Certified DevOps Programming Expert



The DevOps Programming Expert course is designed for professionals who aspire to lead DevOps teams, make a significant impact on software delivery, and excel in client-facing technical roles. If your ambition fit this profile and are ready to take your DevOps career to the next level, this course is your pathway to success.

Candidate Profile: DevOps Programming Expert Course


  • Experience: Minimum 6 years of professional experience in the IT industry.
  • Role: Currently working in a role that involves programming or system administration.

Why Join the DevOps Programming Expert Course:

  • Skills Enhancement
  • Leadership Opportunities
  • Career Advancement
  • Industry Recognition
  • Hands-On Experience

Course Duration: Approximately 2.5 months

Hourly Breakup (Total: Approx. 120 hours)

Common DevOps Topics (Modules 1-11):

  • Modules 1-11: 40 hours (Introduction to DevOps Concepts, Terminology, Datacenter Concepts, Virtualization with Virtualbox, Cloud Computing Concepts, 12 Factor App & Microservices, AWS Cloud Administration, Linux Proficiency, Shell Scripting, Programming Proficiency – Python & Ruby, Vagrant Essentials)
  • Total: 12 hours

DevOps Programming Expert Topics (Modules 12-20):

  • Module 12-21: 90 hours (Docker Compose Coding ,Kubernetes Helm Charts , Terraform Modular Coding ,CloudFormation Coding in AWS ,Ansible Modular Coding , Chef Modular Coding, Puppet Modular Coding , GitHub Actions Coding , Jenkins Pipelines Coding , Nagios, Prometheus, Grafana )
  • Total: 90 hours

Please note that the exact duration of the training may vary a little bit based on the pace of the batch, since we provide ample time to absorb concepts and practice in a hands on manner to everyone before moving on. Also there will be revision and recap sessions throughout the course.We will track everyone’s progress separately and if need be we will supply additional resources and support to help them to keep up with the course.

According to Glassdoor, the average salary for Senior DevOps Engineers in India, equipped with extensive programming knowledge, soars to ₹17,00,000 per year with 6-10 years of experience. But here’s the exciting part – the top 10% of these skilled professionals can command impressive salaries, reaching up to ₹40,00,000 per annum. When you equip yourself with the skills and knowledge from our DevOps Programming Expert course, you’re setting the stage for a rewarding financial future.

Mapped to Your Aspirations: The DevOps Programming Expert course has been meticulously crafted to align with the role of a Senior DevOps Engineer. We understand that Senior DevOps Engineers are the linchpin of any successful DevOps team. They’re the team leaders, the guides, and the technical experts responsible for steering their team through complex challenges. Armed with in-depth implementation expertise, they are the ones who ensure timely and top-notch deliveries, ultimately delighting the customer.

What Awaits You:

  • Immerse in DevOps Programming: Dive deep into Docker Compose, Kubernetes Helm Charts, Terraform, Ansible, Chef, and Puppet. Learn to master GitHub Actions, Jenkins Pipelines, and harness the power of Nagios, Prometheus, Grafana, and more.
  • Hands-On Experience: Gain practical experience through hands-on projects designed to simulate real-world scenarios. Grasp the art of infrastructure automation, container orchestration, and CI/CD pipeline management.
  • Programming Proficiency: Transition from scripting to programming with Python and Ruby. Discover how to code your way to efficiency, scalability, and reliability.
  • Cloud DevOps Excellence: Acquire the skills needed to excel in cloud-native environments with AWS DevOps and Azure DevOps concepts and demonstrations.


Course Outline
Module 1: Foundational DevOps Concepts
  1. Introduction to DevOps Principles
  2. Significance of Collaboration in DevOps
  3. Streamlining Software Delivery Processes
Module 2: DevOps Terminology
  1. Building a Vocabulary for Effective Communication
  2. Industry-Standard DevOps Terminologies
  3. Enhancing Corporate Collaboration Through Terminology
Module 3: Datacenter Concepts
  1. Core Infrastructure Concepts
  2. Modern Data Center Architectures
  3. Bridging Traditional and Contemporary Infrastructures
Module 4: Virtualization with Virtualbox Administration
  1. Traditional Virtualization Techniques
  2. Hands-On Experience with Virtualbox Administration
  3. Resource Optimization Strategies
Module 5: Cloud Computing Concepts
  1. Fundamental Cloud Computing Concepts
  2. Comparing Cloud and Traditional Data Centers
  3. Preparing for a Cloud-Driven World

Module 6: 12 Factor App & Microservices
  1. Exploring Modern Application Design Principles
  2. Deep Dive into the 12 Factor App Methodology
  3. Mastering the Art of Microservices Architecture
Module 7: AWS Cloud Administration
  1. Understanding Cloud Environments
  2. In-Depth Focus on Amazon Web Services (AWS)
  3. Navigating the AWS Cloud Landscape
Module 8: Linux Proficiency
  1. Essential Linux User Skills
  2. Linux as the Primary Platform for DevOps Tools
  3. Maximizing Linux Proficiency for Tool Deployment
Module 9: Shell Scripting
  1. Building a Strong Foundation in Scripting
  2. Unlocking the Power of Algorithms and Coding Through Scripting
  3. Automation Techniques for DevOps Processes
Module 10: Programming Proficiency (Python & Ruby)
  1. Transitioning from Scripting to Full-Fledged Programming
  2. Harnessing the Power of Python and Ruby
  3. Leveraging Programming for DevOps Automation
Module 11: Vagrant Essentials
  1. Vagrant as the Bedrock for Automation
  2. Practical Application of DevOps Concepts with Vagrant
  3. Accelerating Software Release Cycles Through Automation
Module 12: Docker Compose Coding
  1. What: Managed container platform
  2. Why: Software Developers bundle their code with Docker in the model of Immutable Infrastructure-based application deployments. DevOps programmers need to know how to enable developers by supplying appropriate Dockerfile codes to ease such bundling processes.
  3. Topics :
    • Introduction to Docker Compose
    • Understanding Docker Containers
    • Docker Compose YAML Configuration
    • Managing Multi-Container Applications
    • Building Custom Docker Images
    • Best Practices for Docker Compose
    • Docker Compose in Microservices
    • Alternative Container Solutions (ECS, ECR)
Module 13: Kubernetes Helm Charts
  1. What: Managed container orchestration platform
  2. Why: New-age application deployments are all happening as microservices on some form of Kubernetes. As a DevOps programmer, it is important to be well-versed with Kubernetes’s YAML coding.
  3. Topics :- 
    • Introduction to Helm
    • Helm Chart Structure
    • Managing Dependencies with Helm
    • Creating Custom Helm Charts
    • Helm Chart Versioning
    • Helm Charts for Stateful Applications
    • Deploying Helm Charts in Kubernetes
    • Alternative Container Orchestration Platforms (EKS, GKE)
Module 14: Terraform Modular Coding
  1. What: Infrastructure Orchestration as Code
  2. Why: Terraform is the most popular infrastructure-as-code solution for orchestrating API solutions and most cloud platforms. For a DevOps Programmer, the ability to control infrastructure as code is crucial.
  3. Topics :-
    1. Introduction to Terraform
    2. Terraform Configuration Files
    3. Variables and Outputs in Terraform
    4. Infrastructure as Code (IaC) Principles
    5. Creating Reusable Terraform Modules
    6. Terraform State and Remote Backends
    7. Terraform Best Practices
    8. Infrastructure Orchestration with CloudFormation
Module 15: CloudFormation Coding in AWS
  1. What: Infrastructure Orchestration as Code
  2. Why: AWS is the most popular cloud, and CloudFormation is the native orchestration-as-code solution in it. Many companies running solely on AWS see value in using CloudFormation. Sometimes, the latest AWS features are only supported on CloudFormation and not on Terraform.
  3. Topics :- 
    1. AWS Infrastructure as Code (IaC)
    2. AWS CloudFormation Templates
    3. Creating AWS Resources with CloudFormation
    4. AWS CloudFormation Stack Management
    5. Parameterization and Outputs in CloudFormation
    6. Advanced AWS CloudFormation Features
    7. Terraform vs. CloudFormation
    8. Using CloudFormation for AWS DevOps
Module 16: Ansible Modular Coding
  1. What: Infrastructure Configuration Automation as Code
  2. Why: Ansible is the fastest-growing infrastructure-as-code solution for managing servers. A DevOps Programmer should know the three major DevOps coding languages: Puppet, Chef, and Ansible.
  3. Topics :-
    1. Introduction to Ansible
    2. Ansible Playbooks and YAML
    3. Ansible Inventory and Variables
    4. Ansible Modules and Plugins
    5. Creating Reusable Ansible Roles
    6. Ansible Vault for Secrets Management
    7. Ansible Best Practices
    8. Comparing Ansible with Other Configuration Management Tools (Puppet, Chef)
Module 17: Chef Modular Coding
  1. What: Infrastructure Configuration Automation as Code
  2. Why: Chef is a highly scalable agent-based infrastructure-as-code solution for managing servers. A DevOps Programmer should know the three major DevOps coding languages: Puppet, Chef, and Ansible.
  3. Topics :
    1. Introduction to Chef
    2. Chef Cookbooks and Recipes
    3. Managing Nodes with Chef
    4. Chef Attributes and Templates
    5. Creating Custom Chef Resources
    6. Chef Environments and Roles
    7. Chef Best Practices
    8. Chef vs. Ansible vs. Puppet
Module 18: Puppet Modular Coding
  1. What: Infrastructure Configuration Automation as Code
  2. Why: Puppet is one of the first enterprise agent-based infrastructure-as-code solutions for managing servers. A DevOps Programmer should know the three major DevOps coding languages: Puppet, Chef, and Ansible.
  3. Topics :-
    1. Introduction to Puppet
    2. Puppet Manifests and Classes
    3. Puppet Nodes and Facts
    4. Puppet Modules and Forge
    5. Puppet Hiera for Data Separation
    6. Puppet Environments and Roles
    7. Puppet Best Practices
    8. Puppet vs. Ansible vs. Chef
Module 19: GitHub Actions Coding
  1. What: Cloud-based CICD as Code
  2. Why: GitHub is the most popular development platform. A DevOps Programmer is expected to understand how to work on GitHub and use GitHub Actions as a CICD solution.
  3. Topics :
    1. GitHub Actions Introduction
    2. GitHub Actions Workflow Configuration
    3. GitHub Actions for CI/CD
    4. Custom GitHub Actions Actions
    5. Managing Secrets in GitHub Actions
    6. GitHub Actions Best Practices
    7. GitHub Actions vs. Jenkins
Module 20: Jenkins Pipelines Coding
  1. What: CICD
  2. Why: Jenkins is the leading CICD platform, and a DevOps Programmer should know the Jenkins pipeline DSL to manage Jenkins as Code.
  3. Topics :
    1. Introduction to Jenkins Pipelines
    2. Declarative vs. Scripted Pipelines
    3. Building Continuous Integration Pipelines
    4. Creating Continuous Deployment Pipelines
    5. Jenkinsfile Syntax and Structure
    6. Jenkins Pipeline Best Practices
    7. Jenkins Pipelines vs. Other CICD Tools
Module 21: Nagios, Prometheus, Grafana
  1. What: Infrastructure Monitoring
  2. Why: Specialized monitoring tools for DevOps implementations are crucial but often neglected bits of an end-to-end DevOps automation. A fully automated pipeline should also integrate with monitoring tools.
  3. Topics :
    1. Introduction to Monitoring
    2. Nagios Setup and Configuration
    3. Nagios Monitoring Plugins
    4. Prometheus Introduction
    5. Prometheus Monitoring Configuration
    6. Grafana for Data Visualization
    7. Monitoring Best Practices
    8. Integrating Monitoring into DevOps Pipelines
Final Module: Real-World DevOps Projects

These hands-on projects cover a wide range of topics and tools, providing practical experience and technical depth necessary for a Senior DevOps Engineer role. Additionally, they offer opportunities for students to develop problem-solving skills and gain real-world experience.

Project 1: Dockerized Microservices

  • Objective: Build a microservices-based application using Docker containers.
  • Tasks:
    • Create individual Docker containers for different microservices.
    • Define inter-service communication within Docker network.
    • Utilize Docker Compose for multi-container orchestration.
    • Implement auto-scaling for microservices.
  • Why: This project will help students understand containerization, orchestration, and scaling microservices, which are crucial in modern DevOps practices.

Project 2: Kubernetes Orchestration

  • Objective: Deploy a multi-container application on a Kubernetes cluster.
  • Tasks:
    • Set up a Kubernetes cluster (locally or on a cloud platform).
    • Deploy Dockerized microservices using Kubernetes Deployment and Service objects.
    • Implement rolling updates and rollbacks.
    • Configure Ingress for external access.
  • Why: This project provides hands-on experience with Kubernetes, a fundamental skill for DevOps Engineers.

Project 3: Infrastructure as Code with Terraform

  • Objective: Create and manage infrastructure resources using Terraform.
  • Tasks:
    • Define Terraform configuration files for AWS resources.
    • Apply IaC principles to create and update resources.
    • Utilize Terraform modules for reusability.
    • Manage Terraform state.
  • Why: Understanding IaC with Terraform is essential for DevOps Engineers responsible for provisioning and managing cloud infrastructure.

Project 4: Configuration Management with Ansible

  • Objective: Automate server configuration and application deployment using Ansible.
  • Tasks:
    • Write Ansible playbooks for server setup and software installation.
    • Manage Ansible inventories and variables.
    • Implement role-based configuration management.
    • Integrate Ansible with cloud providers.
  • Why: Ansible is a widely used tool for configuration management and automation in DevOps.

Project 5: CI/CD Pipeline with Jenkins

  • Objective: Set up a CI/CD pipeline for automated software delivery.
  • Tasks:
    • Configure Jenkins to build, test, and deploy applications.
    • Create Jenkins pipelines using DSL.
    • Implement automated testing and quality checks.
    • Integrate Jenkins with version control and artifact repositories.
  • Why: CI/CD is at the core of DevOps, and Jenkins is a popular tool for building such pipelines.

Project 6: Monitoring and Alerting with Prometheus and Grafana

  • Objective: Implement a robust monitoring and alerting system.
  • Tasks:
    • Set up Prometheus for metrics collection.
    • Create custom Prometheus exporters.
    • Visualize metrics using Grafana dashboards.
    • Configure alerts based on predefined thresholds.
  • Why: Monitoring is crucial for maintaining the health and performance of DevOps systems.

Project 7: Serverless Computing with AWS Lambda

  • Objective: Build and deploy serverless functions using AWS Lambda.
  • Tasks:
    • Develop serverless functions in Python or Node.js.
    • Configure event triggers for Lambda functions.
    • Manage serverless applications using AWS SAM.
    • Monitor and troubleshoot Lambda functions.
  • Why: Serverless computing is gaining popularity, and knowledge of AWS Lambda is valuable for modern DevOps.



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