker hosts.
This is the notes of a presentation I gave to our IT dept., people who know a lot about VMs! They include a description of differences betwen a VM and a container, why would someone would want to use Docker, how it works (at 30,000 feet), some hints of what are the hub and orchestration, some Dockerfiles examples: jenkins slave, jenkins master, sinopia server, etc. and finally some new features Docker is going to propose in the future and how I intend to mix Configuration tools, such as Ansible, and Docker.
Java Developer Intro to Environment Management with Vagrant, Puppet, and Dock...Lucas Jellema
Creating and managing environments for development and R&D activities can be cumbersome. Quickly spinning up databases and web servers, using physical resources in a smart way, installing application components, and having all the elements talk to each other can take a lot of time. This session takes you by the hand and introduces you to Vagrant and Oracle VM VirtualBox for quickly provisioning VMs in which Docker containers run platform components, applications, and microservices—all set up by use of Puppet and interacting with Git(Hub). You’ll start from zero on your laptop and end with both local and public cloud environments in which to develop, test, and run various types of applications. Lean governance and evolution of the environments are discussed too.
1. This document discusses Microsoft and Docker, including how to deploy Docker containers on Azure. It provides an overview of Azure and Microsoft's support for open source software.
2. Methods for deploying Docker containers on Azure include using a Docker VM extension template, Docker Machine with the Azure driver, and Azure Container Service.
3. The document also covers upcoming integrations between Docker and Windows, such as Windows Server containers, Hyper-V containers, and the Docker beta for Windows developers.
Containers, Microsoft and DevOps: What is Microsoft Doing About All This Anyw...Gil Isaacs
This document discusses a sample containerized application on Azure using DevOps tools and techniques. It describes how the sample application called "The Geek Quiz" is containerized using Docker and deployed to Azure virtual machines. The application deployment is automated using tools like Azure Resource Manager templates, Docker Compose, Azure Automation, and continuous integration/deployment. It also discusses how DevOps practices like infrastructure as code, continuous delivery, and monitoring can be used with containers and Azure.
ContainerDays NYC 2016: "Containers in Azure: Understanding the Microsoft Con...DynamicInfraDays
This document discusses Microsoft's container ecosystem. It covers Docker for Windows, Windows containers, Azure Container Service (ACS), and running .NET on Linux. Docker for Windows allows running Docker natively on Windows using Hyper-V. Windows containers leverage the Windows kernel for isolation using namespaces and control groups. ACS simplifies deploying Docker clusters to Azure. .NET Core allows developing .NET applications on Linux. The document also briefly mentions Docker Datacenter and Enterprise DC/OS as enterprise container solutions.
Azure supports both Linux and Windows containers that allow for efficient isolation and resource sharing. It provides container services and tools including Docker images, Kubernetes, Mesos and Docker support to deploy and manage containers at cloud scale. Azure's container infrastructure can be used to build applications with microservices architecture and provide agility and cost control.
SplunkSummit 2015 - Splunk User Behavioral AnalyticsSplunk
The document discusses Splunk User Behavior Analytics (UBA) and its capabilities for detecting advanced cyber attacks and insider threats through behavioral threat detection using machine learning. It notes that traditional threat detection focuses only on known threats, while UBA aims to detect unknown threats through automated security analytics and anomaly detection based on establishing user and entity baselines and identifying deviations from normal behavior. The document provides examples of UBA use cases and the types of data sources it can integrate to perform threat detection and security analytics.
Docker provides a new, powerful way of prototyping, testing and deploying applications on cloud-based infrastructures. In this seminar we delve into the concept of Docker containers without requiring any previous knowledge from the audience.
Splunk as a_big_data_platform_for_developers_spring_one2gxDamien Dallimore
Splunk is a platform for collecting, analyzing, and visualizing machine data. It provides real-time search and reporting across IT systems and infrastructure. Splunk indexes data from various sources without needing predefined schemas, and scales to handle large volumes of data from thousands of systems. The presentation covers an overview of the Splunk platform and how it can be used by developers, including custom visualizations, the Java SDK, and integrations with Spring applications.
The document summarizes a presentation about containers in Azure. It introduces Docker and Kubernetes as tools for running open source applications on Azure. It notes shortcomings of traditional virtual servers, such as difficulty scaling and versioning applications. Docker is presented as a way to package code and dependencies, while Kubernetes provides container orchestration for tasks like scheduling and updating containers. The presentation demonstrates using OpenShift on APPUiO, a managed container platform, as an alternative to running containers directly on Azure.
Dockerizing Windows Server Applications by Ender Barillas and Taylor BrownDocker, Inc.
A session covering the container workflow from the developers inner loop, CI/CD, to deployment in a container orchestration solution. We'll cover Visual Studio Code from a Mac, Visual Studio Code from Windows with Bash and Visual Studio as an in-container local development environment targeting both Windows and Linux Containers. We'll walk through CI, Validation and CD to the Azure Container Service running Docker Swarm as one example of how you can convert your existing config as code and VM deployments to the containerized workflows startups and early adopter enterprises are using today.
Docker Online Meetup #29: Docker Networking is Now GA Docker, Inc.
At DockerCon in June, we first announced experimental support for Docker Networking. As of the 1.9 release of Docker, we are excited to announce that Docker Networking is generally available to define how your Dockerized apps connect together.
Docker Networking is a feature of Docker Engine that allows you to create virtual networks and attach containers to them so you can create the network topology that is right for your application. The networked containers can even span multiple hosts, so you don’t have to worry about what host your container lands on. They can seamlessly communicate with each other wherever they are - thus enabling true distributed applications.
And Networking is pluggable, so you can use any third-party networking driver to power your networks without having to make any changes to your application.
Read more: http://blog.docker.com/2015/11/docker-multi-host-networking-ga/
Tackling complexity in giant systems: approaches from several cloud providersPatrick Chanezon
Systems architecture evolve in cycles every 15-20 years, oscillating between centralization and decentralization, but growing in size and complexity. The last cycle shifted from vertical to horizontal scalability for hardware, applications and data platforms. This talk will describe approaches used by some of the companies who pioneered cloud platforms, Google, Microsoft, Amazon, Netflix & VMware, to tackle complexity when building these giant distributed systems.
This talk was presented at JFokus 2014.
https://www.jfokus.se/jfokus/talks.jsp#Tacklingcomplexityin
Traditional virtualization technologies have been used by cloud infrastructure providers for many years in providing isolated environments for hosting applications. These technologies make use of full-blown operating system images for creating virtual machines (VMs). According to this architecture, each VM needs its own guest operating system to run application processes. More recently, with the introduction of the Docker project, the Linux Container (LXC) virtualization technology became popular and attracted the attention. Unlike VMs, containers do not need a dedicated guest operating system for providing OS-level isolation, rather they can provide the same level of isolation on top of a single operating system instance.
An enterprise application may need to run a server cluster to handle high request volumes. Running an entire server cluster on Docker containers, on a single Docker host could introduce the risk of single point of failure. Google started a project called Kubernetes to solve this problem. Kubernetes provides a cluster of Docker hosts for managing Docker containers in a clustered environment. It provides an API on top of Docker API for managing docker containers on multiple Docker hosts with many more features.
This document provides an introduction to Docker. It discusses why Docker is useful for isolation, being lightweight, simplicity, workflow, and community. It describes the Docker engine, daemon, and CLI. It explains how Docker Hub provides image storage and automated builds. It outlines the Docker installation process and common workflows like finding images, pulling, running, stopping, and removing containers and images. It promotes Docker for building local images and using host volumes.
Docker San Francisco Meetup April 2015 - The Docker Orchestration Ecosystem o...Patrick Chanezon
The document discusses the Docker ecosystem including:
- The history and components of Docker including the Docker Engine, Hub, Machine, Compose, and Swarm.
- How Docker provides isolation using Linux kernel features like namespaces and cgroups.
- Other projects in the Docker ecosystem like Weave, Flocker, and Powerstrip.
- Orchestration tools like Docker Swarm and Kubernetes that manage Docker containers across multiple hosts.
- Platforms that are built on Docker like CoreOS, Deis, Cloud Foundry, and IBM Bluemix.
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 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.
Docker Devoxx UK - Never mind the bollocks here's the Linux ContainersPatrick Chanezon
This document summarizes the history and current state of containerization technologies. It discusses early implementations in mainframes and virtualization in the 1990s. It then covers the rise of Docker in 2013 which enabled "write once, run anywhere" for applications. The document also outlines the Docker platform and tools like Docker Hub, Docker Machine, and Docker Compose. It discusses orchestration technologies like Docker Swarm and Kubernetes. Finally, it briefly mentions other container-focused companies and platforms like Tutum, Flocker, and Weave.
This document discusses Docker and containerization. It provides a history of containerization from the 1960s to present day. It explains Docker's success in recent years due to factors like cloud adoption, portability across platforms, and the rise of hybrid cloud environments. The document outlines Docker's products and tools like the Docker Engine, Docker Hub, Docker Machine, Docker Compose, Docker Swarm, and Kitematic. It also discusses concepts like namespaces and cgroups that enable isolation in Linux containers. Examples are given of using Docker for developers and deploying applications on Docker.
Docker Azure Friday OSS March 2017 - Developing and deploying Java & Linux on...Patrick Chanezon
This document provides an overview of developing and deploying Java applications on Azure using Docker. It discusses using Docker to build Java applications, running containers, and deploying stacks. It also covers Docker Enterprise Edition, including subscriptions, certifications, and security features. Finally, it demonstrates using Docker on Azure, such as with Azure Container Service, and shows examples of building, running, and deploying Java applications with Docker.
This document discusses Docker and Kubernetes concepts and how they can be used to deploy applications and services. It provides examples of deploying Dataverse, a data repository system, using Docker containers and Kubernetes. Key points covered include Docker concepts like images, containers and registries. It also discusses tools like Docker Compose for defining multi-container applications and Kubernetes for orchestrating containers across a cluster.
Containers and Nutanix - Acropolis Container ServicesNEXTtour
This presentation was given at the London Nutanix user group (NUG) on Oct 26 by Denis Guyadeen. If you would like to join a NUG, you can find more information here http://bit.ly/NTNXUG - Hope to see you at a community meeting!
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.
This document provides information about Linux containers and Docker. It discusses:
1) The evolution of IT from client-server models to thin apps running on any infrastructure and the challenges of ensuring consistent service interactions and deployments across environments.
2) Virtual machines and their benefits of full isolation but large disk usage, and Vagrant which allows packaging and provisioning of VMs via files.
3) Docker and how it uses Linux containers powered by namespaces and cgroups to deploy applications in lightweight portable containers that are more efficient than VMs. Examples of using Docker are provided.
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.
Tell the history of Container/Docker/Kubernetes, and show the key elements of them.
After view this document, you could know the main feature of Container Docker and Kubernetes.
Very basic infomation about how these technique work together.
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.
Best Practices for Running Kafka on Docker ContainersBlueData, Inc.
Docker containers provide an ideal foundation for running Kafka-as-a-Service on-premises or in the public cloud. However, using Docker containers in production environments for Big Data workloads using Kafka poses some challenges – including container management, scheduling, network configuration and security, and performance.
In this session at Kafka Summit in August 2017, Nanda Vijyaydev of BlueData shared lessons learned from implementing Kafka-as-a-Service with Docker containers.
https://kafka-summit.org/sessions/kafka-service-docker-containers
This document provides an introduction and overview of Docker, including its rapid growth and adoption, key benefits for developers and operations teams, technical underpinnings, ecosystem support, use cases, and future plans. Docker provides a way to package applications into lightweight containers that are portable and can run on any infrastructure. It solves issues around dependency management and consistency across environments.
Docker allows building and running applications inside lightweight containers. Some key benefits of Docker include:
- Portability - Dockerized applications are completely portable and can run on any infrastructure from development machines to production servers.
- Consistency - Docker ensures that application dependencies and environments are always the same, regardless of where the application is run.
- Efficiency - Docker containers are lightweight since they don't need virtualization layers like VMs. This allows for higher density and more efficient use of resources.
The Information Technology have led us into an era where the production, sharing and use of information are now part of everyday life and of which we are often unaware actors almost: it is now almost inevitable not leave a digital trail of many of the actions we do every day; for example, by digital content such as photos, videos, blog posts and everything that revolves around the social networks (Facebook and Twitter in particular). Added to this is that with the "internet of things", we see an increase in devices such as watches, bracelets, thermostats and many other items that are able to connect to the network and therefore generate large data streams. This explosion of data justifies the birth, in the world of the term Big Data: it indicates the data produced in large quantities, with remarkable speed and in different formats, which requires processing technologies and resources that go far beyond the conventional systems management and storage of data. It is immediately clear that, 1) models of data storage based on the relational model, and 2) processing systems based on stored procedures and computations on grids are not applicable in these contexts. As regards the point 1, the RDBMS, widely used for a great variety of applications, have some problems when the amount of data grows beyond certain limits. The scalability and cost of implementation are only a part of the disadvantages: very often, in fact, when there is opposite to the management of big data, also the variability, or the lack of a fixed structure, represents a significant problem. This has given a boost to the development of the NoSQL database. The website NoSQL Databases defines NoSQL databases such as "Next Generation Databases mostly addressing some of the points: being non-relational, distributed, open source and horizontally scalable." These databases are: distributed, open source, scalable horizontally, without a predetermined pattern (key-value, column-oriented, document-based and graph-based), easily replicable, devoid of the ACID and can handle large amounts of data. These databases are integrated or integrated with processing tools based on the MapReduce paradigm proposed by Google in 2009. MapReduce with the open source Hadoop framework represent the new model for distributed processing of large amounts of data that goes to supplant techniques based on stored procedures and computational grids (step 2). The relational model taught courses in basic database design, has many limitations compared to the demands posed by new applications based on Big Data and NoSQL databases that use to store data and MapReduce to process large amounts of data.
Course Website http://pbdmng.datatoknowledge.it/
Contact me to download the slides
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.
Docker is the developer-friendly container technology that enables creation of your application stack: OS, JVM, app server, app, database and all your custom configuration. So you are a Java developer but how comfortable are you and your team taking Docker from development to production? Are you hearing developers say, “But it works on my machine!” when code breaks in production? And if you are, how many hours are then spent standing up an accurate test environment to research and fix the bug that caused the problem?
This workshop/session explains how to package, deploy, and scale Java applications using Docker.
In this talk Ben will walk you through running Cassandra in a docker environment to give you a flexible development environment that uses only a very small set of resources, both locally and with your favorite cloud provider. Lessons learned running Cassandra with a very small set of resources are applicable to both your local development environment and larger, less constrained production deployments.
Similar to Devoxx France 2015 - The Docker Orchestration Ecosystem on Azure (20)
Kubernetes has many ways to scale your workloads, most of what we hear about is scaling our cluster up with either with vm sets or autoscaling groups. There is another way, in this talk we will look at virtual kubelet. Virual Kubelet will allow us to talk to a cloud providers container as a service platform like ACI, fargate or ECI. We will deep dive into how you can scale your applications across virtual kubelet. One issue is the kubernetes service type has is scaling to zero due to the way routing to the pod happens if there is no pod for the service to route too. Scaling our applications to zero is just as important and scaling up. We will look at projects that integrate with the horizontal pod autoscaler that fix this issue. Allowing us to not only scale our applications up but as easily down to make our cluster truly elastic.
KubeCon China 2019 - Building Apps with Containers, Functions and Managed Ser...Patrick Chanezon
Cloud native applications are composed of many technologies and components, but three canonical abstraction emerged in the past few years that help developers structure their architecture: container, functions responding to events, and managed services.
This talk will explain how to develop (Docker, local Kubernetes, virtual Kubelet, OpenFaaS), deploy (managed Kubernetes, functions and services) and package (CNAB specification and tooling) applications using these three components and look at not only deployment workflows but also at day 2 concerns that a developer would need to consider in the cloud native landscape.
We will demo every topic and a Github repository will be available for developers to reproduce the demos and learn at their own pace.
Patrick Chanezon and Scott Coulton
Dockercon 2019 Developing Apps with Containers, Functions and Cloud ServicesPatrick Chanezon
Cloud native applications are composed of containers, serverless functions and managed cloud services.
What is the best set of tools on your desktop to provide a rapid, iterative development experience and package applications using these three components?
This hand-on talk will explain how you can complement Docker Desktop, with it’s local Docker engine and Kubernetes cluster, with open source tools such as the Virtual Kubelet, Open Service Broker, the Gloo hybrid app gateway, Draft, and others, to build the most productive development inner-loop for these type of applications.
It will also cover how you can use the Cloud Native Application Bundle (CNAB) format and it’s implementation in the Docker app experimental tool to package your application and manage it with container supply chain tooling such as Docker Hub.
GIDS 2019: Developing Apps with Containers, Functions and Cloud ServicesPatrick Chanezon
The document discusses developer workflows for building cloud applications using containers, functions, and managed cloud services. It presents options for developing applications locally and deploying to the cloud using tools like Docker Desktop, Azure Functions runtime, Azure Dev Spaces, and Telepresence that enable local development and debugging. The document also discusses approaches for packaging and deploying distributed applications using CNAB and Duffle.
This document provides an overview of Patrick Chanezon's background and interests related to Docker and containerization. Some key points:
- Patrick is Chief Developer Advocate at Docker, where he focuses on developer relations and platforms.
- His interests include agile development, DevOps, microservices, and using containers and Docker to improve developer productivity and application portability.
- He discusses how containers have evolved from early uses in mainframes and virtualization to today's platforms like Docker that make containers a natural fit for modern application architectures like microservices and serverless computing.
Patrick Chanezon, un des pionniers du Cloud chez Google, VMware, Microsoft et Docker, vous raconte la révolution des conteneurs logiciels et comment certains concepts du taoïsme, wei-wu-wei, "agir sans agir", et ziran, naturel, ou spontanéïté, permettent d'en mieux cerner les enjeux.
Les conteneurs accélèrent l'adoption du Cloud en entreprise, avec des architectures hybride et multi cloud, la mise en place de démarches agiles et DevOps pour moderniser les applications existantes et réduire les coûts d'infrastructure, et permettent de nouveaux cas d'utilisation dans l'internet des objets et l'intelligence artificielle.
Moby is an open source project providing a "LEGO set" of dozens of components, the framework to assemble them into specialized container-based systems, and a place for all container enthusiasts to experiment and exchange ideas.
One of these assemblies is Docker CE, an open source product that lets you build, ship, and run containers.
This talk will explain how you can leverage the Moby project to assemble your own specialized container-based system, whether for IoT, cloud or bare metal scenarios.
We will cover Moby itself, the framework, and tooling around the project, as well as many of it’s components: LinuxKit, InfraKit, containerd, SwarmKit, Notary.
Then we will present a few use cases and demos of how different companies have leveraged Moby and some of the Moby components to create their own container-based systems.
Video at https://www.youtube.com/watch?v=kDp22YkD6WY
Microsoft Techsummit Zurich Docker and MicrosoftPatrick Chanezon
Docker and Microsoft have been collaborating both in open source and through their commercial partnership to bring the benefits of Docker Windows and Linux containers to Azure Enterprise customers. Docker’s container platform, Docker Enterprise Edition, is used to modernize traditioal applications, and move them to Azure, as well as to develop new cloud native applications using microservices architecture, bringing agility to developers and control to IT Pros. This talk will cover the latest developments in Docker’s container platform with planned support for Kubernetes in Docker for Windows, and Docker Enterprise Edition for Azure, Docker for Azure Stack to enable hybrid cloud deployments, Windows containers, Linux containers on Windows.
Develop and deploy Kubernetes applications with Docker - IBM Index 2018Patrick Chanezon
Docker Desktop and Enterprise Edition now both include Kubernetes as an optional orchestration component. This talk will explain how to use Docker Desktop (Mac or Windows) to develop and debug a cloud native application, then how Docker Enterprise Edition helps you deploy it to Kubernetes in production.
Docker Meetup Feb 2018 Develop and deploy Kubernetes Apps with DockerPatrick Chanezon
This document discusses Docker's support for both Docker Swarm and Kubernetes. It outlines Docker's strategy to provide developers with tools that allow testing and development locally using Docker Community Edition and then deploying applications to production environments running either Swarm or Kubernetes. Docker Enterprise Edition provides security, management and other features for both Swarm and Kubernetes production deployments.
This document provides a recap of DockerCon EU 2017 and discusses Docker's strategy to support both Docker Swarm and Kubernetes as orchestration platforms. Key points include:
- Docker is developing its platform to natively support both Swarm and Kubernetes orchestration. This will allow developers to test locally with Swarm and deploy to production with either Swarm or Kubernetes.
- Docker Enterprise Edition will provide security, management, and support for both Swarm and Kubernetes clusters. It aims to offer the best container development workflow and enterprise container security and management.
- Docker is contributing its projects like containerd, runc, and Moby to the Cloud Native Computing Foundation to promote open governance and collaboration between Docker and Kubernetes.
The document discusses Docker's innovation culture, which is based on traits like building on open source infrastructure, having an accessible design, encouraging risk-taking and experimentation, contributing to open source communities, developing reusable APIs, and hiring a diverse team. It summarizes that Docker's culture of not reinventing wheels, accessibility fueling innovation, failing often and quickly to learn, competing with giants through open source, developing reusable components through APIs, and having a diverse team were keys to its success and leadership in the container space.
The Docker Way: modernize traditional applications without action (wu-wei) and create new cloud native microservices applications with naturalness (ziran).
This talk also provides a summary of all the DockerCon EU 2017 announcements: Kubernetes now supported in Docker, MTA, IBM partnership.
Building specialized container-based systems with Moby: a few use cases
This talk will explain how you can leverage the Moby project to assemble your own specialized container-based system, whether for IoT, cloud or bare metal scenarios. We will cover Moby itself, the framework, and tooling around the project, as well as many of it’s components: LinuxKit, InfraKit, containerd, SwarmKit, Notary. Then we will present a few use cases and demos of how different companies have leveraged Moby and some of the Moby components to create their own container-based systems.
This document outlines the agenda for the June 2017 Moby Summit. It begins with an intro by Solomon Hykes on taking containers mainstream using a library of components and assemblies. The agenda then covers updates on Moby projects like LinuxKit, containerd, InfraKit, and security. It allocates time for birds-of-a-feather sessions on specific projects and technologies, followed by a recap and Q&A panel. The goal is for the open source community to contribute to and collaborate on the Moby projects through the Docker/Moby split.
Docker Cap Gemini CloudXperience 2017 - la revolution des conteneurs logicielsPatrick Chanezon
Si vous avez raté le début : Patrick Chanezon, un des pionniers du Cloud chez Google, VMware, Microsoft et Docker, vous raconte la révolution des conteneurs logiciels en quelques films ; comment ils accélèrent l'adoption du Cloud en entreprise, avec des architectures hybride et multi, la mise en place de démarches agiles et DevOps pour moderniser les applications existantes et réduire les coûts d'infrastructure, et permettent de nouveaux cas d'utilisation dans l'internet des objets et l'intelligence artificielle.
En bref, comment expliquer la stratégie des opérateurs du Cloud avec des films de science- fiction ? C’est le défi que va relever Patrick Chanezon, évangéliste chez Docker.
Docker moves very fast, with an edge channel released every month and a stable release every 3 months. Patrick will talk about how Docker introduced Docker EE and a certification program for containers and plugins with Docker CE and EE 17.03 (from March), the announcements from DockerCon (April), and the many new features planned for Docker CE 17.05 in May.
This talk will be about what's new in Docker and what's next on the roadmap
Oscon 2017: Build your own container-based system with the Moby projectPatrick Chanezon
Build your own container-based system
with the Moby project
Docker Community Edition—an open source product that lets you build, ship, and run containers—is an assembly of modular components built from an upstream open source project called Moby. Moby provides a “Lego set” of dozens of components, the framework for assembling them into specialized container-based systems, and a place for all container enthusiasts to experiment and exchange ideas.
Patrick Chanezon and Mindy Preston explain how you can leverage the Moby project to assemble your own specialized container-based system, whether for IoT, cloud, or bare-metal scenarios. Patrick and Mindy explore Moby’s framework, components, and tooling, focusing on two components: LinuxKit, a toolkit to build container-based Linux subsystems that are secure, lean, and portable, and InfraKit, a toolkit for creating and managing declarative, self-healing infrastructure. Along the way, they demo how to use Moby, LinuxKit, InfraKit, and other components to quickly assemble full-blown container-based systems for several use cases and deploy them on various infrastructures.
Data Protection in a Connected World: Sovereignty and Cyber Securityanupriti
Delve into the critical intersection of data sovereignty and cyber security in this presentation. Explore unconventional cyber threat vectors and strategies to safeguard data integrity and sovereignty in an increasingly interconnected world. Gain insights into emerging threats and proactive defense measures essential for modern digital ecosystems.
How to Avoid Learning the Linux-Kernel Memory ModelScyllaDB
The Linux-kernel memory model (LKMM) is a powerful tool for developing highly concurrent Linux-kernel code, but it also has a steep learning curve. Wouldn't it be great to get most of LKMM's benefits without the learning curve?
This talk will describe how to do exactly that by using the standard Linux-kernel APIs (locking, reference counting, RCU) along with a simple rules of thumb, thus gaining most of LKMM's power with less learning. And the full LKMM is always there when you need it!
Sustainability requires ingenuity and stewardship. Did you know Pigging Solutions pigging systems help you achieve your sustainable manufacturing goals AND provide rapid return on investment.
How? Our systems recover over 99% of product in transfer piping. Recovering trapped product from transfer lines that would otherwise become flush-waste, means you can increase batch yields and eliminate flush waste. From raw materials to finished product, if you can pump it, we can pig it.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/07/intels-approach-to-operationalizing-ai-in-the-manufacturing-sector-a-presentation-from-intel/
Tara Thimmanaik, AI Systems and Solutions Architect at Intel, presents the “Intel’s Approach to Operationalizing AI in the Manufacturing Sector,” tutorial at the May 2024 Embedded Vision Summit.
AI at the edge is powering a revolution in industrial IoT, from real-time processing and analytics that drive greater efficiency and learning to predictive maintenance. Intel is focused on developing tools and assets to help domain experts operationalize AI-based solutions in their fields of expertise.
In this talk, Thimmanaik explains how Intel’s software platforms simplify labor-intensive data upload, labeling, training, model optimization and retraining tasks. She shows how domain experts can quickly build vision models for a wide range of processes—detecting defective parts on a production line, reducing downtime on the factory floor, automating inventory management and other digitization and automation projects. And she introduces Intel-provided edge computing assets that empower faster localized insights and decisions, improving labor productivity through easy-to-use AI tools that democratize AI.
An invited talk given by Mark Billinghurst on Research Directions for Cross Reality Interfaces. This was given on July 2nd 2024 as part of the 2024 Summer School on Cross Reality in Hagenberg, Austria (July 1st - 7th)
In this follow-up session on knowledge and prompt engineering, we will explore structured prompting, chain of thought prompting, iterative prompting, prompt optimization, emotional language prompts, and the inclusion of user signals and industry-specific data to enhance LLM performance.
Join EIS Founder & CEO Seth Earley and special guest Nick Usborne, Copywriter, Trainer, and Speaker, as they delve into these methodologies to improve AI-driven knowledge processes for employees and customers alike.
What Not to Document and Why_ (North Bay Python 2024)Margaret Fero
We’re hopefully all on board with writing documentation for our projects. However, especially with the rise of supply-chain attacks, there are some aspects of our projects that we really shouldn’t document, and should instead remediate as vulnerabilities. If we do document these aspects of a project, it may help someone compromise the project itself or our users. In this talk, you will learn why some aspects of documentation may help attackers more than users, how to recognize those aspects in your own projects, and what to do when you encounter such an issue.
These are slides as presented at North Bay Python 2024, with one minor modification to add the URL of a tweet screenshotted in the presentation.
Interaction Latency: Square's User-Centric Mobile Performance MetricScyllaDB
Mobile performance metrics often take inspiration from the backend world and measure resource usage (CPU usage, memory usage, etc) and workload durations (how long a piece of code takes to run).
However, mobile apps are used by humans and the app performance directly impacts their experience, so we should primarily track user-centric mobile performance metrics. Following the lead of tech giants, the mobile industry at large is now adopting the tracking of app launch time and smoothness (jank during motion).
At Square, our customers spend most of their time in the app long after it's launched, and they don't scroll much, so app launch time and smoothness aren't critical metrics. What should we track instead?
This talk will introduce you to Interaction Latency, a user-centric mobile performance metric inspired from the Web Vital metric Interaction to Next Paint"" (web.dev/inp). We'll go over why apps need to track this, how to properly implement its tracking (it's tricky!), how to aggregate this metric and what thresholds you should target.
The DealBook is our annual overview of the Ukrainian tech investment industry. This edition comprehensively covers the full year 2023 and the first deals of 2024.
Paradigm Shifts in User Modeling: A Journey from Historical Foundations to Em...Erasmo Purificato
Slide of the tutorial entitled "Paradigm Shifts in User Modeling: A Journey from Historical Foundations to Emerging Trends" held at UMAP'24: 32nd ACM Conference on User Modeling, Adaptation and Personalization (July 1, 2024 | Cagliari, Italy)
UiPath Community Day Kraków: Devs4Devs ConferenceUiPathCommunity
We are honored to launch and host this event for our UiPath Polish Community, with the help of our partners - Proservartner!
We certainly hope we have managed to spike your interest in the subjects to be presented and the incredible networking opportunities at hand, too!
Check out our proposed agenda below 👇👇
08:30 ☕ Welcome coffee (30')
09:00 Opening note/ Intro to UiPath Community (10')
Cristina Vidu, Global Manager, Marketing Community @UiPath
Dawid Kot, Digital Transformation Lead @Proservartner
09:10 Cloud migration - Proservartner & DOVISTA case study (30')
Marcin Drozdowski, Automation CoE Manager @DOVISTA
Pawel Kamiński, RPA developer @DOVISTA
Mikolaj Zielinski, UiPath MVP, Senior Solutions Engineer @Proservartner
09:40 From bottlenecks to breakthroughs: Citizen Development in action (25')
Pawel Poplawski, Director, Improvement and Automation @McCormick & Company
Michał Cieślak, Senior Manager, Automation Programs @McCormick & Company
10:05 Next-level bots: API integration in UiPath Studio (30')
Mikolaj Zielinski, UiPath MVP, Senior Solutions Engineer @Proservartner
10:35 ☕ Coffee Break (15')
10:50 Document Understanding with my RPA Companion (45')
Ewa Gruszka, Enterprise Sales Specialist, AI & ML @UiPath
11:35 Power up your Robots: GenAI and GPT in REFramework (45')
Krzysztof Karaszewski, Global RPA Product Manager
12:20 🍕 Lunch Break (1hr)
13:20 From Concept to Quality: UiPath Test Suite for AI-powered Knowledge Bots (30')
Kamil Miśko, UiPath MVP, Senior RPA Developer @Zurich Insurance
13:50 Communications Mining - focus on AI capabilities (30')
Thomasz Wierzbicki, Business Analyst @Office Samurai
14:20 Polish MVP panel: Insights on MVP award achievements and career profiling
What's Next Web Development Trends to Watch.pdfSeasiaInfotech2
Explore the latest advancements and upcoming innovations in web development with our guide to the trends shaping the future of digital experiences. Read our article today for more information.
Video traffic on the Internet is constantly growing; networked multimedia applications consume a predominant share of the available Internet bandwidth. A major technical breakthrough and enabler in multimedia systems research and of industrial networked multimedia services certainly was the HTTP Adaptive Streaming (HAS) technique. This resulted in the standardization of MPEG Dynamic Adaptive Streaming over HTTP (MPEG-DASH) which, together with HTTP Live Streaming (HLS), is widely used for multimedia delivery in today’s networks. Existing challenges in multimedia systems research deal with the trade-off between (i) the ever-increasing content complexity, (ii) various requirements with respect to time (most importantly, latency), and (iii) quality of experience (QoE). Optimizing towards one aspect usually negatively impacts at least one of the other two aspects if not both. This situation sets the stage for our research work in the ATHENA Christian Doppler (CD) Laboratory (Adaptive Streaming over HTTP and Emerging Networked Multimedia Services; https://athena.itec.aau.at/), jointly funded by public sources and industry. In this talk, we will present selected novel approaches and research results of the first year of the ATHENA CD Lab’s operation. We will highlight HAS-related research on (i) multimedia content provisioning (machine learning for video encoding); (ii) multimedia content delivery (support of edge processing and virtualized network functions for video networking); (iii) multimedia content consumption and end-to-end aspects (player-triggered segment retransmissions to improve video playout quality); and (iv) novel QoE investigations (adaptive point cloud streaming). We will also put the work into the context of international multimedia systems research.
What’s New in Teams Calling, Meetings and Devices May 2024
Devoxx France 2015 - The Docker Orchestration Ecosystem on Azure
1. Patrick Chanezon, Docker Inc.
@chanezon
The Docker Ecosystem
With slides from @jpetazzo @timpark @vieux @tnachen IBM
on Microsoft Azure
Ride the Whale!
18. Docker now
A platform to build, ship, and run any app, anywhere
docker engine
docker hub
docker-machine
docker-compose
docker-swarm
19. Docker, the community
>700 contributors
~20 core maintainers
>40,000 Dockerized projects on GitHub
>60,000 repositories on Docker Hub
>25000 meetup members,
>140 cities, >50 countries
>2,000,000 downloads of boot2docker
20. Docker Inc, the company
Headcount: ~130
Revenue:
t-shirts and stickers featuring the cool blue whale
SAAS delivered through Docker Hub
Support & Training
soon: Docker Hub Enterprise, behind the firewall
29. More Windows options
• Nano Server
• Hyper-V Containers
http://azure.microsoft.com/blog/2015/04/08/microsoft-unveils-new-container-technologies-for-the-next-generation-cloud
47. Setup using the hosted discovery service
• Create a cluster:
$ swarm create
• Add nodes to a cluster:
$ swarm join --add=<node_ip> token://<token>
• Start Swarm
$ swarm manage --addr=<swarm_ip> token://<token>
Or you can use your own etcd, zookeeper or consul
Contributions are welcome :
48. Resource Management
• Memory
$ docker run -m 1g …
• CPU
$ docker run -c 1 …
• Ports
$ docker run -p 80:80 …
• More to come, ex: network interfaces
49. Constraints
• Standard constraints induced from docker info
docker run -e “constraint:operatingsystem==*fedora*” …
docker run -e “constraint:storagedriver==*aufs*” …
• Custom constraints with host labels
docker -d --label “region==us-east”
docker run -e “constraint:region==us-east” …
• Pin a container to a specific host
docker run –e “constraint:node==ubuntu-2” …
50. Affinities
• Containers affinities
docker run --name web nginx
docker run -e “affinity:container==web” logger
• Containers Anti-affinities
docker run --name redis-master redis
docker run --name redis-slave -e “affinity:container!=redis*”
…
• Images affinities
docker run -e “affinity:image==redis” redis
51. New in 0.2.0: Soft Affinities/Constraints
• Containers affinities
docker run -e “affinity:container~!=—name web nginx
docker run -e “affinity:container==web” logger
• Containers Anti-affinities
docker run --name redis-master redis
docker run --name redis-slave -e “affinity:container!=redis*”
…
• Images affinities
docker run -e “affinity:image==redis” redis
52. Swarm Scheduler
2 steps:
• 1- Apply filters to exclude nodes
- ports
- labels
- health
• 2- Use a strategy to pick the best node
- random
- binpack
- spread
Contributions are welcome :
53. Swarm Beta: Integrations
• Fully integrated with Machine
• Partially integrated with Compose
• Mesos integration has started in collaboration with Mesosphere.
69. Deis (http://deis.io)
• Open source PaaS platform that builds on CoreOS.
• Replicates the popular Heroku devops workflow.
• Primary mechanism for pushing applications is through git.
• Developer experience is not unlike Azure Websites…
• …but is built on Linux so full support for open source stacks.
• Enables us to win migrations from Salesforce to Azure.
• Hackfest in November to enable Deis for Tagboard.
• Enables us to win startups that expect this workflow.
72. tpark:www$ git push deis master
• Git pushes master to deis git remote on endpoint
• Deis senses static web application
• Selects Heroku Buildpack
• Uses buildpack to build application Docker container.
• Pushes this container to a private Docker registry.
• Orchestrates the creation or update of this container
on the cluster.
• Updates routing mesh to route to these containers.
76. tpark:api$ git push deis master
• Git pushes master to deis git remote on endpoint
• Deis senses node.js application
• Selects Heroku node.js Buildpack
• Uses buildpack to build application Docker container.
• Pushes this container to a private Docker registry.
• Orchestrates the creation or update of this container
on the cluster.
• Updates routing mesh to route to these containers.
80. tpark:api$ deis config:set
DATABASE_URL=postgres://user:pass@example.com:54
32/db
• Applications in Deis are configured through environmental
variables.
• MUST READ: http://12factor.net/
• Key point: Code is separated from config.
• Enables generic containers that are configured at runtime.
• Every app container spun up by Deis will have a copy of these
config environmental variables.
81. tpark:api$ deis logs
• Deis automatically rolls and consolidates logs from all
containers.
97. 97
Customer Managed
Service Provider Managed
IBM SoftLayer
Bluemix started as a public PaaS
Bluemix started with a major focus on developer productivity in the public cloud.
Infrastructure as
a Service
Code
Data
Runtime
Middleware
OS
Virtualization
Servers
Storage
Networking
Code
Data
Runtime
Middleware
OS
Virtualization
Servers
Storage
Networking
Platform as
a Service
98. 98
Customer Managed
Service Provider Managed
IBM SoftLayer
We listened. Now we’re evolving to become even more flexible.
Capabilities in Bluemix now span PaaS and IaaS and can be delivered as a public,
dedicated, or on-premises* implementation.
Infrastructure as
a Service
Code
Data
Runtime
Middleware
OS
Virtualization
Servers
Storage
Networking
Code
Data
Runtime
Middleware
OS
Virtualization
Servers
Storage
Networking
Platform as
a Service
*Bluemix Local coming Summer 2015
Built on open
technologies:
99. How does Bluemix work?
Bluemix is underlined by three key open compute technologies: Cloud Foundry, Docker, and
OpenStack. It extends each of these with a growing number of services, robust DevOps tooling,
integration capabilities, and a seamless developer experience.
99
Flexible Compute Options to Run Apps / Services
Instant Runtimes Containers Virtual Machines
Platform Deployment Options that Meet Your Workload Requirements
Bluemix
Public
Bluemix
Dedicated
Bluemix
Local*
DevOps
Tooling Your Own Hosted Apps / Services
Integration and
API Mgmt
Powered by IBM SoftLayer In Your Data Center
+ + +
+ +
+ Always focused on what’s next
Catalog of Services that Extend Apps’ Functionality
Web Data Mobile AnalyticsCognitive IoT Security Yours
+
*Bluemix Local coming Summer 2015
100. Containers in Bluemix
Bluemix now comes with a fully integrated, high performance Docker experience, meaning monitoring,
logging, elasticity, enterprise images, and VM abstraction are all standard.
100
Docker Value IBM Value-add Customer Value
Docker Hub Registry holds a
repository of 75000+ Docker
images
• IBM hosted public registry containing IBM images - linked to
Docker Hub
• Client unique registry available on and off premises
• Enterprise-ready images
Access to the images you require to deploy
containers that meet your business needs and
strategy
Open-source, standardized,
lightweight, self sufficient LXC
container technology
• Enhanced performance with bare metal deployment
• Run images to local datacenter or cloud
• Deployment choice with pSeries & zSeries
Flexibility to choose the right hybrid cloud mix
for your business
Build, ship, and run standardized
containers
• Integrated monitoring & logging
• Elasticity to grow storage & container needs
• Life-cycle management of containers and data volumes
• No VMs to manage
Docker ease of use combined with enterprise-
level integrity and confidence
Container connections using
links and service discovery
• Private network communication
• External IP address
• Subnet Range
Extends and connects Docker containers to
production-ready enterprise environments
109. 10
3
References
• talk about cloud platforms: Managing complexity in giant systems http://www.slideshare.net/chanezon/tackling-
complexity-in-giant-systems-approaches-from-several-cloud-providers
• talk about Devops, the Microsoft Way
http://www.slideshare.net/chanezon/devops-the-microsoft-way
• MS Open Tech https://msopentech.com/ Blog, VM Depot
• P@ Linux on Azure pages https://github.com/chanezon/azure-linux/
• Tim’s CoreOS tutorial https://github.com/timfpark/coreos-azure
• Tim’s Deis documentation
• @jpetazzo’s presentations http://www.slideshare.net/jpetazzo/
• @bcantrill’s deck http://www.slideshare.net/bcantrill/docker-and-the-future-of-containers-in-production
• @vieux deck on Swarm
• @htchen deck on Mesos + Swarm https://speakerdeck.com/tnachen/docker-swarm-plus-mesos
What I learned from these experiences is that there are a set of key challenges in the internet of things.
The first is discovery.
Let’s say we want to build an application that managing the lighting in our home.
We want to it to be able to ask our own personal internet of things for switches and lights.
So the first challenge we have is being able to express those capabilities on devices and be able query for them.