How to Use Ansible to Install and Set Up Docker on Ubuntu 18.04

Introduction

With the popularization of containerized applications and microservices, server automation now plays an essential role in systems administration. It is also a way to establish standard procedures for new servers and reduce human error.

This guide explains how to use Ansible to automate the steps contained in our guide on How To Install and Use Docker on Ubuntu 18.04. Docker is an application that simplifies the process of managing containers, resource-isolated processes that behave in a similar way to virtual machines, but are more portable, more resource-friendly, and depend more heavily on the host operating system.

While you can complete this setup manually, using a configuration management tool like Ansible to automate the process will save you time and establish standard procedures that can be repeated through tens to hundreds of nodes. Ansible offers a simple architecture that doesn’t require special software to be installed on nodes, and it provides a robust set of features and built-in modules which facilitate writing automation scripts.

Pre-Flight Check

In order to execute the automated setup provided by the playbook discussed in this guide, you’ll need:

• Ansible installed either on your local machine or on a remote server that you have set up as an Ansible Control Node.
• Access to one or more Ubuntu 18.04 servers which will be used as your Ansible hosts. Each should have a non-root user with sudo privileges and a basic firewall configured.

Testing Connectivity to Nodes

To make sure Ansible is able to execute commands on your nodes, run the following command from your Ansible Control Node:

ansible -m ping all

This command will use Ansible’s built-in [ping](https://docs.ansible.com/ansible/latest/modules/ping_module.html) module to run a connectivity test on all nodes from your default inventory file, connecting as the current system user. The ping module will test whether:

• your Ansible hosts are accessible;
• your Ansible Control Node has valid SSH credentials;
• your hosts are able to run Ansible modules using Python.

If you installed and configured Ansible correctly, you will get output similar to this:

Output
server1 | SUCCESS => {
    "changed": false, 
    "ping": "pong"
}
server2 | SUCCESS => {
    "changed": false, 
    "ping": "pong"
}
server3 | SUCCESS => {
    "changed": false, 
    "ping": "pong"
}

Once you get a pong reply back from a host, it means you’re ready to run Ansible commands and playbooks on that server.

What Does this Playbook Do?

This Ansible playbook provides an alternative to manually running through the procedure outlined in our guide on How To Install and Use Docker on Ubuntu 18.04.

Running this playbook will perform the following actions on your Ansible hosts:

1. Install aptitude, which is preferred by Ansible as an alternative to the apt package manager.
2. Install the required system packages.
3. Install the Docker GPG APT key.
4. Add the official Docker repository to the apt sources.
5. Install Docker.
6. Install the Python Docker module via pip.
7. Pull the default image specified by default_container_image from Docker Hub.
8. Create the number of containers defined by create_containers field, each using the image defined by default_container_image, and execute the command defined in default_container_command in each new container.

Once the playbook has finished running, you will have a number of containers created based on the options you defined within your configuration variables.

How to Use this Playbook

To get started, we’ll download the contents of the playbook to your Ansible Control Node.

Use curl to download this playbook from the command line:

curl -L https://raw.githubusercontent.com/do-community/ansible-playbooks/master/docker/ubuntu1804.yml -o docker_ubuntu.yml

This will download the contents of the playbook to a file named docker_ubuntu.yml in your current working directory. You can examine the contents of the playbook by opening the file with your command-line editor of choice:

nano docker_ubuntu.yml

Once you’ve opened the playbook file, you should notice a section named vars with variables that require your attention:

docker_ubuntu.yml

. . .
vars:
  create_containers: 4
  default_container_name: docker
  default_container_image: ubuntu
  default_container_command: sleep 1d
. . .

Here’s what these variables mean:

• create_containers: The number of containers to create.
• default_container_name: Default container name.
• default_container_image: Default Docker image to be used when creating containers.
• default_container_command: Default command to run on new containers.

Once you’re done updating the variables inside docker_ubuntu.yml, save and close the file. If you used nano, do so by pressing CTRL + X, Y, then ENTER.

You’re now ready to run this playbook on one or more servers. Most playbooks are configured to be executed on all servers from your inventory, by default. We can use the -l flag to make sure that only a subset of servers, or a single server, is affected by the playbook. To execute the playbook only on server1, you can use the following command:

ansible-playbook docker_ubuntu.yml -l server1

You will get output similar to this:

Output
...
TASK [Add Docker GPG apt Key] ********************************************************************************************************************
changed: [server1]

TASK [Add Docker Repository] *********************************************************************************************************************
changed: [server1]

TASK [Update apt and install docker-ce] **********************************************************************************************************
changed: [server1]

TASK [Install Docker Module for Python] **********************************************************************************************************
changed: [server1]

TASK [Pull default Docker image] *****************************************************************************************************************
changed: [server1]

TASK [Create default containers] *****************************************************************************************************************
changed: [server1] => (item=1)
changed: [server1] => (item=2)
changed: [server1] => (item=3)
changed: [server1] => (item=4)

PLAY RECAP ***************************************************************************************************************************************
server1                  : ok=9    changed=8    unreachable=0    failed=0    skipped=0    rescued=0    ignored=0   

When the playbook is finished running, log in via SSH to the server provisioned by Ansible and run docker ps -a to check if the containers were successfully created:

sudo docker ps -a

You should see output similar to this:

CONTAINER ID        IMAGE               COMMAND             CREATED             STATUS              PORTS               NAMES
a3fe9bfb89cf        ubuntu              "sleep 1d"          5 minutes ago       Created                                 docker4
8799c16cde1e        ubuntu              "sleep 1d"          5 minutes ago       Created                                 docker3
ad0c2123b183        ubuntu              "sleep 1d"          5 minutes ago       Created                                 docker2
b9350916ffd8        ubuntu              "sleep 1d"          5 minutes ago       Created                                 docker1

This means the containers defined in the playbook were created successfully. Since this was the last task in the playbook, it also confirms that the playbook was fully executed on this server.

The Playbook Contents

You can find the Docker playbook featured in this tutorial in the ansible-playbooks repository To copy or download the script contents directly, click the Raw button towards the top of the script, or click here to view the raw contents directly.

The full contents are also included here for your convenience:

docker_ubuntu.yml

---
- hosts: all
  become: true
  vars:
    create_containers: 4
    default_container_name: docker
    default_container_image: ubuntu
    default_container_command: sleep 1d

  tasks:
    - name: Install aptitude using apt
      apt: name=aptitude state=latest update_cache=yes force_apt_get=yes

    - name: Install required system packages
      apt: name={{ item }} state=latest update_cache=yes
      loop: [ 'apt-transport-https', 'ca-certificates', 'curl', 'software-properties-common', 'python3-pip', 'virtualenv', 'python3-setuptools']

    - name: Add Docker GPG apt Key
      apt_key:
        url: https://download.docker.com/linux/ubuntu/gpg
        state: present

    - name: Add Docker Repository
      apt_repository:
        repo: deb https://download.docker.com/linux/ubuntu bionic stable
        state: present

    - name: Update apt and install docker-ce
      apt: update_cache=yes name=docker-ce state=latest

    - name: Install Docker Module for Python
      pip:
        name: docker

    # Pull image specified by variable default_image from the Docker Hub
    - name: Pull default Docker image
      docker_image:
        name: "{{ default_container_image }}"
        source: pull

    # Creates the number of containers defined by the variable create_containers, using default values
    - name: Create default containers
      docker_container:
        name: "{{ default_container_name }}{{ item }}"
        image: "{{ default_container_image }}"
        command: "{{ default_container_command }}"
        state: present
      with_sequence: count={{ create_containers }}

Feel free to modify this playbook to best suit your individual needs within your own workflow. For example, you could use the [docker_image](https://morioh.com/p/4e215b4c64de) module to push images to Docker Hub or the [docker_container](https://morioh.com/p/c310f568c20d) module to set up container networks.

Conclusion

Automating your infrastructure setup can not only save you time, but it also helps to ensure that your servers will follow a standard configuration that can be customized to your needs. With the distributed nature of modern applications and the need for consistency between different staging environments, automation like this has become a central component in many teams’ development processes.

In this guide, we demonstrated how to use Ansible to automate the process of installing and setting up Docker on a remote server. Because each individual typically has different needs when working with containers, we encourage you to check out the official Ansible documentation for more information and use cases of the docker_container Ansible module.

#docker #ubuntu

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A Simple Wrapper Around Amplify AppSync Simulator

This serverless plugin is a wrapper for amplify-appsync-simulator made for testing AppSync APIs built with serverless-appsync-plugin.

Install

npm install serverless-appsync-simulator
# or
yarn add serverless-appsync-simulator

Usage

This plugin relies on your serverless yml file and on the serverless-offline plugin.

plugins:
  - serverless-dynamodb-local # only if you need dynamodb resolvers and you don't have an external dynamodb
  - serverless-appsync-simulator
  - serverless-offline

Note: Order is important serverless-appsync-simulator must go before serverless-offline

To start the simulator, run the following command:

sls offline start

You should see in the logs something like:

...
Serverless: AppSync endpoint: http://localhost:20002/graphql
Serverless: GraphiQl: http://localhost:20002
...

Configuration

Put options under custom.appsync-simulator in your serverless.yml file

| option | default | description | | ------------------------ | -------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------- | | apiKey | 0123456789 | When using API_KEY as authentication type, the key to authenticate to the endpoint. | | port | 20002 | AppSync operations port; if using multiple APIs, the value of this option will be used as a starting point, and each other API will have a port of lastPort + 10 (e.g. 20002, 20012, 20022, etc.) | | wsPort | 20003 | AppSync subscriptions port; if using multiple APIs, the value of this option will be used as a starting point, and each other API will have a port of lastPort + 10 (e.g. 20003, 20013, 20023, etc.) | | location | . (base directory) | Location of the lambda functions handlers. | | refMap | {} | A mapping of resource resolutions for the Ref function | | getAttMap | {} | A mapping of resource resolutions for the GetAtt function | | importValueMap | {} | A mapping of resource resolutions for the ImportValue function | | functions | {} | A mapping of external functions for providing invoke url for external fucntions | | dynamoDb.endpoint | http://localhost:8000 | Dynamodb endpoint. Specify it if you're not using serverless-dynamodb-local. Otherwise, port is taken from dynamodb-local conf | | dynamoDb.region | localhost | Dynamodb region. Specify it if you're connecting to a remote Dynamodb intance. | | dynamoDb.accessKeyId | DEFAULT_ACCESS_KEY | AWS Access Key ID to access DynamoDB | | dynamoDb.secretAccessKey | DEFAULT_SECRET | AWS Secret Key to access DynamoDB | | dynamoDb.sessionToken | DEFAULT_ACCESS_TOKEEN | AWS Session Token to access DynamoDB, only if you have temporary security credentials configured on AWS | | dynamoDb.* | | You can add every configuration accepted by DynamoDB SDK | | rds.dbName | | Name of the database | | rds.dbHost | | Database host | | rds.dbDialect | | Database dialect. Possible values (mysql | postgres) | | rds.dbUsername | | Database username | | rds.dbPassword | | Database password | | rds.dbPort | | Database port | | watch | - *.graphql
- *.vtl | Array of glob patterns to watch for hot-reloading. |

Example:

custom:
  appsync-simulator:
    location: '.webpack/service' # use webpack build directory
    dynamoDb:
      endpoint: 'http://my-custom-dynamo:8000'

Hot-reloading

By default, the simulator will hot-relad when changes to *.graphql or *.vtl files are detected. Changes to *.yml files are not supported (yet? - this is a Serverless Framework limitation). You will need to restart the simulator each time you change yml files.

Hot-reloading relies on watchman. Make sure it is installed on your system.

You can change the files being watched with the watch option, which is then passed to watchman as the match expression.

e.g.

custom:
  appsync-simulator:
    watch:
      - ["match", "handlers/**/*.vtl", "wholename"] # => array is interpreted as the literal match expression
      - "*.graphql"                                 # => string like this is equivalent to `["match", "*.graphql"]`

Or you can opt-out by leaving an empty array or set the option to false

Note: Functions should not require hot-reloading, unless you are using a transpiler or a bundler (such as webpack, babel or typescript), un which case you should delegate hot-reloading to that instead.

Resource CloudFormation functions resolution

This plugin supports some resources resolution from the Ref, Fn::GetAtt and Fn::ImportValue functions in your yaml file. It also supports some other Cfn functions such as Fn::Join, Fb::Sub, etc.

Note: Under the hood, this features relies on the cfn-resolver-lib package. For more info on supported cfn functions, refer to the documentation

Basic usage

You can reference resources in your functions' environment variables (that will be accessible from your lambda functions) or datasource definitions. The plugin will automatically resolve them for you.

provider:
  environment:
    BUCKET_NAME:
      Ref: MyBucket # resolves to `my-bucket-name`

resources:
  Resources:
    MyDbTable:
      Type: AWS::DynamoDB::Table
      Properties:
        TableName: myTable
      ...
    MyBucket:
      Type: AWS::S3::Bucket
      Properties:
        BucketName: my-bucket-name
    ...

# in your appsync config
dataSources:
  - type: AMAZON_DYNAMODB
    name: dynamosource
    config:
      tableName:
        Ref: MyDbTable # resolves to `myTable`

Override (or mock) values

Sometimes, some references cannot be resolved, as they come from an Output from Cloudformation; or you might want to use mocked values in your local environment.

In those cases, you can define (or override) those values using the refMap, getAttMap and importValueMap options.

• refMap takes a mapping of resource name to value pairs
• getAttMap takes a mapping of resource name to attribute/values pairs
• importValueMap takes a mapping of import name to values pairs

Example:

custom:
  appsync-simulator:
    refMap:
      # Override `MyDbTable` resolution from the previous example.
      MyDbTable: 'mock-myTable'
    getAttMap:
      # define ElasticSearchInstance DomainName
      ElasticSearchInstance:
        DomainEndpoint: 'localhost:9200'
    importValueMap:
      other-service-api-url: 'https://other.api.url.com/graphql'

# in your appsync config
dataSources:
  - type: AMAZON_ELASTICSEARCH
    name: elasticsource
    config:
      # endpoint resolves as 'http://localhost:9200'
      endpoint:
        Fn::Join:
          - ''
          - - https://
            - Fn::GetAtt:
                - ElasticSearchInstance
                - DomainEndpoint

Key-value mock notation

In some special cases you will need to use key-value mock nottation. Good example can be case when you need to include serverless stage value (${self:provider.stage}) in the import name.

This notation can be used with all mocks - refMap, getAttMap and importValueMap

provider:
  environment:
    FINISH_ACTIVITY_FUNCTION_ARN:
      Fn::ImportValue: other-service-api-${self:provider.stage}-url

custom:
  serverless-appsync-simulator:
    importValueMap:
      - key: other-service-api-${self:provider.stage}-url
        value: 'https://other.api.url.com/graphql'

Limitations

This plugin only tries to resolve the following parts of the yml tree:

• provider.environment
• functions[*].environment
• custom.appSync

If you have the need of resolving others, feel free to open an issue and explain your use case.

For now, the supported resources to be automatically resovled by Ref: are:

• DynamoDb tables
• S3 Buckets

Feel free to open a PR or an issue to extend them as well.

External functions

When a function is not defined withing the current serverless file you can still call it by providing an invoke url which should point to a REST method. Make sure you specify "get" or "post" for the method. Default is "get", but you probably want "post".

custom:
  appsync-simulator:
    functions:
      addUser:
        url: http://localhost:3016/2015-03-31/functions/addUser/invocations
        method: post
      addPost:
        url: https://jsonplaceholder.typicode.com/posts
        method: post

Supported Resolver types

This plugin supports resolvers implemented by amplify-appsync-simulator, as well as custom resolvers.

From Aws Amplify:

• NONE
• AWS_LAMBDA
• AMAZON_DYNAMODB
• PIPELINE

Implemented by this plugin

• AMAZON_ELASTIC_SEARCH
• HTTP
• RELATIONAL_DATABASE

Relational Database

Sample VTL for a create mutation

#set( $cols = [] )
#set( $vals = [] )
#foreach( $entry in $ctx.args.input.keySet() )
  #set( $regex = "([a-z])([A-Z]+)")
  #set( $replacement = "$1_$2")
  #set( $toSnake = $entry.replaceAll($regex, $replacement).toLowerCase() )
  #set( $discard = $cols.add("$toSnake") )
  #if( $util.isBoolean($ctx.args.input[$entry]) )
      #if( $ctx.args.input[$entry] )
        #set( $discard = $vals.add("1") )
      #else
        #set( $discard = $vals.add("0") )
      #end
  #else
      #set( $discard = $vals.add("'$ctx.args.input[$entry]'") )
  #end
#end
#set( $valStr = $vals.toString().replace("[","(").replace("]",")") )
#set( $colStr = $cols.toString().replace("[","(").replace("]",")") )
#if ( $valStr.substring(0, 1) != '(' )
  #set( $valStr = "($valStr)" )
#end
#if ( $colStr.substring(0, 1) != '(' )
  #set( $colStr = "($colStr)" )
#end
{
  "version": "2018-05-29",
  "statements":   ["INSERT INTO <name-of-table> $colStr VALUES $valStr", "SELECT * FROM    <name-of-table> ORDER BY id DESC LIMIT 1"]
}

Sample VTL for an update mutation

#set( $update = "" )
#set( $equals = "=" )
#foreach( $entry in $ctx.args.input.keySet() )
  #set( $cur = $ctx.args.input[$entry] )
  #set( $regex = "([a-z])([A-Z]+)")
  #set( $replacement = "$1_$2")
  #set( $toSnake = $entry.replaceAll($regex, $replacement).toLowerCase() )
  #if( $util.isBoolean($cur) )
      #if( $cur )
        #set ( $cur = "1" )
      #else
        #set ( $cur = "0" )
      #end
  #end
  #if ( $util.isNullOrEmpty($update) )
      #set($update = "$toSnake$equals'$cur'" )
  #else
      #set($update = "$update,$toSnake$equals'$cur'" )
  #end
#end
{
  "version": "2018-05-29",
  "statements":   ["UPDATE <name-of-table> SET $update WHERE id=$ctx.args.input.id", "SELECT * FROM <name-of-table> WHERE id=$ctx.args.input.id"]
}

Sample resolver for delete mutation

{
  "version": "2018-05-29",
  "statements":   ["UPDATE <name-of-table> set deleted_at=NOW() WHERE id=$ctx.args.id", "SELECT * FROM <name-of-table> WHERE id=$ctx.args.id"]
}

Sample mutation response VTL with support for handling AWSDateTime

#set ( $index = -1)
#set ( $result = $util.parseJson($ctx.result) )
#set ( $meta = $result.sqlStatementResults[1].columnMetadata)
#foreach ($column in $meta)
    #set ($index = $index + 1)
    #if ( $column["typeName"] == "timestamptz" )
        #set ($time = $result["sqlStatementResults"][1]["records"][0][$index]["stringValue"] )
        #set ( $nowEpochMillis = $util.time.parseFormattedToEpochMilliSeconds("$time.substring(0,19)+0000", "yyyy-MM-dd HH:mm:ssZ") )
        #set ( $isoDateTime = $util.time.epochMilliSecondsToISO8601($nowEpochMillis) )
        $util.qr( $result["sqlStatementResults"][1]["records"][0][$index].put("stringValue", "$isoDateTime") )
    #end
#end
#set ( $res = $util.parseJson($util.rds.toJsonString($util.toJson($result)))[1][0] )
#set ( $response = {} )
#foreach($mapKey in $res.keySet())
    #set ( $s = $mapKey.split("_") )
    #set ( $camelCase="" )
    #set ( $isFirst=true )
    #foreach($entry in $s)
        #if ( $isFirst )
          #set ( $first = $entry.substring(0,1) )
        #else
          #set ( $first = $entry.substring(0,1).toUpperCase() )
        #end
        #set ( $isFirst=false )
        #set ( $stringLength = $entry.length() )
        #set ( $remaining = $entry.substring(1, $stringLength) )
        #set ( $camelCase = "$camelCase$first$remaining" )
    #end
    $util.qr( $response.put("$camelCase", $res[$mapKey]) )
#end
$utils.toJson($response)

Using Variable Map

Variable map support is limited and does not differentiate numbers and strings data types, please inject them directly if needed.

Will be escaped properly: null, true, and false values.

{
  "version": "2018-05-29",
  "statements":   [
    "UPDATE <name-of-table> set deleted_at=NOW() WHERE id=:ID",
    "SELECT * FROM <name-of-table> WHERE id=:ID and unix_timestamp > $ctx.args.newerThan"
  ],
  variableMap: {
    ":ID": $ctx.args.id,
##    ":TIMESTAMP": $ctx.args.newerThan -- This will be handled as a string!!!
  }
}

Requires

• serverless framework
• serverless-appsync-plugin
• serverless-offline
• serverless-dynamodb-local (when using dynamodb resolvers only)
• watchman (if Hot-reloading is desactivated it is not required)

Author: Serverless-appsync
Source Code: https://github.com/serverless-appsync/serverless-appsync-simulator 
License: MIT License

#serverless #sync #graphql 

How to Install Microsoft Teams on Ubuntu 20.04

Microsoft Teams is a communication platform used for Chat, Calling, Meetings, and Collaboration. Generally, it is used by companies and individuals working on projects. However, Microsoft Teams is available for macOS, Windows, and Linux operating systems available now.

In this tutorial, we will show you how to install Microsoft Teams on Ubuntu 20.04 machine. By default, Microsoft Teams package is not available in the Ubuntu default repository. However we will show you 2 methods to install Teams by downloading the Debian package from their official website, or by adding the Microsoft repository.

Install Microsoft Teams on Ubuntu 20.04

1./ Install Microsoft Teams using Debian installer file

01- First, navigate to teams app downloads page and grab the Debian binary installer. You can simply obtain the URL and pull the binary using wget;

$ VERSION=1.3.00.5153
$ wget https://packages.microsoft.com/repos/ms-teams/pool/main/t/teams/teams_${VERSION}_amd64.deb

#linux #ubuntu #install microsoft teams on ubuntu #install teams ubuntu #microsoft teams #teams #teams download ubuntu #teams install ubuntu #ubuntu install microsoft teams #uninstall teams ubuntu

Install VirtualBox in Ubuntu 21.04/20.04/18.04 › Servo Node

VirtualBox is a widely known and open-source tool offered by Oracle. It’s a cross platform virtualization application that can be installed on any system that allows users to run a number of guest operating systems on single machine over a virtual system.

Means, with the usage of VirtualBox on your system, you can easily install many operating systems and can run them simultaneously which can be helpful to develop, demonstrate, deploy and test applications on a single machine.

How to install VirtualBox On Ubuntu 18.04, 20.04 and 21.04?

Since the virtualization system offered by Oracle is available for cross platforms, even Ubuntu users can install the app and take its benefits. In order to install VirtualBox in Ubuntu variants, there’s a number of approaches that can be helpful.

Installing using default repository

sudo apt install virtualbox

Install using official DEB package

Visit the Virtualbox download page and download DEB package in your machine, and run the following command to install the package using ATP command.

sudo apt install ./virtualbox-6.1_6.1.22-144080_Ubuntu_bionic_amd64.deb

for more approaches and information, Read Here

#install virtual box on ubuntu #install virtual box on ubuntu 18.04 #install virtual box on ubuntu 20.04 #install virtual box on ubuntu21.04

How to Install TeamViewer on Ubuntu 20.04

TeamViewer is a cross-platform, proprietary application that allows a user to remotely connect to a workstation, transfer files, and have online meetings. In this tutorial, we will walk you through how to install TeamViewer on Ubuntu 20.04 Desktop through the command line.

Prerequisites

Before continuing with this tutorial, make sure you are logged in as a user with sudo privileges.

Installing TeamViewer on Ubuntu

01- To install TeamViewer, first, download the TeamViewer .deb package. So, open the Terminal and run the following wget command.

$ wget https://download.teamviewer.com/download/linux/teamviewer_amd64.deb

02- Once you have downloaded the TeamViewer‘s Debian package, execute the following command to install Teamviewer:

$ sudo apt install ./teamviewer_amd64.deb

The system will prompt you with a [Y/n] option. Type ‘Y‘ and hit the enter key in order for to continue the installation.

03- Once the installation is done, you can launch TeamViewer either by typing the command teamviewer in your terminal or by clicking on the TeamViewer icon (Activities -> TeamViewer).

04- A pop-up License Agreement will be displayed. To proceed, click on the Accept License Agreement button.

#linux #ubuntu #install teamviewer #install teamviewer ubuntu #teamviewer #teamviewer ubuntu #teamviewer ubuntu install #ubuntu install teamviewer

How to Install PgAdmin 4 on Ubuntu 20.04

pgAdmin is the leading graphical Open Source management, development and administration tool for PostgreSQL. pgAdmin4 is a rewrite of the popular pgAdmin3 management tool for the PostgreSQL database.

In this tutorial, we are going to show you how to install pgAdmin4 in Server Mode as a web application using apache2 and Wsgi module on Ubuntu 20.04 LTS.

#databases #linux #ubuntu #install pgadmin4 #install pgadmin4 ubuntu #install pgadmin4 ubuntu 20 #pgadmin4 #ubuntu pgadmin4 #ubuntu pgadmin4 install