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- Herausgeber: Packt Publishing
- Kategorie: Fachliteratur
- Sprache: Englisch
You?re pro Docker? You?ve read all about orchestration with Docker in books? Now learn how to troubleshoot Docker in practice. Gain all the tools to safely see Docker in action with this 2017 book.
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Seitenzahl: 260
Veröffentlichungsjahr: 2017
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Table of Contents
Troubleshooting Docker
Troubleshooting Docker
Copyright © 2017 Packt Publishing
All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.
Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the authors, nor Packt Publishing, and its dealers and distributors will be held liable for any damages caused or alleged to be caused directly or indirectly by this book.
Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.
First published: March 2017
Production reference: 1280317
Published by Packt Publishing Ltd.
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ISBN 978-1-78355-234-4
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Credits
Authors
Vaibhav Kohli
Rajdeep Dua
John Wooten
Copy Editors
Shaila Kusanale
Safis Editing
Reviewer
Radhakrishna Nayak
Project Coordinator
Ritika Manoj
Commissioning Editor
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Proofreader
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Acquisition Editor
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Indexer
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Content Development Editors
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Production Coordinator
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Technical Editors
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Graphics
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About the Authors
Vaibhav Kohli at present is working in VMware's R&D Department and earlier taught computer engineering for a year at the esteemed University of Mumbai. He works for the office of the CTO, VMware IoT (Internet of Things) project. He has published many research papers in leading journals, IEEE transactions, and has filed patents at VMware on container technology. One of his big data projects has won the top prize at the national-level project showcase event. He has conducted workshops, hackathons, training sessions, and trade shows in many countries and is a reputed & established speaker at conferences on IoT and Docker technology. He is an active open source code contributor, repository manager and has also published many online Docker & Kubernetes tutorials. He has helped many customers and organizations to understand cloud-native apps, DevOps model and migrate to micro-service architecture. He has also recently published a book on Docker Networking.
Vaibhav manages and leads various meetup groups across India on the latest cutting-edge Docker and Kubernetes technologies.
First and foremost, I would like to thank God for providing me the gift of writing. I dedicate this book to my mom & dad, Kamni Kohli & Ashok K Kohli, who have supported me in everything I have ever done. A special thanks to all my mentors who helped shape me into the person that I am…
Rajdeep Dua has over 18 years of experience in the Cloud and Big Data space. He has worked extensively on Cloud Infrastructure and Machine Learning related projects as well evangelized these stacks at Salesforce, Google, VMWare. Currently, he leads Developer Relations team at Salesforce India. He also works with the Machine Learning team at Salesforce.
He has been nominated by Docker as a Docker Captain for his contributions to the community. His contributions to the open source community are in the following projects: Docker, Kubernetes, Android, OpenStack, and Cloud Foundry. He also has teaching experience in Cloud and Big Data at IIIT Hyderabad, ISB, IIIT Delhi, and College of Engineering Pune.
Rajdeep did his MBA in IT and Systems from Indian Institute of Management Lucknow, India, and BTech from Thapar University, Patiala, India. You can reach him on Twitter at @rajdeepdua.
John Wooten is the founder and CEO of CONSULTED, a global open source cloud consultancy that designs secure, succinct, and sustainable cloud architectures. As a leading cloud solutions architect and open technology strategist, John has deep and applicable real-world experience in designing, testing, deploying, and managing public, private, and hybrid cloud systems for both enterprise and government. His primary technical proficiencies include Linux systems administration, OpenStack clouds, and Docker containers. As an open source activist, John is committedly passionate and works extensively within a broad range of open source projects and communities. His latest Internet project is as the founder and maintainer of ÖppenSourced (www.öppensourced.com), a leading repository and defining resource on open source projects and applications. Otherwise, he is a self-proclaimed beach bum in search of the next surfable wave or is hiking and camping in remote locations.
About the Reviewer
Radhakrishna Nayak is a free software evangelist and works as a senior software engineer at Plivo. He has over 5 years of experience. He is a full stack developer and has worked on various open source technologies, such as Python, Django, AngularJS, ReactJS, HTML5, CSS3, MySQL, MongoDB, PostgreSQL, Docker, and many more. He loves to explore and try out new technologies. He is a foodie and loves to explore new restaurants and ice cream parlors.
I would like to thank my parents, Sudheer Nayak and Vranda Nayak, for all their support and freedom to follow my passion. Thanks to all my colleagues at Plivo and Gautham Pai, founder of Jnaapti, for all their support and encouragement. Thanks to Nikhil, Ritika, and the team at Packt Publishing for trusting my abilities and giving the an opportunity to review this book.
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Preface
Docker is an open source, container-based platform that enables anyone to consistently develop and deploy stable applications anywhere. Docker delivers speed, simplicity, and security in creating scalable and portable environments for ultramodern applications. With the advent and prevalence of Docker in the containerization of modern microservices and N-tier applications, it is both prudent and imperative to effectively troubleshoot automated workflows for production-level deployments.
What this book covers
Chapter 1, Understanding Container Scenarios and an Overview of Docker, is about the basic containerization concept with the help of application and OS-based containers. We will throw some light on the Docker technology, its advantages, and the life cycle of Docker containers.
Chapter 2, Docker Installation, will go over the steps to install Docker on various Linux distributions – Ubuntu, CoreOS, CentOS, Red Hat Linux, Fedora, and SUSE Linux.
Chapter 3, Building Base and Layered Images, teaches that a mission-critical task in production-ready application containerization is image building. We will also discuss building images manually from scratch. Moving ahead, we will explore building layered images with a Dockerfile and enlist the Dockerfile commands in detail.
Chapter 4, Devising Microservices and N-Tier Applications, will explore example environments designed seamlessly from development to test, eliminating the need for manual and error-prone resource provisioning and configuration. In doing so, we will touch briefly on how a microservice applications can be tested, automated, deployed, and managed.
Chapter 5, Moving Around Containerized Application, will take a look at Docker registry. We will start with the basic concepts of Docker public repository using Docker Hub and the use case of sharing containers with a larger audience. Docker also provides the option to deploy a private Docker registry, which we look into, that can be used to push, pull, and share the Docker containers internally in the organization.
Chapter 6, Making Containers Work, will teach you about privileged containers, which have access to all the host devices, and super-privileged containers, which show that the containers can run a background service that can be used to run services in Docker containers to manage the underlying host.
Chapter 7, Managing the Networking Stack of a Docker Container, will explain how Docker networking is powered with Docker0 bridge and its troubleshooting issues and configuration. We will also look at troubleshooting the communication issues between Docker networks and the external network. We look into containers communication across multiple hosts using different networking options, such as Weave, OVS, Flannel, and Docker's latest overlay network. We will compare them and look at the troubleshooting issues involved in their configuration.
Chapter 8, Managing Docker Containers with Kubernetes, explains how to manage Docker containers with help of Kubernetes. We will cover many deployment scenarios and troubleshooting issues while deploying Kubernetes on a Bare Metal machine, AWS, vSphere, or using minikube. We will also look at deploying Kubernetes pods effectively and debugging Kubernetes issues.
Chapter 9, Hooking Volume Baggage, will dive into data volumes and storage driver concepts related to Docker. We will discuss troubleshooting the data volumes with the help of the four approaches and look at their pros and cons. The first case of storing data inside the Docker container is the most basic case, but it doesn't provide the flexibility to manage and handle data in the production environment. The second and third cases are about storing the data using data-only containers or directly on the host. The fourth case is about using a third-party volume plugin, Flocker or Convoy, which stores the data in a separate block and even provides reliability with data, even if the container is transferred from one host to another or if the container dies.
Chapter 10, Docker Deployment in a Public Cloud - AWS and Azure, outlines Docker deployment on the Microsoft Azure and AWS public clouds.
What you need for this book
You will need Docker 1.12+ installed on Windows, Mac OS,or Linux machines. Public cloud accounts of AWS, Azure and GCE might be required, which are mentioned in the respective sections of the chapters.
Who this book is for
This book is intended to help seasoned solutions architects, developers, programmers, system engineers, and administrators troubleshoot common areas of Docker containerization. If you are looking to build production-ready Docker containers for automated deployment, you will be able to master and troubleshoot both the basic functions and the advanced features of Docker. Advanced familiarity with the Linux command line syntax, unit testing, the Docker registry, GitHub, and leading container hosting platforms and Cloud Service Providers (CSP) are the prerequisites. In this book you will also learn about ways and means to avoid troubleshooting in the first place.
Conventions
In this book, you will find a number of text styles that distinguish between different kinds of information. Here are some examples of these styles and an explanation of their meaning.
Code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles are shown as follows: "Restart the cluster using the start_k8s.sh shell script."
A block of code is set as follows:
ENTRYPOINT /usr/sbin/sshd -D VOLUME ["/home"] EXPOSE 22 EXPOSE 8080Any command-line input or output is written as follows:
Docker build -t username/my-imagename -f /path/DockerfileNew terms and important words are shown in bold. Words that you see on the screen, for example, in menus or dialog boxes, appear in the text like this: "Specify the Stack name, KeyPair, and cluster 3."
Note
Warnings or important notes appear in a box like this.
Tip
Tips and tricks appear like this.
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Chapter 1. Understanding Container Scenarios and an Overview of Docker
Docker is one of the most recent successful open source projects which provides the packaging, shipping, and running of any application as lightweight containers. We can actually compare Docker containers to shipping containers that provide a standard, consistent way of shipping any application. Docker is a fairly new project and with the help of this book it will be easy to troubleshoot some of the common problems which Docker users face while installing and using Docker containers.
In this chapter, the emphasis will be on the following topics:
Decoding containers
Containerization is an alternative to a virtual machine, which involves the encapsulation of applications and providing it with its own operating environment. The basic foundation for containers is Linux Containers (LXC) which is a user space interface for Linux kernel containment features. With the help of powerful API and simple tools, it lets Linux users create and manage application containers. LXC containers are in-between chroot and a fully-fledged virtual machine. Another key difference between containerization and traditional hypervisors is that containers share the Linux kernel used by the operating system running the host machine, thus multiple containers running in the same machine use the same Linux kernel. It gives the advantage of being fast with almost zero performance overhead compared to VMs.
Major use cases of containers are listed in the following sections.
OS containers
OS containers can be easily imagined as a Virtual Machine (VM) but unlike a VM they share the kernel of the host operating system but provide user space isolation. Similar to a VM, dedicated resources can be assigned to containers and we can install, configure, and run different applications, libraries, and so on, just as you would run on any VM. OS containers are helpful in case of scalability testing where a fleet of containers can be deployed easily with different flavors of distros, which is much less expensive compared to the deployment of VMs. Containers are created from templates or images that determine the structure and contents of the container. It allows you to create a container with the identical environment, same package version, and configuration across all containers mostly used in the case of development environment setups.
There are various container technologies such as LXC, OpenVZ, Docker, and BSD jails which are suitable for OS containers:
An OS-based container
Application containers
Application containers are designed to run a single service in the package, while OS containers which were explained previously, can support multiple processes. Application containers are attracting a lot of attraction after the launch of Docker and Rocket.
Whenever a container is launched, it runs a single process. This process runs an application process, but in the case of OS containers it runs multiple services on the same OS. Containers usually have a layered approach as in the case of Docker containers, which helps with reduced duplication and increased re-use. Containers can be started with a base image common to all components and then we can go on adding layers in the file system that are specific to the component. A layered file system helps to rollback changes as we can simply switch to old layers if required. The run command which is specified in Dockerfile adds a new layer for the container.
The main purpose of application containers is to package different components of the application in separate containers. The different components of the application are packaged separately in containers then they interact with help of APIs and services. The distributed multi-component system deployment is the basic implementation of microservice architecture. In the preceding approach, a developer gets the freedom to package the application as per their requirement and the IT team gets the privilege to deploy the container on multiple platforms in order to scale the system both horizontally as well as vertically:
Note
A hypervisor is a Virtual Machine Monitor (VMM), used to allow multiple operating systems to run and share the hardware resources from the host. Each virtual machine is termed as a guest machine.
Docker layers
The following simple example explains the difference between application containers and OS containers:
Let's consider the example of web three-tier architecture. We have a database tier such as MySQL or Nginx for load balancing and the application tier is Node.js:
An OS container
In the case of an OS container, we can pick up by default Ubuntu as the base container and install services MySQL, nginx, and Node.js using Dockerfile. This type of packaging is good for a testing or development setup where all the services are packaged together and can be shipped and shared across developers. But deploying this architecture for production cannot be done with OS containers as there is no consideration of data scalability and isolation. Application containers help to meet this use case as we can scale the required component by deploying more application-specific containers and it also helps to meet load balancing and recovery use cases. For the previous three-tier architecture, each of the services will be packaged into separate containers in order to fulfill the architecture deployment use case:
Application containers scaled up
The main differences between OS and application containers are:
OS Container
Application Container
Meant to run multiple services on the same OS container
Meant to run a single service
Natively, no layered filesystem
Layered filesystem
Example: LXC, OpenVZ, BSD Jails
Example: Docker, Rocket
Diving into Docker
Docker is a container implementation that has gathered enormous interest in recent years. It neatly bundles various Linux kernel features and services such as namespaces, cgroups, SELlinux, AppArmor profiles, and so on, with Union file systems such as AUFS and BTRFS to make modular images. These images provide highly configurable virtualized environments for applications and follow the write-once-run-anywhere principle. An application can be as simple as running a process to having highly scalable and distributed processes working together.
Docker is gaining a lot of traction in the industry because of its performance savvy and universally replicable architecture, meanwhile providing the following four cornerstones of modern application development:
Furthermore, wide-scale adaptation of Thoughtworks's microservices architecture or Lots of Small Applications (LOSA) is further bringing potential to Docker technology. As a result, big companies such as Google, VMware, and Microsoft have already ported Docker to their infrastructure, and the momentum is continued with the launch of myriad of Docker start-ups namely Tutum, Flocker, Giantswarm, and so on.
Since Docker containers replicate their behavior anywhere, be it your development machine, a bare-metal server, virtual machine, or data center, application designers can focus their attention on development, while operational semantics are left to DevOps. This makes team workflow modular, efficient, and productive. Docker is not to be confused with VM, even though they are both virtualization technologies. Where Docker shares an OS, meanwhile providing a sufficient level of isolation and security to applications running in containers, it later completely abstracts out OS and gives strong isolation and security guarantees. But Docker's resource footprint is minuscule in comparison to VM, and hence preferred for economy and performance. However, it still cannot completely replace VM, and the usage of container is complementary to VM technology:
VM and Docker architecture
Advantages of Docker containers
Following are some of the advantages of using Docker containers in microservice architecture:
Docker lifecycle
These are some of the basic steps involved in the lifecycle of a Docker container:
Tag name can be added in following way:
Docker build -t username/my-imagename .If Dockerfile exists at a different path then the Docker build command can be executed by providing -f flag:
Docker build -t username/my-imagename -f /path/DockerfileAfter the image creation, in order to deploy the container Docker run can be used. The running containers can be checked with the help of the Docker ps command, which lists the currently active containers. There are two more commands to be discussed:The Docker lifecycle
Docker design patterns
Listed here are eight Docker design patterns with examples. Dockerfile is the base structure from which we define a Docker image, it contains all the commands to assemble an image. Using the Docker build command, we can create an automated build that executes all the preceding mentioned command-line instructions to create an image:
$ Docker buildSending build context to Docker daemon 6.51 MB...
