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Docker

Important Resources must read before docker tutorial:

A beginner friendly introduction to containers VMs and docker

Docker Tutorial with python

  • Why DOCKER?

    • An application is working fine on developer console but not in testing or in production.

    • In Dev there can be a software which is updated but in testing and production an older version is being used.

    • Docker is a computer program/tool that makes it easier to deploy and run applications using a concept known as “containerization”.

    • Imagine as a developer your application is packaged up with all of the parts it needs, such as libraries and other dependencies, and it is shipped out as one package

    • Docker in other words is a light weight virtualization tool and containerizing platform where you can run and deploy applications and its dependencies which can be run in a Linux environment.

    • Docker is an open-source project based on Linux containers. It uses Linux Kernel features like namespaces and control groups to create containers on top of an operating system.

  • Docker Engine

    • Docker engine is the layer on which Docker runs. It’s a lightweight runtime and tooling that manages containers, images, builds, and more. It runs natively on Linux systems and is made up of:
        1. A Docker Daemon that runs in the host computer.
        1. A Docker Client that then communicates with the Docker Daemon to execute commands.
        1. A REST API for interacting with the Docker Daemon remotely.

  • Docker Client

    • The Docker Client is what you, as the end-user of Docker, communicate with. Think of it as the UI for Docker.

  • Docker Daemon

    • The Docker daemon is what actually executes commands sent to the Docker Client — like building, running, and distributing your containers. The Docker Daemon runs on the host machine, but as a user, you never communicate directly with the Daemon. The Docker Client can run on the host machine as well, but it’s not required to. It can run on a different machine and communicate with the Docker Daemon that’s running on the host machine.

  • Volumes

    • Volumes are the “data” part of a container, initialized when a container is created. Volumes allow you to persist and share a container’s data. Data volumes are separate from the default Union File System and exist as normal directories and files on the host filesystem. So, even if you destroy, update, or rebuild your container, the data volumes will remain untouched. When you want to update a volume, you make changes to it directly. (As an added bonus, data volumes can be shared and reused among multiple containers, which is pretty neat.)

  • Microservice Architecture :

    • The idea behind microservice is some application is easier to build and maintain where broken down to smaller parts.

    • Each component is developed separately and done....

    • Example : Online Shopping Service :

      • Account Service
      • Product Catalog
      • Cart Server
      • Order Server

  • Advantages of microservice architecture :

    • Building and maintenance is easy as broken down to smaller parts.
    • If we need some new features or update in a module, it is easier because dependencies will be less compared to the application as a whole.
    • If any component go down, application will be largely unaffected.

  • What is the problem to adopting microservices :

    • Before DOCKER : For microservice architecture we have a host machine and there are several virtual machines each virtual machine is for a microservice. So problem is that lots of resource waste. As we use more and more VMs for bigger application lots of disc space, RAM are unused.

  • How Docker solve this problem :

    • We can run several microservices in one virtual machine by running various docker
    • containers for each microservice.
    • Docker do not need any RAM,DISK requirements initially.

  • How Docker solves the problem "not having consistent computing environment throughout the process of delivery (development, testing, production)" :

    • Docker containers are developed by the developers.
    • Docker provides a consistent computing environment throughout the whole SDLC (Software Development Life Cycle).

  • What is an Image?

    • Docker image is the basis of containers. It’s a collection of layers stacked on top of each other. Each Docker image references a list of read-only layers that represent filesystem differences. Think of it like the jar file for java applications, you create one jar file but you can deploy it anywhere a java run time is enabled.

    • A docker image is an archive containing all the files that go in a container.

    • You can create many docker containers from the same docker image.

    • The image can then be deployed to any Docker environment and executable as a container.

    • A Docker image is containing everything needed to run an application as a container. This includes:

      • code
      • runtime
      • libraries
      • environment variables
      • configuration files

      docker image

  • What is a container?

    • A container is a standard unit of software that packages up code and all its dependencies so the application runs quickly and reliably from one computing environment to another.

    • A docker container image is s lightweight, standalone, executable package of software that includes everything needed to run an application: code, libraries, settings etc.

    • Container images become containers at runtime and in the case of docker containers images become containers when they run on docker engine.

    • Containers share the machine's OS system kernel and therefore do not require an OS per application.

    • Applications are safer in containers and Docker provides the strongest default isolation capabilities in the industry.

    • Docker container is the actual running piece created from a docker image. The only difference between a docker image and a docker container is a top writable layer. When you create a new container, you add a new, thin, writable layer on top of the underlying stack. This layer is often called the “container layer”. All changes made to the running container — such as writing new files, modifying existing files, and deleting files — are written to this thin writable container layer. But once you delete the container, this top layer will be deleted as well. So it’s not persistent. The best thing with docker is that you can create a docker image using the current docker container with a commit. Hence, enabling us to capture system information and make it immutable so its reproducible anywhere. This solves many of the server related problems we encounter these days.

    Docker container

  • Containers Vs VM

    • When talking about containerization it is very often compared to virtual machines. Let’s take a look at the following image to see the main difference :

    • The Docker container platform is always running on top of the host operating system. Containers are containing the binaries, libraries, and the application itself. Containers do not contain a guest operating system which ensures that containers are lightweight.

    -In contrast virtual machines are running on a hypervisor (responsible for running virtual machines) and include it’s own guest operating system. This increased the size of the virtual machines significantly, makes setting up virtual machines more complex and requires more resources to run each virtual machine.

    container vs VM

  • Dockerfile

    • Blueprint of a docker image (a text document) is known as Dockerfile. This file contains all the commands you would run in order to build the docker image you want. Docker can build images reading this file, which is one of the key advantages of docker.
    # Super simple example of a Dockerfile
FROM ubuntu:latest
MAINTAINER Tikam Alma 

RUN apt-get update
RUN apt-get install -y python python-pip wget
RUN pip install Flask

ADD hello.py /home/hello.py

WORKDIR /home
    • We first write a Dockerfile which is like the definition of the image. Using the Dockerfile we create a docker image. We then push this image to Docker Hub and provide a unique tag that can be used to identify our image. Using this tag and image name, we can pull the docker image and deploy on another computer as a docker container.

Working of Containers Deep-Dive

  • The term “container” is really just an abstract concept to describe how a few different features work together to visualize a “container”. Let’s run through them real quick:
    1. Namespaces

    • Namespaces provide containers with their own view of the underlying Linux system, limiting what the container can see and access. When you run a container, Docker creates namespaces that the specific container will use.

    • There are several different types of namespaces in a kernel that Docker makes use of, for example:

      • a. NET: Provides a container with its own view of the network stack of the system (e.g. its own network devices, IP addresses, IP routing tables, /proc/net directory, port numbers, etc.).

      • b. PID: PID stands for Process ID. If you’ve ever ran ps aux in the command line to check what processes are running on your system, you’ll have seen a column named “PID”. The PID namespace gives containers their own scoped view of processes they can view and interact with, including an independent init (PID 1), which is the “ancestor of all processes”.

      • c. MNT: Gives a container its own view of the “mounts” on the system. So, processes in different mount namespaces have different views of the filesystem hierarchy.

      • d. UTS: UTS stands for UNIX Timesharing System. It allows a process to identify system identifiers (i.e. hostname, domainname, etc.). UTS allows containers to have their own hostname and NIS domain name that is independent of other containers and the host system.

      • e. IPC: IPC stands for InterProcess Communication. IPC namespace is responsible for isolating IPC resources between processes running inside each container.

      • f. USER: This namespace is used to isolate users within each container. It functions by allowing containers to have a different view of the uid (user ID) and gid (group ID) ranges, as compared with the host system. As a result, a process’s uid and gid can be different inside and outside a user namespace, which also allows a process to have an unprivileged user outside a container without sacrificing root privilege inside a container.

    1. Control groups
      • Control groups (also called cgroups) is a Linux kernel feature that isolates, prioritizes, and accounts for the resource usage (CPU, memory, disk I/O, network, etc.) of a set of processes. In this sense, a cgroup ensures that Docker containers only use the resources they need — and, if needed, set up limits to what resources a container can use. Cgroups also ensure that a single container doesn’t exhaust one of those resources and bring the entire system down.
    1. Isolated Union file system:

      • Docker uses Union File Systems to build up an image. You can think of a Union File System as a stackable file system, meaning files and directories of separate file systems (known as branches) can be transparently overlaid to form a single file system.

      • The contents of directories which have the same path within the overlaid branches are seen as a single merged directory, which avoids the need to create separate copies of each layer. Instead, they can all be given pointers to the same resource; when certain layers need to be modified, it’ll create a copy and modify a local copy, leaving the original unchanged. That’s how file systems can appear writable without actually allowing writes. (In other words, a “copy-on-write” system.)

      • Layered systems offer two main benefits:

          1. Duplication-free: layers help avoid duplicating a complete set of files every time you use an image to create and run a new container, making instantiation of docker containers very fast and cheap.
          1. Layer segregation: Making a change is much faster — when you change an image, Docker only propagates the updates to the layer that was changed.