Containerization using docker and its applications

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Why the buzz around Containers and
Docker?
•The software industry has changed
•Before:
• monolithic applications
• long development cycles
• single environment
• slowly scaling up
•Now:
• decoupled services
• fast, iterative improvements
• multiple environments
• quickly scaling out

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Deployment becomes very complex
•Many different stacks:
• languages
• frameworks
• Databases
•Many different targets:
• individual development environments
• pre-production, QA, staging...
• production: on prem, cloud, hybrid

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Analogy with the shipping industry

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Intermodal shipping containers

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A shipping container system for applications

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Results
•Dev-to-prod reduced from 9 months to 15 minutes (ING)
•Continuous integration job time reduced by more than 60% (BBC)
•Deploy 100 times a day instead of once a week (GILT)
•70% infrastructure consolidation (MetLife)
•60% infrastructure consolidation (Intesa Sanpaolo)
•14x application density; 60% of legacy datacenter migrated in 4 months (GE
Appliances)
•etc.

History and Multi-Dimensional Evolution of Computing
Development Process Application Architecture Deployment and Packaging Application Infrastructure
Waterfall Monolithic Physical Server Datacenter
Agile N-Tier Virtual Servers Hosted
DevOps Microservices Containers Cloud

Virtualization
http://www.edureka.co/devops
Virtualization means to create a virtual version of a device or resource, such as a storage device,
server, network, an OS, hardware, etc. where the framework divides the resource into one or more
execution environments.
 Partitioning a hard drive is considered virtualization because one drive is partitioned to create two
separate hard drives
 Devices, applications and human users are able to interact with the virtual resource as if it were a real
single logical resource
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Virtual Machines vs. Containers - Architecture
Virtual Machines
● Each virtual machine (VM)
includes the app, the
necessary binaries and
libraries and an entire guest
operating system
Containers
● Containers include the app & all of its dependencies,
but share the kernel with other containers.
● Run as an isolated process in userspace on the host OS
● Not tied to any specific infrastructure – containers run
on any computer, infrastructure and cloud.
VMs
Containers
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Virtual Machines vs. Containers – Key differences

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Virtual Machines vs. Containers - Size

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What is Docker?
Docker is an Open platform for developers and sysadmins to build, ship and run
distributed applications.
It can run on most Linux distributions, Windows and Mac OS running Docker Engine
(Toolbox).
It is supported by most of cloud providers and provide a popular Dev/Test, CI &
DevOps platform for many use cases.

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First Public release of Docker
•March 2013, PyCon, Santa Clara:
"Docker" is shown to a public audience for the first time.
•It is released with an open source license.
•Very positive reactions and feedback!
•The dotCloud team progressively shifts to Docker development.
•The same year, dotCloud changes name to Docker.

Docker Architecture
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• Docker Engine – Docker Daemon,
REST API, CLI.
• Docker client – Command Line Interface
(CLI) for interfacing with the Docker
• Image – Hierarchies of files built from a
Dockerfile, the file used as input to the
docker build command
• Container – Running instance of an Image
using the docker run command
• Dockerfile – Text file of Docker instructions
used to assemble a Docker Image
• Docker Hub (Registry) – Image repository

Docker Engine
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Docker Engine is a client-server application with these major components:
•A server which is a type of long-running program called a daemon process (the dockerd command).
•A REST API which specifies interfaces that programs can use to talk to the daemon and instruct it what to do.
•A command line interface (CLI) client (the docker command).

Docker Images
Source: Docker docs and https://docs.docker.com/glossary/
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•Image = files + metadata
•These files form the root filesystem of our container.
•The metadata can indicate a number of things, e.g.:
• the author of the image
• the command to execute in the container when
starting it
• environment variables to be set
• etc.
•Images are made of layers, conceptually stacked on top
of each other.
•Each layer can add, change, and remove files and/or
metadata.
•Images can share layers to optimize disk usage, transfer
times, and memory use.

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Docker Image vs Container
•An image is a read-only filesystem.
•A container is an encapsulated set of processes.
•Running in a read-write copy of that file system.
docker run command starts a container from a given image.

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Analogy with Object oriented programming
• Images are conceptually similar to classes.
• Layers are conceptually similar to inheritance.
• Containers are conceptually similar to instances.

How to change an Image
If an image is read-only, how do we change it?
•We create a new container from that image.
•Then we make changes to that container.
•When we are satisfied with those changes, we transform them into a new layer.
•A new image is created by stacking the new layer on top of the old image.

Creating images
docker build
Performs a repeatable build sequence.
•This is the preferred method!
docker commit
•Saves all the changes made to a container into a new layer.
•Creates a new image (effectively a copy of the container).

Image namespaces
There are three namespaces:
•Root namespace for Official images
e.g. ubuntu, busybox...
•User namespace for User (and organizations) images
e.g. jpetazzo/clock
•Self-hosted namespace for Self-hosted images
e.g. registry.example.com:5000/my-private/image
Let's explain each of them.

Root namespace
The root namespace is for official images.
They are gated by Docker Inc.
They are generally authored and maintained by third parties.
Those images include:
•Small images like busybox.
•Images to be used as bases for your builds like ubuntu, fedora...
•Ready-to-use components and services, like redis, postgresql...
•Over 150 such images are there at this point!

User namespace
The user namespace holds images for Docker Hub users and organizations.
For example:
jpetazzo/clock
The Docker Hub user is:
Jpetazzo
The image name is:
clock

Self-hosted namespace
This namespace holds images which are not hosted on Docker Hub, but on third party registries.
They contain the hostname (or IP address), and optionally the port, of the registry server.
For example:
localhost:5000/wordpress
•localhost:5000 - host and port of the registry
•wordpress - name of the image

Store and manage images
Images can be stored:
•On your Docker host.
•In a Docker registry.
You can use the Docker client to download or upload images.
docker pull - to download image
docker push - to upload image

Tag images
•Images can have tags.
•Tags define image versions or variants.
docker pull ubuntu is equivalent to docker pull
ubuntu:latest
•The :latesttag is generally updated often.

When to (not to) use tags
Don't specify tags:
•When doing rapid testing and prototyping.
•When experimenting.
•When you want the latest version.
Do specify tags:
•When going to production.
•To ensure that the same version will be used everywhere.
•To ensure repeatability later.

Lab1
Docker Install
&
basic commands

Docker Install
Installation process for Docker on Ubuntu 16.04 machine.
1.Install required Packages
sudo apt-get install curl apt-transport-https ca-certificates software-properties-common
2. Setup Docker repository
curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo apt-key add -
sudo add-apt-repository "deb [arch=amd64] https://download.docker.com/linux/ubuntu $(lsb_release -cs)
stable“
3. Install Docker On Ubuntu
sudo apt-get update
sudo apt-get install -y docker-ce
sudo systemctl status docker

Docker CLI – Common / useful commands
• docker pull : pull images/volumes from Docker Registry.
• docker images : list all images on the local volume.
• docker run : run docker image.
• docker ps : list running docker containers (analogous to ps).
• docker ps –a : list all containers including not running.
• docker logs : show log data for a running or stopped container.
• docker rm : remove/delete a container | docker rmi : remove/delete an image.
• docker tag : name a docker image.
• docker build : build docker image from Dockerfile.
• docker login : login to registry.
• docker push : push images/volumes to Docker Registry.
• docker inspect : return container run time configuration parameter metadata.
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Hello World
In your Docker environment, just run the following command:
$ docker run busybox echo hello world
hello world
(If your Docker install is brand new, you will also see a few extra lines, corresponding to the download
of the busybox image.)

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A more useful container
• This is a brand new container.
• It runs a bare-bones, no-frills ubuntu system.
• -it is shorthand for -i -t.
o -i tells Docker to connect us to the container's stdin. (interactive mode)
o -t tells Docker that we want a pseudo-terminal. (tty)

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A more useful container
Try to run figlet in our container.
Alright, we need to install it.

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Do something in our container

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Try to run installed program “figlet”

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Comparing the container and the host
Exit the container by logging out of the shell, with ^D or exit.
Now try to run figlet. Does that work?
(It shouldn't; except if, by coincidence, you are running on a machine where figlet was installed
before.)

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Where is my container
•Can we reuse that container that we took time to customize?
We can, but that's not the default workflow with Docker.
•What's the default workflow, then?
Always start with a fresh container.
If we need something installed in our container, build a custom image.
•That seems complicated!
We'll see that it's actually pretty easy!
•And what's the point?
This puts a strong emphasis on automation and repeatability. Let's see why ...

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Pets Vs Cattle
• In the "pets vs. cattle" metaphor, there are two kinds of servers.
Pets:
o have distinctive names and unique configurations
o when they have an outage, we do everything we can to fix them
o Examples are : Oracle VirtualBox and VMWare
• Cattle:
o have generic names (e.g. with numbers) and generic configuration
o configuration is enforced by configuration management, golden images ...
o when they have an outage, we can replace them immediately with a new server
o Examples are : Docker and Kubernetes
• What's the connection with Docker and containers?

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Local development environments
• When we use local VMs (with e.g. VirtualBox or VMware), our workflow looks like this:
o create VM from base template (Ubuntu, CentOS...)
o install packages, set up environment
o work on project
o when done, shut down VM
o next time we need to work on project, restart VM as we left it
o if we need to tweak the environment, we do it live
• Over time, the VM configuration evolves, diverges.
• We don't have a clean, reliable, deterministic way to provision that environment.

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Local development with Docker
• With Docker, the workflow looks like this:
o create container image with our dev environment
o run container with that image
o work on project
o when done, shut down container
o next time we need to work on project, start a new container
o if we need to tweak the environment, we create a new image
• We have a clear definition of our environment, and can share it reliably with others.

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Objectives
Our first containers were interactive.
We will now see how to:
• Run a non-interactive container.
• Run a container in the background.
• List running containers.
• Check the logs of a container.
• Stop a container.
• List stopped containers.

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A non-interactive container

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Run a container in the background

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Viewing only the last container started

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Viewing only the IDs of the containers

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View the logs of a container

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View only the tail of the logs of a container

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Follow the logs in real time

Some more options to run a container
docker run [OPTIONS] IMAGE [COMMAND] [ARG...]
• Examples:
docker run hello-world # install and run hello-world
(foreground mode by default)
docker run -it ubuntu /bin/bash # run ubuntu container and log into it.
docker run -d -p 9090:80 -t <image id> # -d : detached mode
# -p : port forwarding 9090 -> host
80 -> container
docker exec -it <container id> /bin/bash #login to running container
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Docker Container Lifecycle
– Conception
• BUILD an Image from a Dockerfile
– Birth
• RUN (create+start) a container
– Reproduction
• COMMIT (persist) a container to a new image
• RUN a new container from an image
– Sleep
• KILL a running container
– Wake
• START a stopped container
– Death
• RM (delete) a stopped container
– Extinction
• RMI a container image (delete image)
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Build Docker Images - Dockerfile

Dockerfile
• Like a Makefile (shell script)
• Extends from a Base Image
• Results in a new Docker Image
•A Docker file lists the steps needed to build an images
• docker build command is used to run a Docker file
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Writing our first Dockerfile
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Our Dockerfile must be in a new, empty directory.
• Create a directory to hold our Dockerfile.
$ mkdir MyDockerFile
• Create a Dockerfile inside this directory.
$ cd MyDockerFile
$ vi Dockerfile

Dockerfile build output – sending build context to Docker Daemon
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Dockerfile build output – execution steps
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Using JSON syntax in Dockerfile
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When to use JSON syntax and string syntax
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Dockerfile – CMD and ENTRYPOINT
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These commands allow us to set the default command to run in a container.

Dockerfile with CMD and ENTRYPOINT
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Lab2
Setup website using Nginx
(refer github for code : static-site)

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Containerizing an application using dockerfile
Example Static Site Dockerfile
FROM nginx
COPY wrapper.sh /
COPY html /usr/share/nginx/html
CMD ["./wrapper.sh"]
Docker build image CLI example
$ docker build -t static-site:1.0 .
NOTE: The “.” references Dockerfile in local directory

Excellent Use Cases for Containers
Ready to Run Application Stacks
– Excellent for Dev/Test setups
– Deployment in Seconds, not Hours/Days
– Start Up, Tear Down Quickly
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One-Time Run Jobs and Analytics
– Run the Job / Analysis and quit
Front-End App Servers
– Highly horizontally scalable
– Fast A/B, Rolling Deployments
– Traditional Technologies - MW/Backend
New App Dev & Microservices
– Refactor all or part of legacy app
– Containers are great for Microservices Server Density
– Containers can use dynamic ports
– Run many of the same app on a server
• instead of one per VM

Docker Compose
• Docker Compose
– Docker Tool for defining and running multi-container Docker applications
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Deploy application using Docker Compose
• $ docker-compose up -d
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Lab3
Setup Wordpress site using docker compose
(refer github for code : docker-compose)

5. Create The WordPress Site:
##############################################
#sudo vi docker-compose.yml
---
---
##############################################
6. Now start the application group:
docker-compose up -d
7. Now, in the browser go to port 8080, using your public IP or host name, as shown below
localhost:8080 # Fill this form and click on install WordPress.
8. Now visit your server’s IP address again to port 8181 this time. You’ll be greeted by the phpMyAdmin login
screen:
localhost:8181

Docker Hub
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• Docker Inc.
– Repository
– public and private images
• Enables images to be shared and
moved off the laptop
• Example usage:
– $ docker tag docker-whale:latest username/docker-whale:latest
– $ docker push username/docker-whale:latest
– $ docker pull username/docker-whale:latest

Docker Swarm
• Docker Swarm is a technique to create and maintain a cluster
of Docker Engines.
• The Docker engines can be hosted on different nodes, and these
nodes, which are in remote locations, form a Cluster
when connected in Swarm mode.
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Containerization using docker and its applications

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