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promptlyspeedyandroid · 16 days ago

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Docker Tutorial for Beginners: Learn Docker Step by Step

What is Docker?

Docker is an open-source platform that enables developers to automate the deployment of applications inside lightweight, portable containers. These containers include everything the application needs to run—code, runtime, system tools, libraries, and settings—so that it can work reliably in any environment.

Before Docker, developers faced the age-old problem: “It works on my machine!” Docker solves this by providing a consistent runtime environment across development, testing, and production.

Why Learn Docker?

Docker is used by organizations of all sizes to simplify software delivery and improve scalability. As more companies shift to microservices, cloud computing, and DevOps practices, Docker has become a must-have skill. Learning Docker helps you:

Package applications quickly and consistently

Deploy apps across different environments with confidence

Reduce system conflicts and configuration issues

Improve collaboration between development and operations teams

Work more effectively with modern cloud platforms like AWS, Azure, and GCP

Who Is This Docker Tutorial For?

This Docker tutorial is designed for absolute beginners. Whether you're a developer, system administrator, QA engineer, or DevOps enthusiast, you’ll find step-by-step instructions to help you:

Understand the basics of Docker

Install Docker on your machine

Create and manage Docker containers

Build custom Docker images

Use Docker commands and best practices

No prior knowledge of containers is required, but basic familiarity with the command line and a programming language (like Python, Java, or Node.js) will be helpful.

What You Will Learn: Step-by-Step Breakdown

1. Introduction to Docker

We start with the fundamentals. You’ll learn:

What Docker is and why it’s useful

The difference between containers and virtual machines

Key Docker components: Docker Engine, Docker Hub, Dockerfile, Docker Compose

2. Installing Docker

Next, we guide you through installing Docker on:

Windows

macOS

Linux

You’ll set up Docker Desktop or Docker CLI and run your first container using the hello-world image.

3. Working with Docker Images and Containers

You’ll explore:

How to pull images from Docker Hub

How to run containers using docker run

Inspecting containers with docker ps, docker inspect, and docker logs

Stopping and removing containers

4. Building Custom Docker Images

You’ll learn how to:

Write a Dockerfile

Use docker build to create a custom image

Add dependencies and environment variables

Optimize Docker images for performance

5. Docker Volumes and Networking

Understand how to:

Use volumes to persist data outside containers

Create custom networks for container communication

Link multiple containers (e.g., a Node.js app with a MongoDB container)

6. Docker Compose (Bonus Section)

Docker Compose lets you define multi-container applications. You’ll learn how to:

Write a docker-compose.yml file

Start multiple services with a single command

Manage application stacks easily

Real-World Examples Included

Throughout the tutorial, we use real-world examples to reinforce each concept. You’ll deploy a simple web application using Docker, connect it to a database, and scale services with Docker Compose.

Example Projects:

Dockerizing a static HTML website

Creating a REST API with Node.js and Express inside a container

Running a MySQL or MongoDB database container

Building a full-stack web app with Docker Compose

Best Practices and Tips

As you progress, you’ll also learn:

Naming conventions for containers and images

How to clean up unused images and containers

Tagging and pushing images to Docker Hub

Security basics when using Docker in production

What’s Next After This Tutorial?

After completing this Docker tutorial, you’ll be well-equipped to:

Use Docker in personal or professional projects

Learn Kubernetes and container orchestration

Apply Docker in CI/CD pipelines

Deploy containers to cloud platforms

Conclusion

Docker is an essential tool in the modern developer's toolbox. By learning Docker step by step in this beginner-friendly tutorial, you’ll gain the skills and confidence to build, deploy, and manage applications efficiently and consistently across different environments.

Whether you’re building simple web apps or complex microservices, Docker provides the flexibility, speed, and scalability needed for success. So dive in, follow along with the hands-on examples, and start your journey to mastering containerization with Docker tpoint-tech!

#docker #what is docker #docker tutorial #learn docker #docker for beginner

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qcs01 · 1 year ago

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Ansible and Docker: Automating Container Management

In today's fast-paced tech environment, containerization and automation are key to maintaining efficient, scalable, and reliable infrastructure. Two powerful tools that have become essential in this space are Ansible and Docker. While Docker enables you to create, deploy, and run applications in containers, Ansible provides a simple yet powerful automation engine to manage and orchestrate these containers. In this blog post, we'll explore how to use Ansible to automate Docker container management, including deployment and orchestration.

Why Combine Ansible and Docker?

Combining Ansible and Docker offers several benefits:

Consistency and Reliability: Automating Docker container management with Ansible ensures consistent and reliable deployments across different environments.

Simplified Management: Ansible’s easy-to-read YAML playbooks make it straightforward to manage Docker containers, even at scale.

Infrastructure as Code (IaC): By treating your infrastructure as code, you can version control, review, and track changes over time.

Scalability: Automation allows you to easily scale your containerized applications by managing multiple containers across multiple hosts seamlessly.

Getting Started with Ansible and Docker

To get started, ensure you have Ansible and Docker installed on your system. You can install Ansible using pip: pip install ansible

And Docker by following the official Docker installation guide for your operating system.

Next, you'll need to set up an Ansible playbook to manage Docker. Here’s a simple example:

Example Playbook: Deploying a Docker Container

Create a file named deploy_docker.yml:

---

- name: Deploy a Docker container

hosts: localhost

tasks:

- name: Ensure Docker is installed

apt:

state: present

become: yes

- name: Start Docker service

service:

state: started

enabled: yes

become: yes

- name: Pull the latest nginx image

docker_image:

tag: latest

source: pull

- name: Run a Docker container

docker_container:

image: nginx

state: started

ports:

- "80:80"

In this playbook:

We ensure Docker is installed and running.

We pull the latest nginx Docker image.

We start a Docker container with the nginx image, mapping port 80 on the host to port 80 on the container.

Automating Docker Orchestration

For more complex scenarios, such as orchestrating multiple containers, you can extend your playbook. Here’s an example of orchestrating a simple web application stack with Nginx, a Node.js application, and a MongoDB database:

---

- name: Orchestrate web application stack

hosts: localhost

tasks:

- name: Ensure Docker is installed

apt:

state: present

become: yes

- name: Start Docker service

service:

state: started

enabled: yes

become: yes

- name: Pull necessary Docker images

docker_image:

tag: latest

source: pull

loop:

- nginx

- node

- mongo

- name: Run MongoDB container

docker_container:

image: mongo

state: started

ports:

- "27017:27017"

- name: Run Node.js application container

docker_container:

image: node

state: started

volumes:

- ./app:/usr/src/app

working_dir: /usr/src/app

command: "node app.js"

links:

- mongo

- name: Run Nginx container

docker_container:

image: nginx

state: started

ports:

- "80:80"

volumes:

- ./nginx.conf:/etc/nginx/nginx.conf

links:

- node_app

Conclusion

By integrating Ansible with Docker, you can streamline and automate your container management processes, making your infrastructure more consistent, scalable, and reliable. This combination allows you to focus more on developing and less on managing infrastructure. Whether you're managing a single container or orchestrating a complex multi-container environment, Ansible and Docker together provide a powerful toolkit for modern DevOps practices.

Give it a try and see how much time and effort you can save by automating your Docker container management with Ansible!

For more details click www.qcsdclabs.com

#redhatcourses #information technology #containerorchestration #container #linux #docker #kubernetes #containersecurity #dockerswarm #aws

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tastethelinux · 4 years ago

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How to Install MongoDB on Docker Container linux.

Hi Guys! Hope you are doing well. Let’s Learn about “How to Install MongoDB on Docker Container Linux”. The Docker is an open source platform, where developers can package there application and run that application into the Docker Container. So It is PAAS (Platform as a Service), which uses a OS virtualisation to deliver software in packages called containers. The containers are the bundle of…

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#docker hub #install mongodb #install mongodb docker #install mongodb docker container #install mongodb docker image #install mongodb docker linux #install mongodb docker ubuntu #install mongodb on docker container #mongodb docker install #mongodb docker tutorial #run docker on mongodb container

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hydralisk98 · 5 years ago

Photo

hydralisk98′s web projects tracker:

Core principles=

Fail faster

‘Learn, Tweak, Make’ loop

This is meant to be a quick reference for tracking progress made over my various projects, organized by their “ultimate target” goal:

(START)

(Website)=

Install Firefox

Install Chrome

Install Microsoft newest browser

Install Lynx

Learn about contemporary web browsers

Install a very basic text editor

Install Notepad++

Install Nano

Install Powershell

Install Bash

Install Git

Learn HTML

Elements and attributes

Commenting (single line comment, multi-line comment)

Head (title, meta, charset, language, link, style, description, keywords, author, viewport, script, base, url-encode, )

Hyperlinks (local, external, link titles, relative filepaths, absolute filepaths)

Headings (h1-h6, horizontal rules)

Paragraphs (pre, line breaks)

Text formatting (bold, italic, deleted, inserted, subscript, superscript, marked)

Quotations (quote, blockquote, abbreviations, address, cite, bidirectional override)

Entities & symbols (&entity_name, &entity_number, &nbsp, useful HTML character entities, diacritical marks, mathematical symbols, greek letters, currency symbols, )

Id (bookmarks)

Classes (select elements, multiple classes, different tags can share same class, )

Blocks & Inlines (div, span)

Computercode (kbd, samp, code, var)

Lists (ordered, unordered, description lists, control list counting, nesting)

Tables (colspan, rowspan, caption, colgroup, thead, tbody, tfoot, th)

Images (src, alt, width, height, animated, link, map, area, usenmap, , picture, picture for format support)

old fashioned audio

old fashioned video

Iframes (URL src, name, target)

Forms (input types, action, method, GET, POST, name, fieldset, accept-charset, autocomplete, enctype, novalidate, target, form elements, input attributes)

URL encode (scheme, prefix, domain, port, path, filename, ascii-encodings)

Learn about oldest web browsers onwards

Learn early HTML versions (doctypes & permitted elements for each version)

Make a 90s-like web page compatible with as much early web formats as possible, earliest web browsers’ compatibility is best here

Learn how to teach HTML5 features to most if not all older browsers

Install Adobe XD

Learn Adobe XD basics

Learn Figma basics

Install Microsoft’s VS Code

Install my Microsoft’s VS Code favorite extensions

Learn HTML5

Semantic elements

Layouts

Graphics (SVG, canvas)

Track

Audio

Video

Embed

APIs (geolocation, drag and drop, local storage, application cache, web workers, server-sent events, )

HTMLShiv for teaching older browsers HTML5

HTML5 style guide and coding conventions (doctype, clean tidy well-formed code, lower case element names, close all html elements, close empty html elements, quote attribute values, image attributes, space and equal signs, avoid long code lines, blank lines, indentation, keep html, keep head, keep body, meta data, viewport, comments, stylesheets, loading JS into html, accessing HTML elements with JS, use lowercase file names, file extensions, index/default)

Learn CSS

Selections

Colors

Fonts

Positioning

Box model

Grid

Flexbox

Custom properties

Transitions

Animate

Make a simple modern static site

Learn responsive design

Viewport

Media queries

Fluid widths

rem units over px

Mobile first

Learn SASS

Variables

Nesting

Conditionals

Functions

Learn about CSS frameworks

Learn Bootstrap

Learn Tailwind CSS

Learn JS

Fundamentals

Document Object Model / DOM

JavaScript Object Notation / JSON

Fetch API

Modern JS (ES6+)

Learn Git

Learn Browser Dev Tools

Learn your VS Code extensions

Learn Emmet

Learn NPM

Learn Yarn

Learn Axios

Learn Webpack

Learn Parcel

Learn basic deployment

Domain registration (Namecheap)

Managed hosting (InMotion, Hostgator, Bluehost)

Static hosting (Nertlify, Github Pages)

SSL certificate

FTP

SFTP

SSH

CLI

Make a fancy front end website about

Make a few Tumblr themes

===You are now a basic front end developer!

Learn about XML dialects

Learn XML

Learn about JS frameworks

Learn jQuery

Learn React

Contex API with Hooks

Learn Vue.js

Vuex

NUXT

Learn Svelte

NUXT (Vue)

Learn Gatsby

Learn Gridsome

Learn Typescript

Make a epic front end website about

===You are now a front-end wizard!

Learn Node.js

Express

Nest.js

Koa

Learn Python

Django

Flask

Learn GoLang

Revel

Learn PHP

Laravel

Slim

Symfony

Learn Ruby

Ruby on Rails

Sinatra

Learn SQL

PostgreSQL

MySQL

Learn ORM

Learn ODM

Learn NoSQL

MongoDB

RethinkDB

CouchDB

Learn a cloud database

Firebase, Azure Cloud DB, AWS

Learn a lightweight & cache variant

Redis

SQLlite

NeDB

Learn GraphQL

Learn about CMSes

Learn Wordpress

Learn Drupal

Learn Keystone

Learn Enduro

Learn Contentful

Learn Sanity

Learn Jekyll

Learn about DevOps

Learn NGINX

Learn Apache

Learn Linode

Learn Heroku

Learn Azure

Learn Docker

Learn testing

Learn load balancing

===You are now a good full stack developer

Learn about mobile development

Learn Dart

Learn Flutter

Learn React Native

Learn Nativescript

Learn Ionic

Learn progressive web apps

Learn Electron

Learn JAMstack

Learn serverless architecture

Learn API-first design

Learn data science

Learn machine learning

Learn deep learning

Learn speech recognition

Learn web assembly

===You are now a epic full stack developer

Make a web browser

Make a web server

===You are now a legendary full stack developer

[...]

(Computer system)=

Learn to execute and test your code in a command line interface

Learn to use breakpoints and debuggers

Learn Bash

Learn fish

Learn Zsh

Learn Vim

Learn nano

Learn Notepad++

Learn VS Code

Learn Brackets

Learn Atom

Learn Geany

Learn Neovim

Learn Python

Learn Java?

Learn R

Learn Swift?

Learn Go-lang?

Learn Common Lisp

Learn Clojure (& ClojureScript)

Learn Scheme

Learn C++

Learn C

Learn B

Learn Mesa

Learn Brainfuck

Learn Assembly

Learn Machine Code

Learn how to manage I/O

Make a keypad

Make a keyboard

Make a mouse

Make a light pen

Make a small LCD display

Make a small LED display

Make a teleprinter terminal

Make a medium raster CRT display

Make a small vector CRT display

Make larger LED displays

Make a few CRT displays

Learn how to manage computer memory

Make datasettes

Make a datasette deck

Make floppy disks

Make a floppy drive

Learn how to control data

Learn binary base

Learn hexadecimal base

Learn octal base

Learn registers

Learn timing information

Learn assembly common mnemonics

Learn arithmetic operations

Learn logic operations (AND, OR, XOR, NOT, NAND, NOR, NXOR, IMPLY)

Learn masking

Learn assembly language basics

Learn stack construct’s operations

Learn calling conventions

Learn to use Application Binary Interface or ABI

Learn to make your own ABIs

Learn to use memory maps

Learn to make memory maps

Make a clock

Make a front panel

Make a calculator

Learn about existing instruction sets (Intel, ARM, RISC-V, PIC, AVR, SPARC, MIPS, Intersil 6120, Z80...)

Design a instruction set

Compose a assembler

Compose a disassembler

Compose a emulator

Write a B-derivative programming language (somewhat similar to C)

Write a IPL-derivative programming language (somewhat similar to Lisp and Scheme)

Write a general markup language (like GML, SGML, HTML, XML...)

Write a Turing tarpit (like Brainfuck)

Write a scripting language (like Bash)

Write a database system (like VisiCalc or SQL)

Write a CLI shell (basic operating system like Unix or CP/M)

Write a single-user GUI operating system (like Xerox Star’s Pilot)

Write a multi-user GUI operating system (like Linux)

Write various software utilities for my various OSes

Write various games for my various OSes

Write various niche applications for my various OSes

Implement a awesome model in very large scale integration, like the Commodore CBM-II

Implement a epic model in integrated circuits, like the DEC PDP-15

Implement a modest model in transistor-transistor logic, similar to the DEC PDP-12

Implement a simple model in diode-transistor logic, like the original DEC PDP-8

Implement a simpler model in later vacuum tubes, like the IBM 700 series

Implement simplest model in early vacuum tubes, like the EDSAC

[...]

(Conlang)=

Choose sounds

Choose phonotactics

[...]

(Animation ‘movie’)=

[...]

(Exploration top-down ’racing game’)=

[...]

(Video dictionary)=

[...]

(Grand strategy game)=

[...]

(Telex system)=

[...]

(Pen&paper tabletop game)=

[...]

(Search engine)=

[...]

(Microlearning system)=

[...]

(Alternate planet)=

[...]

(END)

#personal project

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computingpostcom · 3 years ago

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If this is not one of the most robust, free, rich and informative era ever then I cannot think of any other time in history adorned with the wealth of technology as this one. If you would wish to accomplish anything, this era wields the most virile grounds to nourish, nurture and aid the sprouting, the growth and the maturity of your dreams. You can literaly learn to be what you would wish to be in this age. That being said, this disquisition takes on a quest to get you into setting up something similar to Heroku on your own environment. We shall get to know what Heroku is then get off the dock and sail off towards our goal of having such an environment. The proliferation of cloud technologies brought with it many opportunities in terms of service offerings. First and foremost, users had the ability to get as much infrastructure as they could afford. Users can spawn servers, storage and network resources ad libitum which is popularly known as Infrastructure as a service. Then comes the second layer that sits on the infrastructure. It could be anything, cloud identity service, cloud monitoring server et cetera. This layer provides ready made solutions to people who might need them. This is known as software as a service. I hope we are flowing together this far. In addition to that there is another incredible layer that is the focus of this guide. It is a layer that targets developers majorly by making their lives easier on the cloud. In this layer , developers only concentrate on writing code and when they are ready to deploy, they only need to commit their ready project in a source control platform like GitHub/GitLab and the rest is done for them automatically. This layer provides a serverless layer to the developers since they do not have to touch the messy server side stuff. This layer as you might already have guessed is known as Platform as a Service (PaaS). Heroku is one of the solutions that sits on this layer. In this guide, are going to setup a platform that is similar to Heroku on your own infrastructure. As you know, you cannot download and install Heroku on your server. It is an online cloud service that you subscribe to. We will use Caprover to setup our own private Platform as a service (PaaS). CapRover is an extremely easy to use app/database deployment & web server manager for your NodeJS, Python, PHP, ASP.NET, Ruby, MySQL, MongoDB, Postgres, WordPress and even more applications. Features of Caprover CLI for automation and scripting Web GUI for ease of access and convenience No lock-in! Remove CapRover and your apps keep working! Docker Swarm under the hood for containerization and clustering Nginx (fully customizable template) under the hood for load-balancing Let’s Encrypt under the hood for free SSL (HTTPS) One-Click Apps: Deploying one-click apps is a matter of seconds! MongoDB, Parse, MySQL, WordPress, Postgres and many more. Fully Customizable: Optionally fully customizable nginx config allowing you to enable HTTP2, specific caching logic, custom SSL certs and etc Cluster Ready: Attach more nodes and create a cluster in seconds! CapRover automatically configures nginx to load balance. Increase Productivity: Focus on your apps! Not the bells and whistles just to run your apps! Easy Deploy: Many ways to deploy. You can upload your source from dashboard, use command line caprover deploy, use webhooks and build upon git push Caprover Pre-requisites Caprover runs as a container in your server which can be any that supports containerization. Depending on your preferences, you can use Podman or Docker to pull and run Caprover image. For this example, we are going to use Docker. In case you do not have Docker installed, the following guides listed below will be there to help you set it up as fast as possible. Install Docker and Docker Compose on Debian Setup Docker CE & Docker Compose on CentOS 8 | RHEL 8 How To Install Docker on RHEL 7 / CentOS 7

How To Install Docker CE on Ubuntu Once Docker Engine has been installed, add your user account to docker group: sudo usermod -aG docker $USER newgrp docker Another pre-requisite is a wildcard domain name pointed to the IP of your server where Caprover Server will be running. Setup your Heroku PaaS using CapRover Once the pre-requisites are out of the way, the only task remaining now is to set up our Caprover and poke around its rooms just to see what it has to offer. The following steps will be invaluable as you try to get it up and running. Step 1: Prepare your server Once Docker is installed, you can install all of the applications you need during your stay in the server. They include an editor and such kind of stuff. ##On CentOS sudo yum update sudo yum install vim git curl ##On Ubuntu sudo apt update sudo apt install vim git curl That was straingtforward. Next, let us pull Caprover image to set the stone rolling Step 2: Pull and execute Caprover Image We are going to cover the installation of Caprover depending on where your server sits. Scenario 1: Installation on a local server without Public IP Install dnsmasq After all, as mentioned in the pre-requisites section, we shall need a small DNS server to resolve domain names since Caprover is so particular with it. In case you have a local DNS server that supports wildcard domains, then you are good to go. You can skip the DNS setup part. In case you do not have it, install lightweight dnsmasq as follows: sudo yum -y install dnsmasq After dnsmasq is successfully installed, start and enable the service. sudo systemctl start dnsmasq sudo systemctl enable dnsmasq Add Wildcard DNS Recod Once dnsmasq is running as expected, we can go ahead and add the configs and wildcard domain name as shown below: $ sudo vim /etc/dnsmasq.conf listen-address=::1,127.0.0.1,172.20.192.38 domain=example.com server=8.8.8.8 address=/caprover.example.com/172.20.192.38 Replace the IPs therein with yours accordingly. Then restart dnsmasq sudo systemctl restart dnsmasq Test if it works We shall use the dig utility to test if our configuration works $ dig @127.0.0.1 test.caprover.example.com ; DiG 9.11.20-RedHat-9.11.20-5.el8 @127.0.0.1 test.caprover.example.com ; (1 server found) ;; global options: +cmd ;; Got answer: ;; ->>HEADER> Checking System Compatibility > Checking System Compatibility

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luckyloading560 · 4 years ago

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Docker Commands Windows

Docker Commands Windows Server 2016

MongoDB document databases provide high availability and easy scalability. You do not need to push your certificates with git commands. When the Docker Desktop application starts, it copies the /.docker/certs.d folder on your Windows system to the /etc/docker/certs.d directory on Moby (the Docker Desktop virtual machine running on Hyper-V). Docker Desktop for Windows can’t route traffic to Linux containers. However, you can ping the Windows containers. Per-container IP addressing is not possible. The docker (Linux) bridge network is not reachable from the Windows host. However, it works with Windows containers. Use cases and workarounds.

Estimated reading time: 15 minutes

Welcome to Docker Desktop! The Docker Desktop for Windows user manual provides information on how to configure and manage your Docker Desktop settings.

For information about Docker Desktop download, system requirements, and installation instructions, see Install Docker Desktop.

Settings

The Docker Desktop menu allows you to configure your Docker settings such as installation, updates, version channels, Docker Hub login,and more.

This section explains the configuration options accessible from the Settings dialog.

Open the Docker Desktop menu by clicking the Docker icon in the Notifications area (or System tray):

Select Settings to open the Settings dialog:

General

On the General tab of the Settings dialog, you can configure when to start and update Docker.

Start Docker when you log in - Automatically start Docker Desktop upon Windows system login.

Expose daemon on tcp://localhost:2375 without TLS - Click this option to enable legacy clients to connect to the Docker daemon. You must use this option with caution as exposing the daemon without TLS can result in remote code execution attacks.

Send usage statistics - By default, Docker Desktop sends diagnostics,crash reports, and usage data. This information helps Docker improve andtroubleshoot the application. Clear the check box to opt out. Docker may periodically prompt you for more information.

Resources

The Resources tab allows you to configure CPU, memory, disk, proxies, network, and other resources. Different settings are available for configuration depending on whether you are using Linux containers in WSL 2 mode, Linux containers in Hyper-V mode, or Windows containers.

Advanced

Note

The Advanced tab is only available in Hyper-V mode, because in WSL 2 mode and Windows container mode these resources are managed by Windows. In WSL 2 mode, you can configure limits on the memory, CPU, and swap size allocatedto the WSL 2 utility VM.

Use the Advanced tab to limit resources available to Docker.

CPUs: By default, Docker Desktop is set to use half the number of processorsavailable on the host machine. To increase processing power, set this to ahigher number; to decrease, lower the number.

Memory: By default, Docker Desktop is set to use 2 GB runtime memory,allocated from the total available memory on your machine. To increase the RAM, set this to a higher number. To decrease it, lower the number.

Swap: Configure swap file size as needed. The default is 1 GB.

Disk image size: Specify the size of the disk image.

Disk image location: Specify the location of the Linux volume where containers and images are stored.

You can also move the disk image to a different location. If you attempt to move a disk image to a location that already has one, you get a prompt asking if you want to use the existing image or replace it.

Download Apple MacOS High Sierra for Mac to get a boost with new technologies in the latest Mac OS update coming fall 2017. Apple download sierra.

File sharing

Note

The File sharing tab is only available in Hyper-V mode, because in WSL 2 mode and Windows container mode all files are automatically shared by Windows.

Use File sharing to allow local directories on Windows to be shared with Linux containers.This is especially useful forediting source code in an IDE on the host while running and testing the code in a container.Note that configuring file sharing is not necessary for Windows containers, only Linux containers. If a directory is not shared with a Linux container you may get file not found or cannot start service errors at runtime. See Volume mounting requires shared folders for Linux containers.

File share settings are:

Add a Directory: Click + and navigate to the directory you want to add.

Apply & Restart makes the directory available to containers using Docker’sbind mount (-v) feature.

Tips on shared folders, permissions, and volume mounts

Share only the directories that you need with the container. File sharing introduces overhead as any changes to the files on the host need to be notified to the Linux VM. Sharing too many files can lead to high CPU load and slow filesystem performance.

Shared folders are designed to allow application code to be edited on the host while being executed in containers. For non-code items such as cache directories or databases, the performance will be much better if they are stored in the Linux VM, using a data volume (named volume) or data container.

Docker Desktop sets permissions to read/write/execute for users, groups and others 0777 or a+rwx.This is not configurable. See Permissions errors on data directories for shared volumes.

Windows presents a case-insensitive view of the filesystem to applications while Linux is case-sensitive. On Linux it is possible to create 2 separate files: test and Test, while on Windows these filenames would actually refer to the same underlying file. This can lead to problems where an app works correctly on a developer Windows machine (where the file contents are shared) but fails when run in Linux in production (where the file contents are distinct). To avoid this, Docker Desktop insists that all shared files are accessed as their original case. Therefore if a file is created called test, it must be opened as test. Attempts to open Test will fail with “No such file or directory”. Similarly once a file called test is created, attempts to create a second file called Test will fail.

Shared folders on demand

You can share a folder “on demand” the first time a particular folder is used by a container.

If you run a Docker command from a shell with a volume mount (as shown in theexample below) or kick off a Compose file that includes volume mounts, you get apopup asking if you want to share the specified folder.

You can select to Share it, in which case it is added your Docker Desktop Shared Folders list and available tocontainers. Alternatively, you can opt not to share it by selecting Cancel.

Proxies

Docker Desktop lets you configure HTTP/HTTPS Proxy Settings andautomatically propagates these to Docker. For example, if you set your proxysettings to http://proxy.example.com, Docker uses this proxy when pulling containers.

Your proxy settings, however, will not be propagated into the containers you start.If you wish to set the proxy settings for your containers, you need to defineenvironment variables for them, just like you would do on Linux, for example:

For more information on setting environment variables for running containers,see Set environment variables.

Network

Note

The Network tab is not available in Windows container mode because networking is managed by Windows.

You can configure Docker Desktop networking to work on a virtual private network (VPN). Specify a network address translation (NAT) prefix and subnet mask to enable Internet connectivity.

DNS Server: You can configure the DNS server to use dynamic or static IP addressing.

Note

Some users reported problems connecting to Docker Hub on Docker Desktop. This would manifest as an error when trying to rundocker commands that pull images from Docker Hub that are not alreadydownloaded, such as a first time run of docker run hello-world. If youencounter this, reset the DNS server to use the Google DNS fixed address:8.8.8.8. For more information, seeNetworking issues in Troubleshooting.

Updating these settings requires a reconfiguration and reboot of the Linux VM.

WSL Integration

In WSL 2 mode, you can configure which WSL 2 distributions will have the Docker WSL integration.

By default, the integration will be enabled on your default WSL distribution. To change your default WSL distro, run wsl --set-default <distro name>. (For example, to set Ubuntu as your default WSL distro, run wsl --set-default ubuntu).

You can also select any additional distributions you would like to enable the WSL 2 integration on.

For more details on configuring Docker Desktop to use WSL 2, see Docker Desktop WSL 2 backend.

Docker Engine

The Docker Engine page allows you to configure the Docker daemon to determine how your containers run.

Type a JSON configuration file in the box to configure the daemon settings. For a full list of options, see the Docker Enginedockerd commandline reference.

Click Apply & Restart to save your settings and restart Docker Desktop.

Command Line

On the Command Line page, you can specify whether or not to enable experimental features.

You can toggle the experimental features on and off in Docker Desktop. If you toggle the experimental features off, Docker Desktop uses the current generally available release of Docker Engine. Final cut pro mac app store.

Experimental features

Experimental features provide early access to future product functionality.These features are intended for testing and feedback only as they may changebetween releases without warning or can be removed entirely from a futurerelease. Experimental features must not be used in production environments.Docker does not offer support for experimental features.

For a list of current experimental features in the Docker CLI, see Docker CLI Experimental features.

Run docker version to verify whether you have enabled experimental features. Experimental modeis listed under Server Adobe photoshop 2020 patcher windows. data. Sonos controller mac 10.6.8 download. If Experimental is true, then Docker isrunning in experimental mode, as shown here:

Kubernetes

Note

The Kubernetes tab is not available in Windows container mode.

Docker Desktop includes a standalone Kubernetes server that runs on your Windows machince, sothat you can test deploying your Docker workloads on Kubernetes. To enable Kubernetes support and install a standalone instance of Kubernetes running as a Docker container, select Enable Kubernetes.

For more information about using the Kubernetes integration with Docker Desktop, see Deploy on Kubernetes.

Reset

The Restart Docker Desktop and Reset to factory defaults options are now available on the Troubleshoot menu. For information, see Logs and Troubleshooting.

Troubleshoot

Visit our Logs and Troubleshooting guide for more details.

Log on to our Docker Desktop for Windows forum to get help from the community, review current user topics, or join a discussion.

Log on to Docker Desktop for Windows issues on GitHub to report bugs or problems and review community reported issues.

For information about providing feedback on the documentation or update it yourself, see Contribute to documentation.

Switch between Windows and Linux containers

From the Docker Desktop menu, you can toggle which daemon (Linux or Windows)the Docker CLI talks to. Select Switch to Windows containers to use Windowscontainers, or select Switch to Linux containers to use Linux containers(the default).

For more information on Windows containers, refer to the following documentation:

Microsoft documentation on Windows containers.

Build and Run Your First Windows Server Container (Blog Post)gives a quick tour of how to build and run native Docker Windows containers on Windows 10 and Windows Server 2016 evaluation releases.

Getting Started with Windows Containers (Lab)shows you how to use the MusicStoreapplication with Windows containers. The MusicStore is a standard .NET application and,forked here to use containers, is a good example of a multi-container application.

To understand how to connect to Windows containers from the local host, seeLimitations of Windows containers for localhost and published ports

Settings dialog changes with Windows containers

When you switch to Windows containers, the Settings dialog only shows those tabs that are active and apply to your Windows containers:

If you set proxies or daemon configuration in Windows containers mode, theseapply only on Windows containers. If you switch back to Linux containers,proxies and daemon configurations return to what you had set for Linuxcontainers. Your Windows container settings are retained and become availableagain when you switch back.

Dashboard

The Docker Desktop Dashboard enables you to interact with containers and applications and manage the lifecycle of your applications directly from your machine. The Dashboard UI shows all running, stopped, and started containers with their state. It provides an intuitive interface to perform common actions to inspect and manage containers and Docker Compose applications. For more information, see Docker Desktop Dashboard.

Docker Hub

Docker Commands Windows

Select Sign in /Create Docker ID from the Docker Desktop menu to access your Docker Hub account. Once logged in, you can access your Docker Hub repositories directly from the Docker Desktop menu.

For more information, refer to the following Docker Hub topics:

Two-factor authentication

Docker Desktop enables you to sign into Docker Hub using two-factor authentication. Two-factor authentication provides an extra layer of security when accessing your Docker Hub account.

You must enable two-factor authentication in Docker Hub before signing into your Docker Hub account through Docker Desktop. For instructions, see Enable two-factor authentication for Docker Hub.

Docker Desktop for Windows user manual. Estimated reading time: 17 minutes. Welcome to Docker Desktop! The Docker Desktop for Windows user manual provides information on how to configure and manage your Docker Desktop settings. The fastest and easiest way to get started with Docker on Windows. Docker Desktop is an application for MacOS and Windows machines for the building and sharing of containerized applications and microservices. Docker Desktop delivers the speed, choice and security you need for designing and delivering containerized applications on your desktop. I have the same thing, but I also noticed that Hyper-V has to be enabled. As in, if your copy of Windows 10 has Hyper-V, you can install it by simply enabling it because it’s already there. On Windows 10 Home, though, there is no Hyper-V to enable. I also have Windows 10 Home. The only option for Home edition users is to use Docker. Docker supports Docker Desktop on Windows for those versions of Windows 10 that are still within Microsoft’s servicing timeline. What’s included in the installer The Docker Desktop installation includes Docker Engine, Docker CLI client, Docker Compose, Notary, Kubernetes, and Credential Helper. https://luckyloading560.tumblr.com/post/653769899713380352/docker-windows-home-edition.

After you have enabled two-factor authentication:

Docker Commands Windows Server 2016

Go to the Docker Desktop menu and then select Sign in / Create Docker ID.

Enter your Docker ID and password and click Sign in.

After you have successfully signed in, Docker Desktop prompts you to enter the authentication code. Enter the six-digit code from your phone and then click Verify.

After you have successfully authenticated, you can access your organizations and repositories directly from the Docker Desktop menu.

Adding TLS certificates

You can add trusted Certificate Authorities (CAs) to your Docker daemon to verify registry server certificates, and client certificates, to authenticate to registries.

How do I add custom CA certificates?

Docker Desktop supports all trusted Certificate Authorities (CAs) (root orintermediate). Docker recognizes certs stored under Trust RootCertification Authorities or Intermediate Certification Authorities.

Docker Desktop creates a certificate bundle of all user-trusted CAs based onthe Windows certificate store, and appends it to Moby trusted certificates. Therefore, if an enterprise SSL certificate is trusted by the user on the host, it is trusted by Docker Desktop.

To learn more about how to install a CA root certificate for the registry, seeVerify repository client with certificatesin the Docker Engine topics.

How do I add client certificates?

You can add your client certificatesin ~/.docker/certs.d/<MyRegistry>:<Port>/client.cert and~/.docker/certs.d/<MyRegistry>:<Port>/client.key. You do not need to push your certificates with git commands.

When the Docker Desktop application starts, it copies the~/.docker/certs.d folder on your Windows system to the /etc/docker/certs.ddirectory on Moby (the Docker Desktop virtual machine running on Hyper-V).

You need to restart Docker Desktop after making any changes to the keychainor to the ~/.docker/certs.d directory in order for the changes to take effect.

The registry cannot be listed as an insecure registry (seeDocker Daemon). Docker Desktop ignorescertificates listed under insecure registries, and does not send clientcertificates. Commands like docker run that attempt to pull from the registryproduce error messages on the command line, as well as on the registry.

To learn more about how to set the client TLS certificate for verification, seeVerify repository client with certificatesin the Docker Engine topics.

Where to go next

Try out the walkthrough at Get Started.

Dig in deeper with Docker Labs example walkthroughs and source code.

Refer to the Docker CLI Reference Guide.

windows, edge, tutorial, run, docker, local, machine

0 notes

joblistan · 4 years ago

Link

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0 notes

codeonedigest · 2 years ago

Text

Spring Boot Microservices + MongoDB in Docker Containers | Step by step tutorial for Beginners

Full Video Link: https://youtu.be/qWzBUwKiCpM Hi, a new #video on step by step #tutorial for #springboot #microservices running in #docker #container with #mongodb also running in #docker #container is published on #codeonedigest #youtube channel. Easy

MongoDB is an open-source document database and leading NoSQL database. MongoDB is written in C++. This video will give you complete understanding of running the MongoDB in docker container. MongoDB works on concept of collection and document. MongoDB is a cross-platform, document-oriented database that provides, high performance, high availability, and easy scalability. Mongo Database –…

View On WordPress

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cladeymoore · 6 years ago

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Continuous Integration at Coinbase: How we optimized CircleCI for speed & cut our build times by…

Continuous Integration at Coinbase: How we optimized CircleCI for speed and cut our build times by 75%

Tuning a continuous integration server presents an interesting challenge — infrastructure engineers need to balance build speed, cost, and queue times on a system that many developers do not have extensive experience managing at scale. The results, when done right, can be a major benefit to your company as illustrated by the recent journey we took to improve our CI setup.

Continuous Integration at Coinbase

As Coinbase has grown, keeping our developers happy with our internal tools has been a high priority. For most of Coinbase’s history we have used CircleCI server, which has been a performant and low-maintenance tool. As the company and our codebase have grown, however, the demands on our CI server have increased as well. Prior to the optimizations described here, builds for the monorail application that runs Coinbase.com had increased significantly in length (doubling or tripling the previous average build times) and developers commonly complained about lengthy or non-finishing builds.

Our CI builds were no longer meeting our expectations, and it was with the previous issues in mind that we decided to embark on a campaign to get our setup back into shape.

It’s worth sharing here that Coinbase specifically uses the on-premise server version of CircleCI rather than their cloud offering — hosting our own infrastructure is important to us for security reasons, and these concepts specifically apply to self-managed CI clusters.

The Four Golden Signals

We found the first key to optimizing any CI system to be observability, as without a way to measure the effects of your tweaks and changes it’s impossible to truly know whether or not you actually made an improvement. In our case, server-hosted CircleCI uses a nomad cluster for builds, and at the time did not provide any method of monitoring your cluster or the nodes within. We had to build systems of our own, and we decided a good approach would be using the framework of the four golden signals, Latency, Traffic, Errors, and Saturation.

Latency

Latency is the total amount of time it takes to service a request. In a CI system, this can be considered to be the total amount of time a build takes to run from start to finish. Latency is better measured on a per-repo or even per-build basis as build length can vary hugely based on the project.

To measure this, we built a small application that queried CircleCI’s API regularly for build lengths, and then shipped over that information to Datadog to allow us to build graphs and visualizations of average build times. This allowed us to chart the results of our improvement experiments empirically and automatically rather than relying on anecdotal or manually curated results as we had done previously.

CircleCI API results

Traffic

Traffic is the amount of demand being placed on your system at any one time. In a CI system, this can be represented by the total number of concurrently running builds.

We were able to measure this by using the same system we built to measure latency metrics. This came in handy when determining the upper and lower bounds for the use of our build resources as it allowed us to see exactly how many jobs were running at any one time.

Errors

Errors are the total amount of requests or calls that fail. In a CI system this can be represented by the total number of builds that fail due to infrastructural reasons. It’s important here to make a distinction between builds that fail correctly, due to tests, linting, code errors, etc. rather than builds that fail due to platform issues.

One issue we encountered was that occasionally AWS would give us “bad” instances when spinning up new builders that would run much slower than a normal “good” instance. Adding error detection into our builder startup scripts allowed us to terminate these and spin up new nodes before they could slow down our running builds.

Saturation

Saturation is how “full” your service is, or how much of your system resources are being used. In a CI system, this is fairly straightforward — how much I/O, CPU, and memory are the builders under load using.

To measure saturation for our setup we were able to tap into cluster metrics by installing a Datadog Agent on each of our builders, which allowed us to get a view into system stats across the cluster.

Datadog job statistics

Identifying the Root Cause

Once your monitoring setup is in place it becomes easier to dig into the root cause of build slowdowns. One of the difficulties in diagnosing CI problems without cluster-wide monitoring is that it can be hard to identify which builders are experiencing load at any one time or how that load affects your builds. Latency monitoring can allow you to figure out which builds are taking the longest, and saturation monitoring can allow you to identify the nodes running those builds for closer investigation.

For us, the new latency measuring we added allowed us to quickly confirm what we had previously guessed: not every build was equal. Some builds ran at the quick speeds we had previously been experiencing but other builds would drag on for far longer than we expected.

In our case this discovery was the big breakthrough — once we could quickly identify builds with increased latency and find the saturated nodes the problem quickly revealed itself: resource contention between starting builds! Due to the large number of tests for our larger builds we use CircleCI’s parallelization feature to split up our tests and run them across the fleet in separate docker containers. Each test container also requires another set of support containers (Redis, MongoDB, etc.) in order to replicate the production environment. Starting all of the necessary containers for each build is a resource-intensive operation, requiring significant amounts of I/O and CPU. Since Nomad uses bin-packing for job distributions our builders would sometimes launch up to 5 different sets of these containers at once, causing massive slow-downs before tests could even start running.

Build Experimentation

Setting up a development environment is key to debugging CI problems once found as it allows you to push your system to its limits while ensuring that none of your testing affects productivity in production. Coinbase maintains a development cluster for CircleCI that we use to test out new versions before pushing them out to production, but in order to investigate our options we turned the cluster into a smaller replica of our production instance, allowing us to effectively load test CircleCI builders. Keeping your development cluster as close as possible to production can help ensure any solutions you find are reflective of what can actually help in a real environment.

Once we had identified why our builds were encountering issues, and we’d set up an environment to run experiments in, we could start developing a solution. We repeatedly ran the same large builds that were causing the problems on our production cluster on different sizes and types of EC2 instances in order to figure out which was the most time and cost-effective options to use.

EC2 instance type comparison

While we previously had been using smaller numbers of large instances to run our builds it turns out the optimal setup for our cluster was actually a very large number of smaller instances (m5.larges in our case) — small enough that CircleCI would only ship one parallelized build container to each instance, preventing the build trampling issues that were the cause of the slow downs. A nice side effect of identifying the correct instance types was that it actually allowed us to reduce our server cost footprint significantly as we were able to size our cluster more closely to its usage.

Problem? Solved!

Applying your changes to a production environment is the final step. Determining whether the effects of the tuning worked can be done the same way the problems were identified — with the four golden signals.

After we had identified what worked best on our development cluster we quickly implemented the new builder sizing in production. The results? A 75% decrease in build time for our largest builds, significant cost savings due to the right-sizing of our cluster, and most important of all: happy developers!

Builds, before and after

This website may contain links to third-party websites or other content for information purposes only (“Third-Party Sites”). The Third-Party Sites are not under the control of Coinbase, Inc., and its affiliates (“Coinbase”), and Coinbase is not responsible for the content of any Third-Party Site, including without limitation any link contained in a Third-Party Site, or any changes or updates to a Third-Party Site. Coinbase is not responsible for webcasting or any other form of transmission received from any Third-Party Site. Coinbase is providing these links to you only as a convenience, and the inclusion of any link does not imply endorsement, approval or recommendation by Coinbase of the site or any association with its operators.

Unless otherwise noted, all images provided herein are by Coinbase.

Continuous Integration at Coinbase: How we optimized CircleCI for speed & cut our build times by… was originally published in The Coinbase Blog on Medium, where people are continuing the conversation by highlighting and responding to this story.

from Money 101 https://blog.coinbase.com/continuous-integration-at-coinbase-how-we-optimized-circleci-for-speed-cut-our-build-times-by-378c8b1d7161?source=rss----c114225aeaf7---4 via http://www.rssmix.com/

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howtorapeurjob · 8 years ago

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Docker - Nginx

原本在Windows中，Nginx可以點兩下就啟動，只要資料夾內的東西有放好就可以快速連上，也不需要特別多做一些設定 Docker已經存在許久，但是主要的作業系統都是以Windows為主，所以在當時不支援的情況之下就沒特別玩弄(雖然現在已經開始支援Windows) 目前因為是用Mac 所以就可以很順利的快速使用

安裝

Mac的安裝說明在 https://docs.docker.com/docker-for-mac/ 下載的安裝檔則是在 https://docs.docker.com/docker-for-mac/install/#download-docker-for-mac 目前單純安裝Community Edition / Stable版本解壓縮後直接丟到Application裡面就可以了

另外推薦安裝的是Kitematic, 打開功能介面就有這個選項他可以幫你安裝其他人設定好的image 包括了官方的比如: MongoDB / Python / Nginx 等

設定

實際上我是根據官網的說明來設定Nginx https://docs.docker.com/docker-for-mac/#explore-the-application-and-run-examples 好處是直接下指令之後，立刻幫你下載image並將80port建立好，讓你排便順暢沒煩惱，但是Nginx最大的好處是內部的設定檔以及Routing等功能。

但是等一下，這樣我怎麼知道我的Web應該放在哪邊？因為沒有透過複雜的設定去建立設定檔，所以無法讓Docker內的image直接讀取本機的資料夾。其實只要把檔案丟進去就好了！！開啟Docker之後，點選Kitematic，並對Nginx點選EXEC

在Command line中用CP的指令將我們的檔案複製到Nginx的路徑下就可以了，而hostname就是虛擬機的名稱

docker cp index.html b0ac4a31eb99:/usr/share/nginx/html

如此一來我們就可以將新的資料更新到Docker了！！

感謝鯨魚偉哉鯨魚

#Mac #Docker #nginx

0 notes

holytheoristtastemaker · 5 years ago

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Have you ever built an application but it doesn't run on all platforms? Or been sick of installing different dependencies and libraries for each service/component in the application? Dodged the whole nine yards just to deploy, scale and manage a simple application??

Then DOCKER is waiting for you!!!

Docker:What the hell is it?

Docker is a set of platform as a service products that uses OS-level virtualization to deliver software in packages called containers. (Well. . .thats the GOOGLE definition for you! )

To wrap it up simply,it is just a BOX!

Imagine,

A printer box, we insert a paper and get printed text or colors on it. So how is it working ? Perhaps all the colors and required material is already present in the printer.

Consider a car wash, car is sent in, many process like washing, cleaning etc happen and at the end we get a shiny clean car (or a less rusty one).

So, docker is like a printer box or car wash setup in this instance, taking an input and giving an output basically.

It is basically a box with an application and its related dependencies, libraries etc inside it

But why docker?

Imagine we are building a zoo, we toss all animals like monkeys, Lion and Crocodiles in one big park with only one kind of food and only one kind of environment, lets say, land.

The bananas eaten by monkeys can’t be used by Lions and crocodiles, the meat for Lions can’t be eaten by monkeys. Monkeys want trees and crocodiles need a water space in the environment.

In similar way, if we are building an application that has services like a database and framework etc, The libraries and dependencies(food) used by databases (cassandra, postgresql, mongodb etc) may not be compatible/suitable for frameworks (strapi, nodejs express etc).

Eg: MongoDb version 4.26 might not be compatible/suitable for NodeJs version 4.16.4

To make it easy to develop, run and maintain an application and to operate on all the platforms we came up docker. The problem in zoo example can be solved by providing each animal, a separate boundary with the required food and environment.

Containers

In docker we have those separate boundaries called containers. We place each service in one container with all the libraries and dependencies required for it.

Container is a completely isolated environment with their own processes, network interfaces and their own mounts.

Wait, doesnt it look familiar? Yes,you are right if you guessed it, they remind us of Virtual machines. If its similar to VMs, Why on Earth do we need to use Containers??

Well, Each VM has a separate OS along with libraries, dependencies and application, which increases overload and utilization, making it difficult to operate it in small PCs(though we might not use it there).

Whereas Containers share the same OS, considerably less overload and utilization than VMs. Hence they are just the darlings preferred for application development, deployment and management.

Images

These are readymade templates of services like MongoDb, NodeJs etc, to run in containers. We can either use existing images from docker.io or create our own.

Creating an Image of the service helps in shipping it for deployments. Then it is just running a simple command to get the server up and running. We dont have to worry about creating environment, installing dependencies and what not.

Magic commands

Its time to blow some fairy pixel dust and do some magic!

Lets start with running an image in a container,using run command.

Run redis image in container

docker run redis

List the version details

docker version

List the Running containers

docker ps

List the Running & Not Running containers

docker ps -a

Remove a container

docker rm [container ID]

Note: To remove a container make sure it is stopped first using stop command.

List the images

docker images

Remove an image

docker rmi [image_name]

Just download the image but not run in the container

docker pull [image_name]

Thank you so much for reading my content. More of such content coming on this blog, so stay tuned.

0 notes

udemytutorialfreedownload · 5 years ago

Link

Docker Mastery: with Kubernetes +Swarm from a Docker Captain

Build, test, deploy containers with the best mega-course on Docker, Kubernetes, Compose, Swarm and Registry using DevOps

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Learn faster with included live chat group (21,000 members!) and weekly live Q&A.

Gain the skills to build development environments with your code running in containers.

Build Swam and Kubernetes clusters for server deployments!

Hands-on with best practices for making Dockerfiles and Compose files like a Pro!

Build and publish your own custom images.

Create your own custom image registry to store your apps and deploy them in corporate environments.

READ ALSO: 1. MongoDB - The Complete Developer's Guide 2020 2. Spring Framework 5: Beginner to Guru 3. Learn How To Code: Google's Go (golang) Programming Language 4. The Complete Oracle SQL Certification Course

Requirements

No paid software required - Just install your favorite text editor and browser!

Local admin access to install Docker for Mac/Windows/Linux.

Understand the terminal or command prompt basics.

Linux basics like shells, SSH, and package managers. (tips included to help newcomers!)

Know the basics of creating a server in the cloud (on any provider). (tips included to help newcomers!)

Understand the basics of web and database servers. (how they typically communicate, IP's, ports, etc.)

Have a GitHub and Docker Hub account.

Description

Updated Monthly in 2019! Be ready for the Dockerized future with the number ONE Docker + Kubernetes mega-course on Udemy. Welcome to the most complete and up-to-date course for learning and using containers end-to-end, from development and testing to server deployments and production. Taught by an award-winning Docker Captain and DevOps consultant.

Just starting out with Docker? Perfect. This course starts out assuming you're new to containers.

Or: Using Docker now and need to deal with real-world problems? I'm here for you! See my production topics around Swarm, Kubernetes, secrets, logging, rolling upgrades, and more.

BONUS: This course comes with Slack Chat and Live Weekly Q&A with me!

"I've followed another course on (Udemy). This one is a million times more in-depth." "...when it comes to all the docker stuff, this is the course you're gonna want to take" - 2019 Student Udemy Review

Just updated in November 2019 with sections on:

Docker Security top 10

Docker 19.03 release features

Why should you learn from me? Why trust me to teach you the best ways to use Docker? (Hi, I'm Bret, please allow me to talk about myself for a sec):

I'm A Practitioner. Welcome to the real world: I've got 20 years of sysadmin and developer experience, over 30 certifications, and have been using Docker and the container ecosystem for my consulting clients and my own companies since Docker's early days. Learn from someone who's run hundreds of containers across dozens of projects and organizations.

I'm An Educator. Learn from someone who knows how to make a syllabus: I want to help you. People say I'm good at it. For the last few years, I've trained thousands of people on using Docker in workshops, conferences, and meetups. See me teach at events like DockerCon, O'Reilly Velocity, GOTO Conf, and Linux Open Source Summit. I hope you'll decide to learn with me and join the fantastic online Docker community.

I Lead Communities. Also, I'm a Docker Captain, meaning that Docker Inc. thinks I know a thing or two about Docker and that I do well in sharing it with others. In the real-world: I help run two local meetups in our fabulous tech community in Norfolk/Virginia Beach USA. I help online: usually in Slack and Twitter, where I learn from and help others.

"Because of the Docker Mastery course, I landed my first DevOps job. Thank you, Captain!" - Student Ronald Alonzo

"There are a lot of Docker courses on Udemy -- but ignore those, Bret is the single most qualified person to teach you." - Kevin Griffin, Microsoft MVP

Giving Back: a portion of my profit on this course will be donated to supporting open source and protecting our freedoms online! This course is only made possible by the amazing people creating the open-source. I'm standing on the shoulders of (open source) giants! Donations will be split between my favorite charities including the Electronic Frontier Foundation and Free Software Foundation. Look them up. They're awesome!

This is a living course and will be updated as Docker and Kubernetes feature change.

This course is designed to be fast at getting you started but also get you deep into the "why" of things. Simply the fastest and best way to learn the latest container skills. Look at the scope of topics in the Session and see the breadth of skills you will learn.

Also included is a private Slack Chat group with 20k students for getting help with this course and continuing your Docker and DevOps learning with help from myself and other students.

"Bret's course is a level above all of those resources, and if you're struggling to get a handle on Docker, this is the resource you need to invest in." - Austin Tindle, Course Student

Some of the many cool things you'll do in this course:

Edit web code on your machine while it's served up in a container

Lockdown your apps in private networks that only expose necessary ports

Create a 3-node Swarm cluster in the cloud

Install Kubernetes and learn the leading server cluster tools

Use Virtual IP's for built-in load balancing in your cluster

Optimize your Dockerfiles for faster building and tiny deploys

Build/Publish your own custom application images

Learn the differences between Kubernetes and Swarm

Create your own image registry

Use Swarm Secrets to encrypt your environment configs, even on disk

Deploy container updates in a rolling always-up design

Create the config utopia of a single set of YAML files for local dev, CI testing, and prod cluster deploys

And so much more...

After taking this course, you'll be able to:

Use Docker in your daily developer and/or sysadmin roles

Deploy apps to Kubernetes

Make Dockerfiles and Compose files

Build multi-node Swarm clusters and deploying H/A containers

Make Kubernetes YAML manifests and deploy using infrastructure-as-code methods

Build a workflow of using Docker in dev, then test/CI, then production with YAML

Protect your keys, TLS certificates, and passwords with encrypted secrets

Keep your Dockerfiles and images small, efficient, and fast

Run apps in Docker, Swarm, and Kubernetes and understand the pros/cons of each

Develop locally while your code runs in a container

Protect important persistent data in volumes and bind mounts

Lead your team into the future with the latest Docker container skills!

Extra things that come with this course:

Access to the course Slack team, for getting help/advice from me and other students.

Bonus videos I put elsewhere like YouTube, linked to these courses resources.

Weekly Live Q&A on YouTube Live.

Tons of reference links to supplement this content.

Updates to content as Docker changes its features on these topics.

Who this course is for:

Software developers, sysadmins, IT pros, and operators at any skill level.

Anyone who makes deploys or operates software on servers.

Docker Mastery: with Kubernetes +Swarm from a Docker Captain

Created by Bret Fisher, Docker Captain Program

Last updated 3/2020

English

English, French [Auto-generated]

Size: 11.24 GB

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#News Updates #Docker Mastery: with Kubernetes +Swarm from a Docker Captain

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chaj · 6 years ago

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via thenewstack.io

Google Cloud Run is a serverless environment to run containers. For the background and context of this latest Google Cloud Platform (GCP) service, refer to my previous article.

In this tutorial, we will deploy a web application based on Node.js and MongoDB to the Cloud Run platform. Since Cloud Run is meant to host and scale stateless web applications, we will use mLab service to persist data. Since both mLab and Cloud Run are serverless, we just need to focus on the code and business logic instead of worrying about the infrastructure.

There are two steps involved in this workflow: provisioning an mLAB Mongo database instance, and deploying code to Cloud Run. This tutorial assumes you have an active account on Google Cloud Platform with the CLI and SDK installed on your development machine. You also need Docker Desktop to build images locally.

Step 1: Provisioning a mLab MongoDB Instance

mLab offers a managed MongoDB database as a service. It has a free plan called Sandbox that provides 500MB of storage to run a database instance for development and testing. It is a shared database server process running on a shared virtual machine, good enough for our prototype.

mLab instances can be deployed in multiple cloud platforms including GCP. Refer to the documentation on creating a database within GCP. Make sure that you launch the instance in us-central1 (lowa) region. This is the same region where our web app will be deployed. Since both the services are running in the same region, the latency is minimal.

Below is the screenshot of the mLab database service that I launched for this tutorial. Make sure your instance looks similar. Keep the connection string handy which is needed for the next step.

Step 2: Building and Deploying a Cloud Run Service

Start by cloning the Github repo that has the sample MEAN web application. We will then build a Docker image and push it to Google Container Registry (GCR).

Navigate to the root of the repo to find the Dockerfile. We will use this to build the image locally.

Run the below commands to set the environment. This initializes all the variables required to build and deploy the service. Ensure you are replacing the placeholders with appropriate values.

PROJECT_ID='GCP project id' REGION_ID='us-central1' IMAGE='todo:v1' CLOUD_RUN_SVC="todo" DB_HOST='mLAB connection string' gcloud components install beta gcloud components update gcloud config set run/region $REGION_ID gcloud auth configure-docker gcloud components install docker-credential-gcr

The above commands install the Cloud Run CLI followed by configuring the local Docker environment with Google Container Registry credentials.

It’s time for us to build the container and push it to GCR.

docker build . --tag gcr.io/$PROJECT_ID/$IMAGE docker push gcr.io/$PROJECT_ID/$IMAGE

Verify that the image is available in GCR by running the below command:

gcloud container images list

With the database and container image in place, let’s go ahead and deploy the web application.

gcloud beta run deploy $CLOUD_RUN_SVC \ --image gcr.io/$PROJECT_ID/$IMAGE \ --allow-unauthenticated \ --update-env-vars DBHOST=$DB_HOST

The switch, –allow-unauthenticated, will let the service accept the traffic from the public internet. Notice that we are passing the MongoDB connection string generated by mLab as an environment variable. The code expects the connection string from the DBHOST environment variable.

You can retrieve the running services with the below command:

gcloud beta run services list

You can also explore the service configuration from the GCP Console.

Clicking on the URL takes us to the web application.

Cloud Run services can also be deployed on existing GKE clusters. They act like typical Kubernetes Pods with access to resources available within the cluster. In the next part of this tutorial, I will demonstrate how to access stateful services running in a GKE cluster from a Cloud Run service. Stay tuned.

Feature image by Gerd Altmann from Pixabay.

The post Tutorial: Deploying a Web Application on Google Cloud Run appeared first on The New Stack.

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