DevOps with Multi-Cloud

Who Is This Course For? 

• Current DevOps Engineers: To transition from single-cloud to multi-cloud pipeline management.
• Cloud Engineers: To learn how to apply DevOps practices (like IaC and CI/CD) to the infrastructure they manage.
• Software Developers: To gain the skills needed to own the full deployment lifecycle of their applications.
• Solution Architects / Technical Leads: To understand the strategic and architectural implications of multi-cloud adoption.

Course content

MODULE -1

DevOps Culture, Principles, and Multi-Cloud Foundations

1.1 The DevOps Mindset: CAMS model (Culture, Automation, Measurement, Sharing), Lean principles, and the evolution to DevSecOps.

1.2 Multi-Cloud Strategy: Understanding use cases (e.g., regional compliance, best-of-breed services, avoiding vendor lock-in), risks, and governance models.

1.3 Cross-Cloud Networking: Review of VPC/VNet/VPC concepts and establishing secure, low-latency connectivity (VPN/Interconnect) between AWS, Azure, and GCP.

1.4 Identity Federation: Implementing centralized authentication via Azure AD or a third-party tool like Okta to manage roles across all three clouds.

Hands-On Lab: Setting up cloud access roles and federated authentication for a multi-cloud environment.

MODULE -2

Infrastructure as Code (IaC) with Terraform Fundamentals

2.1 Terraform Basics: HCL syntax, resource configuration, providers, and state management (local vs. remote state).

2.2 Building Multi-Cloud Templates: Writing generic Terraform code to deploy basic compute resources (EC2, Azure VM, GCP Compute Engine).

2.3 Remote State Management: Configuring and securing state files using cloud-native storage buckets (S3, Azure Blob Storage, GCS) with locking.

2.4 Data Sources and Output Variables: Using data sources to fetch existing cloud infrastructure information for reuse.

Hands-On Lab: Provisioning a basic three-tier architecture (Web, App, DB) across two clouds using a shared, remote Terraform state.

MODULE – 3

Advanced IaC, Modularization, and Policy as Code

3.1 Terraform Modules: Designing reusable, parameterized modules for networks, security groups, and common service patterns.

3.2 Terragrunt for DRY Code: Using Terragrunt to keep configurations DRY (Don’t Repeat Yourself) across multiple environments (Dev, QA, Prod).

3.3 Integrating Cloud-Native IaC: Introduction to AWS CloudFormation and Azure Bicep for complex native resource deployments.

3.4 Policy as Code (Sentinel/OPA): Implementing policy checks (e.g., “VM size must be ‘small'” or “Storage buckets must be encrypted”) before deployment using Terraform Cloud Sentinel or OPA.

Hands-On Lab: Creating a module registry and enforcing compliance policies on new infrastructure deployments.

MODULE – 4

Container Orchestration with Kubernetes (K8s)

4.1 Docker and Container Best Practices: Optimizing Dockerfile size and build speed with multi-stage builds.

4.2 Kubernetes Core: Deployments, Services, ConfigMaps, Secrets, and Ingress Controllers.

4.3 Multi-Cloud K8s Deployment: Provisioning and managing clusters using EKS (AWS), AKS (Azure), and GKE (GCP).

4.4 Helm and Kustomize: Packaging applications for repeatable deployment across different cloud K8s clusters.

Hands-On Lab: Deploying a multi-container application using Helm to one cluster on AWS and one on GCP.

MODULE – 5

Continuous Integration (CI) Automation

5.1 CI Tooling Deep Dive: Configuring jobs and workflows in GitHub Actions and a self-hosted runner (e.g., Jenkins or GitLab CI).

5.2 Automated Testing: Integrating unit, integration, and end-to-end (E2E) tests into the CI pipeline.

5.3 Security Scanning (SAST/DAST): Incorporating Static Application Security Testing (SAST) and Dynamic Application Security Testing (DAST) tools like SonarQube or OWASP ZAP.

5.4 Artifact Management: Using cloud-native registries (ECR, ACR, Artifact Registry) and third-party solutions (J-Frog Artifactory) for version control of binaries and containers.

Hands-On Lab: Creating a CI workflow that builds a Docker image, runs a security scan, and pushes the artifact to the respective cloud registry.

MODULE – 6

Continuous Delivery (CD) and GitOps

6.1 Advanced CD Concepts: Blue/Green, Canary, and Rolling deployment strategies.

6.2 GitOps Implementation: Deep dive into ArgoCD and FluxCD for declarative, automated deployments.

6.3 Traffic Shaping and Service Mesh: Using Istio/Linkerd to manage inter-service communication, implement circuit breakers, and perform advanced traffic splits (Canary).

6.4 Serverless CI/CD: Deploying Function-as-a-Service (Faas) applications using AWS Lambda, Azure Functions, and GCP Cloud Functions via specialized pipelines.

Hands-On Lab: Implementing a GitOps pipeline that performs a Canary deployment on Kubernetes and automatically rolls back if health checks fail.

MODULE – 7

Observability and Monitoring

7.1 Unified Logging: Implementing centralized logging with Fluentd/Loki/Elasticsearch to collect and aggregate logs from all three cloud providers.

7.2 Metrics Collection (Prometheus): Deploying Prometheus for time-series data collection and using Grafana for unified visualization.

7.3 Distributed Tracing: Integrating OpenTelemetry/Jaeger into applications to trace requests across services running in different cloud environments.

7.4 Advanced Alerting: Configuring complex alert rules (e.g., rate-of-change) in Prometheus and routing notifications via Alertmanager to incident management tools (PagerDuty, Opsgenie).

Hands-On Lab: Building a single Grafana dashboard that shows key metrics and logs from components hosted in AWS, Azure, and GCP.

MODULE  – 8

Security, Resilience, and FinOps (Capstone)

8.1 Secrets Management: Using HashiCorp Vault or integrating cloud-native services (Key Vault, Secret Manager, AWS Secrets Manager) securely into applications and CI/CD pipelines.

8.2 Disaster Recovery (DR) Planning: Defining RTO/RPO metrics and implementing cross-region/cross-cloud failover strategies (Active-Passive vs. Active-Active).

8.3 FinOps and Cost Management: Best practices for tagging, automating cost reporting, and using cloud-agnostic tools to enforce budget policies and optimize cloud spend.

8.4 Capstone Project: Students design and implement a complete multi-cloud solution, showcasing IaC, CI/CD, Observability, and DR capabilities.

Hands-On Lab: Auditing cloud spend, implementing automated cost-saving measures, and executing a mock disaster recovery failover.

What You’ll Get

• Daily classes for 1 to 1½ hours
• Doubt clarification session every day
• Hands-on labs & real-world projects
• Mock exams & interview preparation
• Certificate of Completion
• Lifetime access to course materials
• One-on-one mentoring & career support (optional)

Learning Outcomes 🧠

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

• Design and Implement CI/CD Pipelines: Architect, implement, and manage robust Continuous Integration/Continuous Delivery (CI/CD) pipelines using tools like Jenkins, GitLab CI, or native cloud services across different cloud platforms (AWS, Azure, GCP).
• Master Infrastructure as Code (IaC): Utilize tools such as Terraform or CloudFormation/ARM/Pulumi to provision and manage infrastructure consistently and repeatably across multi-cloud environments.
• Implement Containerization and Orchestration: Deploy, scale, and manage containerized applications using Docker and Kubernetes, including setting up multi-cloud Kubernetes clusters and service meshes.
• Monitor and Observe Multi-Cloud Systems: Implement comprehensive monitoring, logging, and tracing solutions using tools like Prometheus, Grafana, ELK stack, or cloud-native services to maintain application health and performance across disparate cloud providers.
• Apply Cloud Security and Compliance Best Practices: Integrate security practices (DevSecOps) into the CI/CD pipeline, manage identity and access across multiple clouds, and ensure compliance with relevant industry standards.

Career Roles 💼

• DevOps Engineer / SRE (Site Reliability Engineer): The core role, focusing on automating infrastructure, managing CI/CD pipelines, and ensuring the reliability, scalability, and performance of systems across various cloud providers.
• Multi-Cloud Architect: Specializes in designing strategic, resilient, and cost-effective application and infrastructure solutions that leverage the best services from two or more cloud vendors.
• Cloud Infrastructure Engineer: Responsible for building, deploying, and managing the foundational infrastructure (networking, compute, storage) using IaC tools across the specified multi-cloud platforms.
• Kubernetes/Container Specialist: A specialized role focusing on the deployment, maintenance, and optimization of container orchestration systems (like EKS, AKS, GKE) and related tools in a multi-cloud context.
• DevSecOps Engineer: Focuses on integrating security testing, vulnerability scanning, and compliance checks directly into the automated CI/CD and multi-cloud infrastructure provisioning processes.