Multi Cloud DevOps Course Training

1. What is an Application?

2. Types of Applications

3. Web Application Fundamentals

4. Web Technologies: (List key technologies and their roles)

Frontend: HTML, CSS, JavaScript, React

Backend: Python, Java, Node.js

Databases: SQL (MySQL, PostgreSQL), NoSQL (MongoDB).

5. Software Development Life Cycle (SDLC)

Phases: Planning, Analysis, Design, Implementation (Coding), Testing, Deployment, Maintenance.

6. Application Development Methodologies

Agile: Core principles, Scrum, Kanban

Waterfall

1. What is Data

2. Types of Data

3. Data Storage

4. Data Analysis

5. Data Engineering

6. Data Science

1. The Importance of Computing Power

2. Key Computing Technologies:

CPU (Central Processing Unit)

GPU (Graphics Processing Unit)

3. Cloud Computing:

What is the Cloud?

Cloud Service Models:

IaaS (Infrastructure as a Service)

PaaS (Platform as a Service)

SaaS (Software as a Service)

1. What is Artificial Intelligence (AI)?

2. How AI Works?

3. Key Concepts:

Machine Learning (ML)

Deep Learning (DL)

4. Generative AI:

What is Generative AI?

Examples: Large Language Models (LLMs), image generation models.

5. AI in Everyday Learning

1. Customer Relationship Management (CRM)

2. Human Resource Management Systems (HRMS)

3. Retail & E-Commerce

4. Healthcare

Topics:

1. Introduction to Linux OS

Exploring the fundamentals of the Linux operating system and its importance in DevOps environments.

2. Linux Distributions and Architecture

Understanding various Linux distributions and the architecture of Linux-based systems.

3. Command Line Interface (CLI) & Filesystem

Mastering the CLI and understanding how to navigate and manage the Linux filesystem.

4. File Management and vi Editor

Techniques for managing files in Linux, including file manipulation and editing with vi.

5. Archives and Package Management

Utilizing tools like tar and zip for file archiving and managing packages in Linux.

6. System Installation and Package Managers

Installing and managing software using package managers such as APT and YUM.

7. Users, Groups, and Permissions

Managing users and groups, and configuring file and system permissions to maintain security.

8. Networking Basics: IP Address, Protocols, & Ports

Understanding basic networking concepts like IP addressing, protocols, and port management in Linux.

9. Firewalls and Security Measures

Configuring firewalls and implementing security best practices to protect Linux-based systems.

10. Load Balancers

Introduction to load balancing techniques in Linux environments for improving scalability and reliability.

Topics:

1. Introduction to Version Control System

Basics of version control systems and their role in managing software code and collaboration.

2. Centralized vs Distributed Version Control Systems

Exploring the differences between centralized and distributed version control systems with practical examples.

3. Git & GitHub Introduction

Overview of Git as a distributed version control system and GitHub as a platform for hosting and collaborating on Git repositories.

4. Git Workflow

Understanding the typical workflow in Git, including stages of code changes, commits, and push/pull operations.

5. GitHub for Collaboration

Using GitHub for effective collaboration in teams, including issues, pull requests, and project boards.

6. Git Branching Model

Strategies for managing different branches in Git, including feature branches, master/main, and release branches.

7. Git Merging and Pull Requests

Techniques for merging code and using pull requests for collaborative code review and integration.

8. Git Rebase

A deep dive into Git rebase, its advantages, and how it improves the Git history.

9. Handling Detached Head and Undoing Changes

Best practices for managing detached HEAD states in Git and methods to undo changes or revert commits.

10. Advanced Git Features: Git Ignore, Tagging

Leveraging `.gitignore` for excluding unwanted files from version control and tagging releases for version management.

Topics:

1. Introduction to Containerisation

The basics of container technology and how Docker revolutionizes software deployment and scalability.

2. Monolithic vs Microservices Architecture

Comparison of traditional monolithic architecture vs modern microservices approaches in application design.

3. Introduction to Virtualisation and Containerisation

Understanding virtualization and how containerisation offers a more efficient and scalable alternative.

4. Docker Architecture

An in-depth exploration of Docker’s architecture and its core components, including Docker daemon, images, and containers.

5. Setting up Docker

Guidelines for installing Docker and configuring it on various operating systems and environments.

6. Docker Registry, Images, and Containers

Exploring Docker images, container creation, and the role of Docker registries for storing and sharing images.

7. Running Docker Containers

Managing Docker containers, including lifecycle operations such as starting, stopping, and scaling containers.

8. Docker Volumes and Networks

How to use Docker volumes for persistent storage and Docker networks for inter-container communication.

9. Docker Logs and Tags

Handling Docker container logs for troubleshooting and using tags for managing image versions.

10. Dockerize Applications and Docker Compose

Best practices for containerizing applications and orchestrating multi-container applications using Docker Compose.

Topics:

1. Introduction to CI/CD & GitHub Actions

Overview of Continuous Integration (CI), Continuous Delivery/Deployment (CD), and the role GitHub Actions plays in automating these processes.

2. Benefits and Requirements of CI/CD with GitHub Actions

The advantages of adopting CI/CD practices using GitHub Actions, including tight integration with GitHub, free usage for public repositories, and flexibility with YAML-based workflows.

3. Setting Up GitHub Actions Workflows

Step-by-step guide to creating and configuring workflows in the .github/workflows directory.

4. Understanding GitHub Actions Syntax and Structure

Explanation of key components like name, on, jobs, runs-on, steps, uses, and run in workflow YAML files.

5. Events and Triggers

Using various events to trigger workflows (e.g., push, pull_request, schedule, workflow_dispatch).

6. Jobs and Steps Configuration

Defining jobs and steps within workflows to automate tasks like building, testing, and deploying code.

7. Actions Marketplace

Exploring and utilizing pre-built actions from the GitHub Actions Marketplace to simplify CI/CD tasks.

8. Creating Custom Actions

Developing custom actions for specific project needs.

9. Continuous Deployment with GitHub Actions

Implementing Continuous Deployment pipelines with GitHub Actions to automate software delivery to various environments (e.g., staging, production).

10. Secrets Management

Storing and using secrets securely in workflows to protect sensitive information like API keys and credentials.

11. GitHub Actions Integrations

Integrating GitHub Actions with other tools and platforms (e.g., Docker, AWS, Azure, Google Cloud, Slack) for a complete CI/CD solution.

Topics:

1. Introduction to SonarQube

What SonarQube is and how it helps in improving code quality by detecting bugs, vulnerabilities, and code smells.

2. Setting up SonarQube

Guide to installing and configuring SonarQube for code quality analysis.

3. Integrating SonarQube with CI/CD Pipelines

Automating code quality checks by integrating SonarQube with Jenkins or other CI tools.

4. SonarQube Metrics and Rules

Understanding the key metrics and quality gates provided by SonarQube to evaluate code quality.

5. Code Coverage and Test Reporting

Using SonarQube to track code coverage and report on test results to ensure high test reliability.

6. Detecting Bugs and Vulnerabilities

How SonarQube identifies security vulnerabilities and issues in the codebase, and best practices for remediation.

7. Refactoring with SonarQube Insights

Leveraging SonarQube's refactoring recommendations to improve the structure and maintainability of your code.

8. SonarQube for Code Reviews

Using SonarQube as a tool to perform automated code reviews and ensuring adherence to coding standards.

9. Customizing SonarQube Rules

Tailoring SonarQube's rule set to suit specific project needs or coding practices.

10. SonarQube Dashboards and Reports

Interpreting SonarQube's visual dashboards and reports to track code quality improvements over time.

Topics:

1. Introduction to Nexus Repository

What Nexus Repository is and how it helps in managing software artifacts in a centralized location.

2. Setting up Nexus Repository

Guide to installing and configuring Nexus Repository for storing build artifacts, libraries, and dependencies.

3. Managing Artifacts in Nexus

Understanding artifact repositories in Nexus and how to manage them effectively.

4. Nexus Repository Formats

Exploring different formats of repositories supported by Nexus, including Maven, Docker, and NPM.

5. Integrating Nexus with CI/CD Pipelines

How to integrate Nexus Repository with Jenkins or other CI/CD tools to automate artifact deployment.

6. Artifact Versioning and Metadata

Managing versions of artifacts and handling metadata to ensure traceability and consistency.

7. Nexus Proxying External Repositories

Configuring Nexus to proxy external repositories for caching dependencies and improving build efficiency.

8. Security and Access Control in Nexus

Implementing security measures and access control policies in Nexus to protect sensitive artifacts.

9. Nexus Repository Health and Monitoring

Best practices for monitoring Nexus Repository's health and ensuring its availability.

10. Nexus for Release Management

Leveraging Nexus for managing release candidates and ensuring reliable artifact deployment during releases.

Topics:

1. Introduction to High Availability

Understanding the importance of high availability in systems design.

2. Introduction to Container Orchestration

Exploring the concept and need for container orchestration.

3. Container Orchestration Tools

Overview of tools available for container orchestration including Kubernetes.

4. Overview of Kubernetes

Introduction to Kubernetes and its role in container orchestration.

5. Kubernetes Architecture

Understanding the architectural components of Kubernetes.

Topics:

1. Components of Kubernetes

Detailed look at core Kubernetes components, including master and node components.

2. Kubernetes Objects

Introduction to the fundamental objects in Kubernetes.

3. Pods

Understanding Pods, the smallest deployable units in Kubernetes.

4. Replica Sets

Role and functioning of Replica Sets in managing pods.

5. Deployments

How Deployments automate the updating and rollback of applications.

Topics:

1. Services

Introduction to Services as a way to expose applications running on a set of Pods. 2. ClusterIP

Exploring ClusterIP for internal cluster communication.

3. NodePort

Understanding how NodePort exposes services outside of the cluster.

4. Load Balancer

Using Load Balancers to distribute traffic evenly across services.

5. Ingress

Configuring Ingress for external access to services within the cluster.

Topics:

1. Config Maps

Managing application configuration using Config Maps.

2. Secrets

Securely storing sensitive information with Secrets.

3. Persistent Volume (PV) and Persistent Volume Claim (PVC)

Understanding the storage capabilities in Kubernetes with PV and PVC.

4. Storage Classes

Exploring dynamic volume provisioning through Storage Classes.

5. StatefulSets

Managing stateful applications with StatefulSets.

Topics:

1. Overview of Production Clusters

Considerations for running Kubernetes in production environments.

2. Overview of AKS

Introduction to Azure Kubernetes Service (AKS).

3. Setup AKS

Steps for setting up a Kubernetes cluster on AKS.

4. Deploy Applications On AKS

Practical guide to deploying applications on AKS.

5. Monitoring and Logging

Tools and strategies for monitoring and logging in a Kubernetes environment.

Why Python? (Simplicity, Libraries, Community Support).

Setting up Python (Anaconda, Jupyter Notebook, VS Code.

Data Types (int, float, string, list, tuple, dict).

Control Structures (if-else, loops).

Functions & Modules.

File Handling.

Classes & Objects

Inheritance & Polymorphism.

Encapsulation & Abstraction.

How OOP is used in AI (e.g., Model Classes in TensorFlow/PyTorch).

NumPy – Arrays & Numerical Computation.

Pandas – Data Manipulation & Analysis.

Matplotlib & Seaborn – Data Visualization.

Reading/Writing CSV, Excel, JSON.

Handling Missing Data.

Data Cleaning & Transformation.

Topics:

1. Introduction to High Availability

Understanding the importance of high availability in systems design.

2. Introduction to Container Orchestration

Exploring the concept and need for container orchestration.

3. Container Orchestration Tools

Overview of tools available for container orchestration including Kubernetes.

4. Overview of Kubernetes

Introduction to Kubernetes and its role in container orchestration.

5. Kubernetes Architecture

Understanding the architectural components of Kubernetes.

Topics:

1. Components of Kubernetes

Detailed look at core Kubernetes components, including master and node components.

2. Kubernetes Objects

Introduction to the fundamental objects in Kubernetes.

3. Pods

Understanding Pods, the smallest deployable units in Kubernetes.

4. Replica Sets

Role and functioning of Replica Sets in managing pods.

5. Deployments

How Deployments automate the updating and rollback of applications.

Topics:

1. Services

Introduction to Services as a way to expose applications running on a set of Pods. 2. ClusterIP

Exploring ClusterIP for internal cluster communication.

3. NodePort

Understanding how NodePort exposes services outside of the cluster.

4. Load Balancer

Using Load Balancers to distribute traffic evenly across services.

5. Ingress

Configuring Ingress for external access to services within the cluster.

Topics:

1. Config Maps

Managing application configuration using Config Maps.

2. Secrets

Securely storing sensitive information with Secrets.

3. Persistent Volume (PV) and Persistent Volume Claim (PVC)

Understanding the storage capabilities in Kubernetes with PV and PVC.

4. Storage Classes

Exploring dynamic volume provisioning through Storage Classes.

5. StatefulSets

Managing stateful applications with StatefulSets.

Topics:

1. Overview of Production Clusters

Considerations for running Kubernetes in production environments.

2. Overview of AKS

Introduction to Azure Kubernetes Service (AKS).

3. Setup AKS

Steps for setting up a Kubernetes cluster on AKS.

4. Deploy Applications On AKS

Practical guide to deploying applications on AKS.

5. Monitoring and Logging

Tools and strategies for monitoring and logging in a Kubernetes environment.

Topics

1. Cloud Concepts

Understanding the benefits and considerations of using cloud services.

Exploring Infrastructure-as-a-Service (IaaS), Platform-as-a-Service (PaaS), Software-as-a-Service (SaaS).

Differentiating between Public Cloud, Private Cloud, and Hybrid Cloud models.

Topics

1. Azure Compute

Introduction to the types of compute services offered by Azure and their use cases.

2. Azure Storage

Overview of Azure's storage options and recommendations for different data types and usage scenarios.

3. Azure Networking

Basic concepts of Azure networking solutions including virtual networks, subnets, and connectivity options.

4. Azure Database Services

Introduction to Azure's database services for relational and non-relational data.

Topics

1. Azure Pricing and Support

Understanding Azure pricing, cost management tools, and Azure support plans and services.

2. Azure Governance

Azure governance methodologies, including Role-Based Access Control (RBAC), resource locks, and Azure Policy.

Topics

1. Azure Portal and Azure CLI

Utilizing the Azure Portal and Azure Command-Line Interface (CLI) for managing Azure services.

2. Azure Management Tools

Introduction to Azure management tools like Azure Monitor, Azure Resource Manager, and Azure Policy for efficient resource management.

Topics

1. App Services

Overview of Azure App Service plans, networking for an App Service, and container images.

Understanding how to deploy and manage web apps and APIs using Azure App Services.

Fundamentals of Cloud Computing

Walk through AWS Free Tier Account

AWS Management Console

Cloud Offerings

Public vs Private vs Hybrid

Infrastructure As A Service

IAAS

Platform As A Service

PAAS

Software As A Service

SAAS

AWS Regions

AWS Availability Zones

VPC Components

Internet Gateway

Subnets

Route Tables

Network Access Control List

NACL

Security Group

VPC Requirement

VPC Subnetting

VPC Requirement

Build Custom VPC

Introduction To EC2

EC2 Components

EC2 Instance Setup

SSH Clients

GitBash

Putty

Terminal

AWS Key Pairs

Apache Web Server Setup

Hosting Web Application

Public IP

Private IP

Elastic IP

Godaddy

DNS Setup

Configuring DNS for Website Mapping

Intro To Databases

IAAS Databases vs PAAS Database

Host IAAS Databases

Host PAAS Databases

Setup Web Application For IAAS DB

Setup Web Application For PAAS RDS

Introduction to Generative AI

1. What is Generative AI?

2. Key Applications:

Text (ChatGPT, Claude, LLaMA)

Images (DALL·E, MidJourney, Stable Diffusion)

Audio (Music Generation, Voice Cloning)

Code (GitHub Copilot, Cursor)

3. Evolution of GenAI:

Rule-Based → Deep Learning → Transformers

GANs vs. VAEs vs. LLMs

1. Effective Prompt Design

Instruction-Based, Few-Shot, Zero-Shot

2. Advanced Techniques:

Chain-of-Thought (CoT) Prompting

Self-Consistency & Iterative Refinement

Hands-on:

Optimizing prompts for GPT-4, Claude, LLaMA

Transformer Architecture

1. Why Transformers? (Limitations of RNNs/LSTMs)

2. Key Components:

Self-Attention & Multi-Head Attention

Encoder-Decoder (BERT vs. GPT)

3. Evolution: BERT → GPT → T5 → Mixture of Experts

4. Large Language Models (LLMs)

5. Pre-training vs. Fine-tuning

6. Popular Architectures:

GPT-4, Claude, Gemini, LLaMA 3

BERT (Encoder-based) vs. T5 (Text-to-Text

Introduction to AI Agents

1. What are AI Agents?

2. vs. Traditional AI:

3. Applications:

AI Agent Frameworks

1. CrewAI (Multi-Agent Collaboration):

2. n8n (Workflow Automation):

Designing AI Agents

CrewAI + n8n: Automating Business Workflows

Multi-Agent Systems: Collaboration & Specialization

Real-World Applications

Case Studies:

AI Customer Support Agents