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Vagrant: Building and maintaining portable virtual software development environment

I had a new developer joining my team. But onboarding required him to successfully install all the necessary software. The project was complex with a disparate set of software, and modules required to make all of it work seamlessly. Despite best efforts, it took the developer a couple of hours to completely set up his machine.

vagrant

It set me to think if there is something that can be done to improve and expedite this onboarding. Why should it take a new developer so much time to set up his system when the very same activity has been done a couple of times before by earlier developers.

A little bit of ‘googling’ made me stumble upon some thing called Vagrant. Perhaps I was too ignorant before, but now I realize there exists better ways to handle this problem. The activity that took our developer hours can be finished in a few minutes.

Here is how Vagrant can help you set up your development environment in minutes.

  1. Install the latest version of Vagrant from https://www.vagrantup.com/downloads.html. You can download the version for your OS. You can also read more about Vagrant from https://www.vagrantup.com/docs/getting-started/
  1. After installing Vagrant, you will need to install VirtualBox from https://www.virtualbox.org

Now that you have installed Vagrant, and the Virtual Box, lets play around a bit with it.

From your bash shell you can run the following commands

$ init hashicorp/precise64

$ vagrant up

After running the above commands, you will have a fully running Virtual Machine running Ubuntu 12.04 LTS 64 bit. You can SSH into the machine with

vagrant ssh

, and when you are done playing around with your newly created virtual machine, you may choose to destroy it by running; vagrant destroy

Next Steps

Now that you have created a virtual environment, lets see how we can get started with creating a new vagrant aware project.

New Project

Setting up a new project would require us creating a new directory, and then running the init command inside the directory.

$ mkdir new_vagrant_project

$ cd new_vagrant_project

$ vagrant init

The last init command above will place a new file Vagrantfile inside the current directory. You may also choose to convert an existing project to make it vagrant aware by running the same vagrant init command from an existing directory.

So far all you have in your directory is one single file called Vagrantfile. But where is the OS? We have not yet installed it. How will my project run in my favorite OS?

Answers to above questions lie in the VirtualBox. Virtual Box is the software, which is the container for your OS. Instead of building the virtual machine from scratch, which would be slow and tedious process as all the OS files will need to be downloaded every time, Vagrant uses a base image to quickly clone the virtual machine. These base images are called boxes in vagrant, and as Vagrant website also says “specifying the box to use for your vagrant environment is the first step after creating a new Vagrantfile”.

The virtual box type or the OS need to be specified in Vagrantfile. Below is how you can tell Vagrant that you would like to use Ubuntu Precise 64 to run your application on.

Vagrant.configure(“2”) do |config|

config.vm.box = “hashicorp/precise64”

end

Vagrant gives you a virtual environment of a server with any OS of your liking. In this example, we added Precise 64 version of the Ubuntu OS. However if you would like to add anything else, you can search for options here

https://app.terraform.io/session

Its time to bootup the virtual machine. It can be done using

vagrant up

Next we can log in to the machine by running

vagrant ssh

When you are done fiddling around with the machine, you can destroy it by running vagrant destroy.

Now that the OS is ready, its time to install necessary softwares, and other dependencies. How do we do that?
Enter Ansible!!

Ansible helps us in provisioning the virtual machine booted up in the steps above. Provisioning is nothing but configuring, and installing different dependencies required to run on your application.

Ansible (http://docs.ansible.com/ansible/index.html) can be downloaded, and installed on your machine from http://docs.ansible.com/ansible/intro_installation.html#installing-the-control-machine

Please note that Ansible is not the only provisioning tool that can work with Vagrant. Vagrant works equally well with other provisioners like Puppet, Chef, etc.

The provisioner, Ansible in the current case needs to be configured with the Vagrant so that virtual machine knows how it should provision the machine after boot up.

The basic Vagrantfile Ansible configuration looks like

Vagrant.configure(“2”) do |config|

config.vm.box = “hashicorp/precise64”

config.vm.network ‘private_network’, ip: ‘192.168.1.x’

config.vm.network ‘forward_port’, guest: xxxx, host: yyyy

config.vm.provision “ansible” do |ansible|

ansible.playbook = “playbook.yml”

end
end

The configuration ‘private_network’ will give an IP to your virtual machine so that traffic can flow from/to the virtual machine.

The ‘forward_port’ configuration enables us to specify that requests coming on a port xxxx to the virtual machine from outside will be routed inside the VM on an application listening on port yyyy.

Playbook is a very integral component of Ansible. Playbook contains instructions that Ansible will execute to ready your machine. These instructions can be a list of softwares to be downloaded, and installed, or any other configuration that your application requires to function properly. Playbooks are expressed in YAML format. Each playbook is composed of one or more ‘plays’ in a list.

The goal of a play is to map a group of hosts to some well-defined roles, represented by ‘tasks’.

Here is a playbook example with just one play.

- hosts: webservers

vars:

http_port: 80

max_clients: 200

remote_user: root

tasks:

- name: ensure apache is at the latest version

yum: name=httpd state=latest

- name: write the apache config file

template: src=/srv/httpd.j2 dest=/etc/httpd.conf

notify:

- restart apache

- name: ensure apache is running (and enable it at boot)

service: name=httpd state=started enabled=yes

handlers:

- name: restart apache

service: name=httpd state=restarted

A playbook can also have multiple plays, with each play executing on a group of servers. You can also have multiple plays in a playbook, with each play running on a different group of servers as in http://docs.ansible.com/ansible/playbooks_intro.html

In the next part of this series, I will take a real example where an application requires multiple software, and configurations, and how we make use of Vagrant & Ansible to run it in the developer’s machine, and then automate deployment to the cloud servers.

In case, you any queries on Virtualizing Your Development Environment To Make It A Replica Of Production, feel free to approach us on hello@mantralabsglobal.com, our developers are here to clear confusions and it might be a good choice based on your business and technical needs.

This guest post has been written by Parag Sharma Mantra Labs CEO.

He is an 14 year IT industry veteran with stints in companies like Zapak and RedBus before founding Mantra Labs back in 2009. Since then, Mantra has dabbled in various products and is now a niche technology solutions house for enterprises and startups.

Mantra Labs is an IT service company and the core service provided by the company are Web Development, Mobile Development, Enterprise on the Cloud, Internet of Things. The other services provided by the company are Incubate start-up, provide Pro-active solutions and are Technical Partners of Funds & Entrepreneurs.

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Smart Machines & Smarter Humans: AI in the Manufacturing Industry

We have all witnessed Industrial Revolutions reshape manufacturing, not just once, but multiple times throughout history. Yet perhaps “revolution” isn’t quite the right word. These were transitions, careful orchestrations of human adaptation, and technological advancement. From hand production to machine tools, from steam power to assembly lines, each transition proved something remarkable: as machines evolved, human capabilities expanded rather than diminished.

Take the First Industrial Revolution, where the shift from manual production to machinery didn’t replace craftsmen, it transformed them into skilled machine operators. The steam engine didn’t eliminate jobs; it created entirely new categories of work. When chemical manufacturing processes emerged, they didn’t displace workers; they birthed manufacturing job roles. With each advancement, the workforce didn’t shrink—it evolved, adapted, and ultimately thrived.

Today, we’re witnessing another manufacturing transformation on factory floors worldwide. But unlike the mechanical transformations of the past, this one is digital, driven by artificial intelligence(AI) working alongside human expertise. Just as our predecessors didn’t simply survive the mechanical revolution but mastered it, today’s workforce isn’t being replaced by AI in manufacturing,  they’re becoming AI conductors, orchestrating a symphony of smart machines, industrial IoT (IIoT), and intelligent automation that amplify human productivity in ways the steam engine’s inventors could never have imagined.

Let’s explore how this new breed of human-AI collaboration is reshaping manufacturing, making work not just smarter, but fundamentally more human. 

Tools and Techniques Enhancing Workforce Productivity

1. Augmented Reality: Bringing Instructions to Life

AI-powered augmented reality (AR) is revolutionizing assembly lines, equipment, and maintenance on factory floors. Imagine a technician troubleshooting complex machinery while wearing AR glasses that overlay real-time instructions. Microsoft HoloLens merges physical environments with AI-driven digital overlays, providing immersive step-by-step guidance. Meanwhile, PTC Vuforia’s AR solutions offer comprehensive real-time guidance and expert support by visualizing machine components and manufacturing processes. Ford’s AI-driven AR applications of HoloLens have cut design errors and improved assembly efficiency, making smart manufacturing more precise and faster.

2. Vision-Based Quality Control: Flawless Production Lines

Identifying minute defects on fast-moving production lines is nearly impossible for the human eye, but AI-driven computer vision systems are revolutionizing quality control in manufacturing. Landing AI customizes AI defect detection models to identify irregularities unique to a factory’s production environment, while Cognex’s high-speed image recognition solutions achieve up to 99.9% defect detection accuracy. With these AI-powered quality control tools, manufacturers have reduced inspection time by 70%, improving the overall product quality without halting production lines.

3. Digital Twins: Simulating the Factory in Real Time

Digital twins—virtual replicas of physical assets are transforming real-time monitoring and operational efficiency. Siemens MindSphere provides a cloud-based AI platform that connects factory equipment for real-time data analytics and actionable insights. GE Digital’s Predix enables predictive maintenance by simulating different scenarios to identify potential failures before they happen. By leveraging AI-driven digital twins, industries have reported a 20% reduction in downtime, with the global digital twin market projected to grow at a CAGR of 61.3% by 2028

4. Human-Machine Interfaces: Intuitive Control Panels

Traditional control panels are being replaced by intuitive AI-powered human-machine interfaces (HMIs) which simplify machine operations and predictive maintenance. Rockwell Automation’s FactoryTalk uses AI analytics to provide real-time performance analytics, allowing operators to anticipate machine malfunctions and optimize operations. Schneider Electric’s EcoStruxure incorporates predictive analytics to simplify maintenance schedules and improve decision-making.

5. Generative AI: Crafting Smarter Factory Layouts

Generative AI is transforming factory layout planning by turning it into a data-driven process. Autodesk Fusion 360 Generative Design evaluates thousands of layout configurations to determine the best possible arrangement based on production constraints. This allows manufacturers to visualize and select the most efficient setup, which has led to a 40% improvement in space utilization and a 25% reduction in material waste. By simulating layouts, manufacturers can boost productivity, efficiency and worker safety.

6. Wearable AI Devices: Hands-Free Assistance

Wearable AI devices are becoming essential tools for enhancing worker safety and efficiency on the factory floor. DAQRI smart helmets provide workers with real-time information and alerts, while RealWear HMT-1 offers voice-controlled access to data and maintenance instructions. These AI-integrated wearable devices are transforming the way workers interact with machinery, boosting productivity by 20% and reducing machine downtime by 25%.

7. Conversational AI: Simplifying Operations with Voice Commands

Conversational AI is simplifying factory operations with natural language processing (NLP), allowing workers to request updates, check machine status, and adjust schedules using voice commands. IBM Watson Assistant and AWS AI services make these interactions seamless by providing real-time insights. Factories have seen a reduction in response time for operational queries thanks to these tools, with IBM Watson helping streamline machine monitoring and decision-making processes.

Conclusion: The Future of Manufacturing Is Here

Every industrial revolution has sparked the same fear, machines will take over. But history tells a different story. With every technological leap, humans haven’t been replaced; they’ve adapted, evolved, and found new ways to work smarter. AI is no different. It’s not here to take over; it’s here to assist, making factories faster, safer, and more productive than ever.

From AR-powered guidance to AI-driven quality control, the factory floor is no longer just about machinery, it’s about collaboration between human expertise and intelligent systems. And at Mantra Labs, we’re diving deep into this transformation, helping businesses unlock the true potential of AI in manufacturing.

Want to see how AI-powered Augmented Reality is revolutionizing the manufacturing industry? Stay tuned for our next blog, where we’ll explore how AI in AR is reshaping assembly, troubleshooting, and worker training—one digital overlay at a time.

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