Build Fast, Deploy Fast: Innovating in the Enterprise by Imran Raja and Andy Lim
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3. Lessons learned include the need for a proxy for the Docker remote API across multiple hosts, and approaches for keeping Docker advantages like image portability when integrating with an IaaS platform.
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* Dockerfiles can inherit from other docker images, but images are not
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so as usage grows identical or similar instructions can be duplicated
across many files
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instructions
* Dockerfiles are just that, files. So they can come from anywhere
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use containers to maintain parity across development, testing, and production environments, but we can also use containerization to significantly reduce time needed for testing by spinning up multiple instances of fully isolated testing environments and executing tests in parallel. This strategy also helps you maximize the utilization of infrastructure resources. The enhanced toolset provided by Docker makes this process simple and unobtrusive, and you’ll see how Docker Engine, Registry, Machine, and Compose can work together to make your tests fast.
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As containers move from the developer's workstation into production environments there are many questions about how they fit into a company's existing infrastructure. Should a workload run in a VM or in a container? Should that container run on physical or virtual? In the data center or in the cloud?
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Abstract:
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Nishant Totla is a software engineer at Docker, and works on the core open source team. He is currently working on Docker SwarmKit and Docker Swarm. Prior to Docker, he was a PhD student at UC Berkeley, doing research on programming languages. In his spare time, he enjoys long-distance running, biking, and other outdoor activities. Nishant tweets at @nishanttotla.
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• Experimental build
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• Compose to Swarm
• Data management commands
• Brand new “init system”
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Why Docker
Configuration management tools like Chef, Puppet, and Ansible aim to reduce inconsistencies by imposing and managing consistent configurations across environments. However, they do not fully address issues related to dependencies, isolation, and portability. Docker containers build on these tools by adding standard interfaces and a lightweight virtualization layer that encapsulates code and dependencies, allowing applications and their environments to be packaged together and run consistently on any infrastructure while also providing isolation.
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Raymond Arifianto, AccelByte and
Mark Mandel, Google -
We have been deploying containerized micro-services for our Game Backend Services for a while. Now we are tackling the challenge to scale up fleets of game dedicated servers in multiple regions, multiple data centers and multiple providers - some in bare metal, some in Cloud. So we leverage docker containerization to deploy Game Servers to achieve Portability, Fast Deployment and Predictability, enabling us to scale up to thousands of servers, on demand, without a sweat.
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Docker continues to be the standard tool for building container images. For more than a year Docker ships with BuildKit as an alternative image builder, providing advanced features for secret and cache management. These features help to make image builds faster and more secure. In this session, Docker Captain Nicholas Dille will teach you how to use Buildkit features to your advantage.
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At Appsembler, we've built a system to deploy personalized learning labs using Docker Swarm. Each learning lab consists of arbitrary software running in a Docker container, so each student can have their own isolated environment to learn and experiment. The containers can be paired with another container running the Cloud9 IDE, allowing students to modify code and see the results in real time without the need to install anything on their own system.
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Dockerizing Windows Server Applications by Ender Barillas and Taylor Brown
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.
The Dockerfile Explosion and the Need for Higher Level Tools by Gareth Rushgrove
Dockerfiles are great. They provide a zero-barrier-to-entry format for
describing a single Docker image which is immediately clear to anyone
reading them. But with that simplicity comes problems that become
apparent as your adoption of Docker gathers pace.
* Dockerfiles can inherit from other docker images, but images are not
Dockerfiles
* Dockerfile provides no built-in mechanism for creating abstractions,
so as usage grows identical or similar instructions can be duplicated
across many files
* The Docker APi exposes a build endpoint, but the API is very course,
taking Dockerfile as the transport rather than exposing the individual
instructions
* Dockerfiles are just that, files. So they can come from anywhere
The one layer per line in a Dockerfile limitation can lead to an
explosion of layers, which fail to take advantage of the promised
space and performance benefits.
Efficient Parallel Testing with Docker by Laura Frank
Fast and efficient software testing is easy with Docker. We often
use containers to maintain parity across development, testing, and production environments, but we can also use containerization to significantly reduce time needed for testing by spinning up multiple instances of fully isolated testing environments and executing tests in parallel. This strategy also helps you maximize the utilization of infrastructure resources. The enhanced toolset provided by Docker makes this process simple and unobtrusive, and you’ll see how Docker Engine, Registry, Machine, and Compose can work together to make your tests fast.
Docker for Mac and Windows: The Insider's Guide by Justin Cormack
Docker for Mac and Windows were released in beta in March, and provide lots of new features that users have been clamouring for including: file system notifications, simpler file sharing, and no Virtualbox hassles.
During this talk, I will give the inside guide to how these products work. We will look at all the major components and how they fit together to make up the product. This includes a technical deep dive covering the hypervisors for OSX and Windows, the custom file sharing code, the networking, the embedded Alpine Linux distribution, and more.
Containers and VMs and Clouds: Oh My. by Mike Coleman
As containers move from the developer's workstation into production environments there are many questions about how they fit into a company's existing infrastructure. Should a workload run in a VM or in a container? Should that container run on physical or virtual? In the data center or in the cloud?
The reality is that there is no "right" answer, just a series of questions that admins should be asking as they look to figure out where to run their application workloads. In this talk we'll take a look at the key differences between containers and VMs. From there we'll discuss the coexistence of VMs and containers, and finally we'll take a look at key factors to consider when making the decision where to run your applications. Throughout the presentation we'll highlight real world customers, their problems, and their ultimate deployment decisions.
Windows Server and Docker - The Internals Behind Bringing Docker and Containe...
Docker leverages capabilities in Linux like namespaces and cgroups to enable containers and then builds tooling on top to enable users to build distributed apps. A common question is "What about Docker support for Windows?" In this session the Windows engineering leads will dive deep into the primitives within Windows to enable an awesome Docker experience on Windows. This session will also include a live demo of Docker and Windows Server.
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Metrics and monitoring are a time honored tradition for any engineering discipline. It is how we ensure the systems we use are working the way we expect. If this is a time honored tradition, why is it not a built into every piece of software we create, from the ground up? With software engineering, usually the trick to solving anything is to make it easier. By solving the hard parts of application metrics in Docker, we should make it more likely that metrics are a part of your services from the start.
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Nishant Totla is a software engineer at Docker, and works on the core open source team. He is currently working on Docker SwarmKit and Docker Swarm. Prior to Docker, he was a PhD student at UC Berkeley, doing research on programming languages. In his spare time, he enjoys long-distance running, biking, and other outdoor activities. Nishant tweets at @nishanttotla.
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Docker Roadshow 2016
This presentation is from the 2016 Enterprise Roadshow series in North America and Europe. This presentation explains the Docker enterprise solution including Containers as a Service workflows powered by Docker Datacenter and the integration with HPE to deliver a container platform on hybrid cloud infrastructure.
Learn more: www.docker.com/enterprise
Docker and Microsoft - Windows Server 2016 Technical Deep Dive
This document summarizes a webinar about Docker and Windows Server 2016. It discusses how Docker is now supported on 98% of enterprise workloads, including Windows Server 2016, providing the same benefits of Docker on Linux to Windows developers and IT professionals. It outlines how Microsoft and Docker partnered to port Docker Engine to Windows, and how Docker images can now be built and run across Linux and Windows. It provides examples of using Docker with Windows Server 2016 for development/testing and migrating applications.
Online Meetup: What's new in docker 1.13.0
Core team member and release captain Victor Vieux will introduce us to what's new in Docker 1.13. Victor will first give an overview and demo some of the new features below:
• Restructuration of CLI commands
• Experimental build
• CLI backward compatibility
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• Compose to Swarm
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Configuration management tools like Chef, Puppet, and Ansible aim to reduce inconsistencies by imposing and managing consistent configurations across environments. However, they do not fully address issues related to dependencies, isolation, and portability. Docker containers build on these tools by adding standard interfaces and a lightweight virtualization layer that encapsulates code and dependencies, allowing applications and their environments to be packaged together and run consistently on any infrastructure while also providing isolation.
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みなさんこんにちはこれ何文字まで入るの？40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの？えこ...
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