Mastering DevOps 2.0

10 WEEKS

15 MODULES

4 PROJETCS

1K LEARNERS

06+

Focused Niche IT Tech Bootcamps

500+

5 Star Reviews on Google

1000+

Success Stories and counting..

Infinite

happy, satisfied Pragraites

About Program

Mastering DevOps Tools program is full hands-on comprehensive learning solution to advance your career as a Cloud & DevOps Engineer. This DevOps 2.0 program will provide you full insight into the fast-growing domain of DevOps. You will master the skills required for application continuous integration & continuous deployment, end-to-end product automation, config management, Platform-as a-service as well as Infrastructure-as-a-service. This new program come equipped with co-working opportunities to further strengthen your learning as well as post program placement support.

PROGRAM DETAILS

Program Duration

This Program will be delivered in few Weeks. There will be 2 classes per week.

Classes Details

Every Sunday : 10:00 AM - 0 2:00 PM Every Wednesday : 8:30PM - 10:30 PM

Program Fee

Please contact our team for ISA, Scholarships and Financial Aid available.

How You Will Learn

Hiring Companies

Program Curriculum

Our curriculum development team analyses the 100’s of job postings in the local and international markets, followed by a discussion with hiring managers to keep the focus on the area more relevant to you and companies.

MODULE 1 - INTRODUCTION TO DEVOPS

Module will cover the principles of DevOps. The concepts of bridging the gap between software development and operations. We will discuss the Dev and Ops Stereotypes: Perceptions and Realities. The fundamentals of DevOps business goals and what cloud & DevOps is doing for enterprises.

1. Program Features and Attractions
2. DevOps and Cloud Solution Fundamentals
3. DevOps Roles and Core Concepts
4. Legacy System Problems and Solutions
5. DevOps Principles, patterns and frameworks

MODULE 2 - LINUX FUNDAMENTALS

Module will cover the fundamentals of Linux and cloud computing; you will be developing skill to run the jobs on Linux and accessing a Linux machine on AWS cloud

1. Introduction to Operating Systems.
2. Overview of Linux Operating System.
3. Basic components & commands like ls, grep.
4. Advance command like find, dpkg etc.
5. vi, vim, emacs Editor and File Systems
6. Spinning a Linux System on cloud
7. ssh & Sftp in action using user/pass and private/public key.
8. Basic & Advanced shell scripting
9. Package Management and User Administration
10. Yum, dpkg, apt, sysctl and bootlo

MODULE 3 - VAGRANT

Module will cover the virtual machine environment management and basic virtualization skills and provide a
hands-on knowledge of it. It leverages a declarative configuration file which describes all your software
requirements, packages, operating system configuration, users, and more.

1. Vagrant Introduction and Installation.
2. Plugins and Provisioning
3. Managing Boxes

Install a virtual box on your machine and add a vagrant box.
Initialize vagrant box and prepare the ground for work.

MODULE 4 - MASTERING GIT

The module will cover the fundamentals of Git and enable participants to use Git version control and manage the project efficiently.

1. Introduction to Source Code control systems.
2. Overview of Git and Workflow
3. Creating/Cloning/Committing a new repo.
4. Branching & Merging in git
5. Fix merge conflicts and mistakes
6. Merge requests/pull requests.
7. Remote and Rebase in git
8. Bitbucket, Gitlab CI

Term Project 1: Setting up the GitLab project and defining the branch strategy and authoring the merge.

MODULE 5 - JENKINS

Module will cover the fundamentals of Continuous Integration and Continuous Deployments and integrations with other tools. At the end of module, you would be able to create automated pipelines

1. Jenkins and Installation
2. Configuring Master, Slave and multimode
3. Set up a job and pipeline
4. Build, Integrate and delivery pipeline
5. Pipeline as a Code

Term Project 2: Setup a Java application CI/CD with Jenkins and deploy the application on AWS
Term Project 3: Setup a Web application CI/CD with Jenkins and deploy the application on GCP

MODULE 6 - AWS FUNDAMENTALS

Module will cover the implementation of Cloud computing, deployment models and cloud virtualization. Our focus will be on compute and networking modules of AWS

1. Introduction to AWS and Cloud Infrastructure
2. AWS Elastic Compute Cloud and Types
3. AWS Virtual Private Cloud and Implementation
4. Custom VPCs vs Load balancer
5. AWS architecture and Security

Prepare a Linux-based EC2 instance on AWS and connect with the Github repository.

MODULE 7 - GCP FUNDAMENTALS

Module will help you gain a solid understanding of the various components of the Google Cloud Platform.

1. Introduction to GCP and Cloud Infrastructure
2. Deploy an application to Container and Compute Engine
3. GCP Networking
4. Systems Operations
5. Autoscaling and load balancing

Prepare an e2-micro on GCP and connect with Jenkins pipeline.

MODULE 8 - DOCKER AND CONTAINERIZATION

The module will help you to master the core fundamentals of continuous deployment using Docker. We will Simplify and accelerate cloud-native application development and will start the containerization journey

1. Installation and configuration
2. Managing containers
3. Node networking
4. Build process in docker
5. Writing Docker files and Docker Compose
6. Managing local images and customization
7. Docker Registry and Private Registry

Prepare a container-based environment and deploy a web application along with standard API gateway implementation.

MODULE 9 - DOCKER SWARM

Module will cover the Build, automate, and monitor a server cluster for containers using the Linux. We will
discuss two types of Docker Swarm mode services.

1. Clustering
2. Scheduling
3. Swarm App Lifecycle
4. Replicated services
5. Global services

Term Project 4: Set up a multi-tier application with Load balancer, Database, Caching & deploy on swarm cluster.

MODULE 10 - KUBERNETES AND DEPLOYMENTS

Module will cover the automating deployment, scaling, and management of containerized applications.
Letting you effortlessly manage workloads and learn ecosystem of deployment solutions.

1. Deploy kube cluster on AWS/GCP
2. Basic of kubectl and Mini Cube
3. Kubernetes Architecture, Pods, Services
4. Deploy and Scale on Kube
5. DNS & Server discovery
6. Auto-scaling and rolling updates
7. Namespace and Quotas
8. Deploying Microservices on Kubernetes

Term Project 5: Deploy Project 4 on the Kubernetes cluster hosted on GCP.
Term Project 6: Deploy Kong Ingress on GCP with microservices deployment

MODULE 11 - TERRAFORM AND INFRA AUTOMATION

Module will help you to create, manage and maintain resources using Terraform and gain experience using Terraform to provision resources in cloud environments.

1. Introduction to Infrastructure as Code
2. Terraform Installation & Workflows
3. Configuration Management & Orchestration
4. Provisioning and Deployments

Term Project 7: Deploy the resources using terraform on AWS and GCP

MODULE 12 - ANSIBLE & ENVIRONMENTS PREPARATION

Module will start with orchestration and change management fundamentals then move to how Ansible works. We will learn the ad-hoc commands across all systems, write playbooks, and create roles using the modules.

1. Ansible Configuration and installation
2. Ansible inventories and modules
3. Ansible playbooks and variables, facts
4. Playbook modules
5. Ansible Vault
6. Ansible plugins and roles

Term Project 8: Deploy EC2 machine on AWS and deploy an application using ansible.

MODULE 13 - MONITORING TOOLS

Module will help you to master the core fundamentals of continuous deployment using Docker. We will Simplify and accelerate cloud native application development and will start the containerization journey.

1. Grafana
2. Datadog
3. Nagios
4. Splunk

Term Project 9: Set up an elastic search cluster on AWS and route all the logs from cloudwatch to the kibana dashboard and execute queries to debug

MODULE 14 - CAPSTONE PROJECT

Prepare a code pipeline and deploy to a cluster-based environment in blue/green deployment model and apply the skills and knowledge which were developed throughout the cohort. For Example: Deploy a Microservice on Kubernetes cluster for the hiring platform with one of our client.

Data Analytics Training FAQs

What Does a Data Analyst do?

Data analysts play a unique role among the many data-centric jobs often found in today’s businesses. A Data Analyst commonly works on collecting and interpreting data, analyzing the outcome, and reporting the results back to the relevant team. A Data Analyser also works closely with identifying patterns and trends in data sets, working alongside organizations within the business or the management team to establish business needs, define new data collection and analysis processes, and add real value to a company.

How do I become a Data Analyst?

This Data Analyst course developed in collaboration with IBM will give you sufficient insights into data analysis tools and methodologies to excel in your next role as a Data Analyst. You will earn an industry-recognized certificate from IBM and Simplilearn that will attest to your new skills and on-the-job expertise. The Data Analytics certification course online will train you on statistics essentials, SQL basics, data science, and data visualization using R and Python, Business Analytics with Excel, Power BI, and Data Visualization with Tableau Desktop 10.

What is the average salary of a Data Analyst?

Although data analysts are well-paid worldwide and exponential demand for data analysts will never decline, data analysts’ salaries vary in different sectors and nations. Data analysts’ salaries depend on their skills, experience, company & location. Our Data Analyst course helps you achieve a higher salary, expertise, and skills to succeed in this lucrative growing profession. The average annual salary in top countries is:

India: Rs. 440846
US (New York): $74,229
New Zealand: $70,000
Canada: $61,766

How to learn Data Analytics?

Data Analytics is one of the major areas to explore in this digitalized world. To learn data analytics, you need to have an in-depth understanding of SQL, Python or R programming, data visualization techniques, statistics, regression, and more. While you can get started on your own, it is recommended to enroll in a University partnered Data Analytics Program to learn data analytics from Purdue faculty. You’ll get up-to-date knowledge of the field and know about the strategies and best practices that are actually followed by companies.

What are the modules covered in this Data Analytics course?

This Data Analytics certification course consists of the following modules:

Introduction to Data Analytics Business
Analytics with Excel
Programming Basics and Data Analytics with Python
Tableau
Power BI
Data Analytics with Python
Data Science with R Programming
Data Analyst Capstone

Will this course help me to start my career as Data Analyst?

Yes, anyone embarking on a career as Data Analyst can take these Data Analytics courses. Getting certified will demonstrate your seriousness towards the field and help you build a strong foundation in data analytics concepts.

Program Fee - $1500.00

Admissions are closed once the requisite number of participants enroll for the upcoming cohort.
Apply early to secure your seat.

Popular