Multi Cloud AI & Python

Learning Objectives:
By the end of the course, learners will be able to:

•  Understand and implement IaaS, PaaS, SaaS models in Azure and AWS.
•  Apply DevOps & DevSecOps practices with Jenkins, Azure DevOps, Harness, and SonarQube.
•  Master containerization and orchestration using Docker, Kubernetes, and Helm.
•  Automate infrastructure using Terraform and Ansible.
•  Integrate security scanning tools such as Checkov, Trivy, and Gitleaks in CI/CD pipelines.
•  Build and manage AI-driven operations (AIOps) for intelligent monitoring and alerting.
•  Gain hands-on experience through 21+ industrial-grade projects.

Recommended For:

• Developers and DevOps Engineers transitioning into Cloud Security roles.
• IT professionals aiming to specialize in Multi-Cloud Automation and DevSecOps.
• Students aspiring to gain real-world project exposure across Azure, AWS, and Kubernetes ecosystems.

Resources:
1. Spacious Classrooms:

• Modern, air-conditioned classrooms with comfortable seating for an optimal learning experience.
• Fully equipped with projectors and whiteboards to support interactive and engaging sessions.
• Provides an ideal environment for focused learning, teamwork, and group discussions.

2. Class Schedule:

• Regular Classes: 1 hour daily (Monday to Friday).
• Flexible Practice Slots: Available for all batches to enhance practical exposure.
• Real-Time Project Environment: Simulates industry-level work experience for better skill application.

3. Practice Labs:

• Spacious, dedicated lab designed for extended hands-on sessions.
• Open Access: 8:00 AM – 7:00 PM (Monday to Saturday).
• Mandatory Lab Practice: Every student must complete a minimum of 2 hours of lab practice daily.
• Continuous Mentor Support: Available during lab hours to provide personalized guidance with “Junior Trainers”
• Saturday Sessions: Include weekly exams or mock interviews to reinforce learning and assess progress.

Course Outline

Module 1: AI Agent – GitHub Co-pilot Workspace:

• Introduction to GitHub Co-pilot and setup.
• Integrating Co-pilot for AI-assisted coding in VS Code.
• Generating code, YAML, and scripts using Co-pilot.
• Leveraging Co-pilot for IaC and automation.

Module 2: AI Chatbox – Claude:

• Introduction to Claude AI chatbox.
• Working with Claude for conversational AI.
• Prompt engineering based on specific requirements.

Module 3: AI Deployment – Harness:

• Introduction to Harness CI/CD with AI.
• Building pipelines for intelligent deployments.
• Automated rollback and anomaly detection.
• Deploying applications using Harness.

Module 4: Azure AI Foundry:

• Introduction to Azure AI Foundry.
• Architecture of Azure AI Foundry.
• Building and deploying AI Agents in Azure AI Foundry.
• Integrating AI models into DevOps workflows.
• Working with Hubs, Projects, and AI Playgrounds.

Module 5: Kubectl AI:

• Introduction to Kubectl AI for Kubernetes.
• Using AI – powered natural language commands to manage Kubernetes clusters.
• Enhancing efficiency in Kubernetes operations.

Module 6: AIOps for Cloud & DevOps:

• Understanding AIOps and predictive analytics.
• Implementing AI-driven log analysis and alerting.
• Auto-healing using cloud-native AIOps.

Module 7: AI for IaC:

• Generating and validating Terraform/Ansible code with AI.
• Auto-documentation and linting.
• Policy compliance checks via AI tools.

Module 8: AI for Kubernetes Troubleshooting:

• Why K8s troubleshooting is hard (pods failing, networking issues, scaling problems).
• How AI tools help.
• Kubectl AI Plugins.
• K8sGPT – AI powered troubleshooting for Kubernetes clusters.
• Azure OpenAI + K8s logs for Root Cause Analysis (RCA).

Module 9: GitHub Co-pilot & AI Pair Programming:

• What is GitHub Copilot?
• How to set up Copilot for Powershell, Bash, Terraform, Kubernetes, and YAML files.
• Prompt engineering for DevOps: Writing better prompts for IaC & CI/CD.

Module 10: Azure Cloud Services:
1. Introduction to Azure Cloud Infrastructure:

• Overview of Cloud Technology
• Setting up a free – tier Azure account.
• Understanding subscriptions and tenants.
• Exploring IaaS, PaaS, and SaaS models.

2. Implementing and Managing Azure Networking:

• Overview of Azure Networking.
• Implementing and managing Azure virtual networks.
• Configuring virtual networks, subnets, and connectivity.
• Configuring Virtual Network Region and Global Peering.
• Understanding Azure to on-premises connectivity.
• Deploying Azure Virtual Network Gateway.
• Configuring User Defined Routes (UDR).
• Setting up Azure Virtual Network Gateway with AWS over IPSec VPN.
• Implementing Azure Service Endpoints.
• Understanding Hub and Spoke architecture.

3. Understanding and Configuring Network Security Groups (NSG):

• Overview of Azure NSGs.
• Creating and updating inbound/outbound security rules.
• Understanding NSG rule hierarchy and priority.
• Creating NSG rules with service tags.
• Understanding and creating Application Security Groups (ASG).

4. Implementing & Configuring Azure Virtual Machines:

• Overview of Azure virtual machines.
• Deploying virtual machines via Azure portal and CLI.
• Managing virtual machine storage.
• Understanding Availability Sets, Fault Domains, and Update Domains.
• Placing virtual machines in Availability Sets.

5. Designing & Implementing Azure Load Balancing:

• Overview of load balancing.
• Types of Azure load balancers (Basic vs. Standard).
• Configuring Azure Standard Load Balancer.
• Implementing Azure DNS.
• Buying and configuring a domain with GoDaddy.
• Creating DNS zones and records (A, CNAME).
• Load balancing across Availability Sets.

6. Configuring Azure Application Gateway:

• Understanding Azure Application Gateway architecture.
• Configuring path-based routing and SSL offloading.
• Setting up multiple VMs with Application Gateway.

7. Configuring Auto Scaling with Virtual Machine Scale Sets (VMSS):

• Understanding Azure VMSS
• Creating custom VM images for VMSS
• Deploying and stress-testing VMSS
• Observing auto-scaling behavior

8. Planning & Implementing Azure Storage:

• Overview of Azure Storage accounts.
• Understanding Blob Storage and File Shares.
• Configuring Azure FileSync.
• Data migration using Azure Storage Explorer.
• Managing storage permissions.
• Deploying static websites with custom domains

9. Backup & Disaster Recovery:

• Overview of backup and disaster recovery.
• Backing up VMware servers, Azure VMs, and Azure SQL.
• Configuring Azure replication and failover groups.
• Setting up Azure disaster recovery vault.
• Implementing a full BCDR strategy.

10. Planning & Implementing Azure SQL Database:

• Azure SQL Database (PaaS) vs. SQL Database (IaaS).
• Structured vs. unstructured data.
• Understanding DTUs in Azure SQL.
• Configuring global replication and failover groups.

11. Implementing Azure App Services:

• Overview of Azure Web Apps (PaaS).
• Deploying and managing web apps.
• Configuring Azure App Service plans and deployment slots.
• Scaling and ensuring resilience.

12. Configure Diagnostics, Monitoring, and Analytics:

• Setting up Azure monitoring and alerts.
• Using Log Analytics.
• Introduction to Azure Key Vault.
• Creating and managing vaults, secrets, and credentials.
• Integrating vaults with Azure Pipelines.
• Configure and manage VMs, storage, and networks.
• Integrate Key Vault, Log Analytics, and ELK Stack.
• Centralized logging and analytics.

Module 11: Infrastructure as Code (IaC) – Terraform + Checkov:

• Introduction to Terraform and infrastructure automation.
• Installing Terraform.
• Understanding providers, resources, and basic syntax.
• Writing your first Terraform script (main.tf).
• Exploring Terraform Plan, Show, Apply, and Destroy.
• Using Terraform Registry, console, and outputs

1. Terraform Variables & Modules:

• Breaking down main.tf into variables.tf and output.tf.
• Introduction to Terraform modules.
• Creating and using basic modules.
• Exploring module repositories.

2. Terraform with Azure – Lab Part 1:

• Setting up systems for Azure.
• Creating storage accounts and resource groups.
• Managing remote state and data sources.
• Working with state files and templates.

3. Terraform with Azure – Lab Part 2:

• Setting up virtual networks and subnets.
• Configuring NSGs on Azure.
• Checkov Integration:
• ➢ Introduction & Fundamentals.
• ➢ Installation & Basic Usage.
• ➢ Deep Dive into Policies & Rules.
• ➢ Use Cases & Hands-On Labs.

Module 12: DevOps – Azure DevOps + Gitleaks:
1. Introduction to DevOps:

• Understanding DevOps concepts and history.
• Exploring DevOps methodologies: Agile, Scrum, Waterfall.

2. Azure DevOps Introduction:

• Overview of Azure DevOps Services.
• Setting up a free-tier Azure DevOps account.
• Creating Azure Projects.
• Navigating the Azure DevOps Overview tab.
• Scenario – based interview questions and solutions.

3. Azure Work Item Management:

• Understanding Azure DevOps Boards.
• Creating and managing work items.
• Backing up and migrating work items.
• Customizing iteration paths and board views.

4. Repository Management:

• Introduction to repository management.
• Centralized vs. distributed version control.
• Basic and advanced Git commands (cherry-picking, rebase, stash).
• Git security with Talisman (pre-commit/pre-push hooks).
• Analyzing Talisman reports.

5. Azure Repos:

• Introduction to Azure Repos.
• Creating multi-branch repositories.
• Cloning, forking, and managing commit history.
• Advanced pull request concepts (merge, squash, rebase).
• Tag creation, security, and policies.

6. Azure Service Connections and Agent Pools:

• Understanding service principals and connections.
• Creating service connections.
• Hosted vs. self-hosted agent pools.
• Setting up self-hosted agent pools.

7. YAML and Azure Pipelines:

• YAML syntax and data types.
• Understanding continuous integration (CI).
• Creating build pipelines for ASP.NET, Java Spring Boot, and SQL DACPAC projects.
• Configuring build triggers, variables, and filters.
• Using deployment groups, environments, and task groups.

8. Release Pipelines:

• Understanding continuous deployment and delivery.
• Creating classic and YAML release pipelines.
• Deploying ASP.NET, Java, and SQL DACPAC applications.
• Deployment strategies.

9. Maven and Build Pipeline Security:

• Introduction to Maven for Java builds.
• Setting up SonarQube for static code analysis.
• Integrating SonarQube with Java pipelines.
• Creating custom publish gates and analyzing reports.

10. Azure Artifacts:

• Creating and managing private feeds.
• Packaging and pushing dependencies to feeds.

11. Azure Settings:

• Organization and project settings.
• Azure Active Directory integration.
• Managing permissions, users, groups, and retention policies.
• Gitleaks Integration:
• ➢ Introduction & Fundamentals.
• ➢ Installation & Basic Usage.
• ➢ Configuration & Custom Rules.
• ➢ Integrating into CI/CD & Developer Workflows.

Module 13: Docker + Trivy:
1. Docker Engine Installation:

• Manual and automated deployment on Ubuntu/CentOS.
• Understanding Docker Desktop vs. Server.
• Version checks and default locations.

2. Docker Architecture:

• Docker daemon, client, registry, and objects.
• Managing images and containers.
• Deploying sample applications (e.g., web servers).

3. Docker Networking:

• Understanding IP, subnets, CIDR, and network types (host, bridge, null, overlay).
• Overview of Docker Network Plugins.

4. Docker Storage:

• Ephemeral vs. persistent storage.
• Bind and volume mounts.
• Building and managing custom images with Dockerfiles.
• Storing images in Docker Hub.
• Trivy Integration:
• ➢ Introduction & Fundamentals.
• ➢ Installation & Basic Usage.
• ➢ Scanning Targets & Advanced Options.
• ➢ Integrating Trivy into CI/CD & DevSecOps Pipelines.

Module 14: Kubernetes + Security:

• Introduction to Kubernetes.
• Understanding Kubernetes architecture and namespaces.
• Installing and configuring Kubernetes.
• Managing ReplicaSets, Services, Load Balancers, and Ingress.
• Configuring volumes and namespaces.
• Exploring Azure Kubernetes Service (AKS).

Module 15: Ansible Automation:

• Installing and configuring Ansible.
• Managing inventory files and modules.
• Using Ansible Galaxy and Roles.
• Integrating Ansible with Azure DevOps pipelines.

Module 16: Containerization Security & Monitoring – ELK Stack:
1. Helm Charts:

• Introduction to Helm Charts.
• Installation and basic commands.

2. Monitoring (Prometheus and Grafana):

• Setting up monitoring stacks.
• Configuring Prometheus and Grafana.
• Analyzing and visualizing metrics.
• Monitoring & Observability with the ELK Stack:
• ➢ Introduction & Fundamentals.
• ➢ Setup & Installation.
• ➢ Monitoring & Alerting Use-Cases.
• ➢ Visualization & Dashboards.

Module 17: Amazon Web Services (AWS):
1. Networking in AWS:

• Introduction to AWS and networking fundamentals.
• VPC overview, components, and peering.
• Configuring VPN connections and Transit Gateway.
• Managing security groups, network ACLs, and load balancers.
• Setting up AWS Route 53 and DNS.
• Monitoring with CloudWatch and VPC Flow Logs

2. IAM (Identity Access Management)

• Introduction to IAM and its components.
• Creating users, groups, roles, and policies.
• Managing password policies and MFA.
• Implementing identity federation and cross-account access.
• Using AWS Organizations and Service Control Policies.

3. Compute:

• Introduction to EC2 instances.
• Creating launch templates and EC2 instances.
• Saving sessions with PuTTY.
• Creating images from EC2 instances.

4. Storage:

• Overview of AWS storage services (S3, EBS, Storage Gateway).
• Managing S3 buckets, EBS volumes, and snapshots.
• Configuring data lifecycle policies and S3 Glacier.

5. Databases:

• Introduction to AWS database services.
• Creating and managing RDS and Aurora instances.
• Configuring high availability, backups, and disaster recovery.
• Optimizing performance and costs.

6. Management and Governance:

• Overview of AWS Organizations, Control Tower, and Cost Explorer.
• Configuring AWS Budgets, Systems Manager, and Config Rules.

Module 18: Jenkins:

• Overview of SDLC and Jenkins.
• Understanding Jenkins Master-Slave architecture.
• Installing and configuring Jenkins.
• Managing plugins, freestyle, and pipeline jobs.
• Configuring slave nodes.

Module 19: Python for DevOps:
1. Python Introduction:

• Why Python for DevOps.
• Installing Python and setting up the environment.
• Writing and executing Python scripts.

2. Datatypes, Variables, and Best Practices in Python:

• Understanding Python datatypes (int, float, string, list, tuple, dict, set).
• Variable declaration and best practices.

3. Functions and Modules in Python:

• Defining and calling functions.
• Understanding function arguments (positional, keyword, default).
• Creating and importing modules.
• Using built-in and third-party Python modules.

4. Control Statements and Loops in Python:

• If-else conditions.
• For and while loops.
• Loop control statements (break, continue, pass).

5. File Handling in Python:

• Reading and writing files (open(), read(), write()).
• Working with JSON and CSV files.
• File handling best practices.

6. Python Socket Library:

• Understanding socket programming.
• Creating a simple client-server connection in Python.

7. Boto3 | AWS SDK for Python:

• Introduction to AWS SDK (boto3).
• Automating AWS services.

8. Docker SDK for Python:

• Introduction to the docker-py library.
• Automating Docker container management using Python.
• Running and managing containers programmatically.

9. Kubernetes with Python:

• Using Python Kubernetes-client SDK.
• Automating Kubernetes deployment using Python.
• Managing Kubernetes resources (pods, deployments, services).

Real-Time Industrial Projects (21+ Projects):
1. Azure Pipelines:

• End-to-end CI/CD pipelines for various applications.

2. AWS:

• Infrastructure end-to-end project with multiple mini-projects.

3. Jenkins:

• Java application CI/CD deployment.
• Infrastructure deployment using CI/CD pipelines.

4. Docker:

• Deploying multi-container applications.

5. Kubernetes:

• Deploying custom .NET applications on pods.

6. Terraform:

• Deploying Azure App Service with Terraform.

Course Duration:

• Estimated Duration: 5Months (depending on pace and prior experience).
• Weekly Commitment: Exam, Mock interviews, including lectures, labs, and projects.

Learning Methodology:

• Lectures: Interactive sessions covering theoretical concepts.
• Hands-On Labs: Practical exercises to reinforce learning.
• Real-Time Projects: Industry-relevant projects to build a portfolio.
• Assessments: Quizzes and scenario-based questions to evaluate progress.
• Community Support: Access to forums and instructor Q&A sessions.

Certification:
Upon completion, participants earn the MultiCloud-DevSecOps Mastery Certificate from V Cube Software
Solutions, validating expertise in Cloud, DevOps, Security Automation, and AI-driven tools.