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    Why enroll for Advanced DevOps Certification Training with GenAI?

    pay scale by Edureka courseThe global DevOps market, valued at USD 51.8 B in 2026, is projected to reach USD 93.13 B by 2035 at a CAGR of 5.6% - Business Research Insights
    IndustriesBy 2027, 80% of organizations will adopt DevOps platforms, marking a major and rapid 25% jump compared to 2023 - Gartner
    Average Salary growth by Edureka courseThe average annual salary for a DevOps Engineer in the United States is USD 129,417, with top earners up to USD 200,000 - Indeed

    DevOps Training with GenAI Benefits

    The DevOps market is growing rapidly, as organizations worldwide adopt DevOps practices driven by cloud-native technologies, containerization, and AI-powered automation. Our comprehensive program equips you with job-ready skills to stand out, as demand for skilled DevOps professionals is at an all-time high.
    Annual Salary
    DevOps Architect average salary
    Hiring Companies
     Hiring Companies
    Annual Salary
    Site Reliability Engineer average salary
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    Platform Engineer average salary
    Hiring Companies
     Hiring Companies
    Annual Salary
    DevOps Engineer average salary
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    Why Advanced DevOps Certification Training with GenAI from edureka

    Live Interactive Learning

    Live Interactive Learning

    • World-Class Instructors
    • Expert-Led Mentoring Sessions
    • Instant doubt clearing
    Lifetime Access

    Lifetime Access

    • Course Access Never Expires
    • Free Access to Future Updates
    • Unlimited Access to Course Content
    24x7 Support

    24x7 Support

    • One-On-One Learning Assistance
    • Help Desk Support
    • Resolve Doubts in Real-time
    Hands-On Project Based Learning

    Hands-On Project Based Learning

    • Industry-Relevant Projects
    • Course Demo Dataset & Files
    • Quizzes & Assignments
    Industry Recognised Certification

    Industry Recognised Certification

    • Edureka Training Certificate
    • Graded Performance Certificate
    • Certificate of Completion

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    About your Advanced DevOps Certification Training with GenAI

    DevOps Skills Covered

    • skillCI/CD Pipeline Design & Automation
    • skillContainer Orchestration
    • skillInfrastructure as Code (IaC)
    • skillObservability & Site Reliability Engineering
    • skillDevSecOps & Security Integration
    • skillAI-Powered DevOps

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    DevOps Course Curriculum

    Curriculum Designed by Experts

    AdobeIconDOWNLOAD CURRICULUM

    Module 1: DevOps Fundamentals, Culture, and AI Transformation

    9 Topics

    Topics

    • Introduction to DevOps: History, Evolution & Benefits
    • DevOps Culture, Practices & Core Principles
    • DLC vs DevOps Lifecycle
    • DevOps Toolchain Overview & Tool Selection
    • Agile, Lean & DevOps Integration
    • Key Metrics: DORA Metrics, Lead Time, MTTR, Change Failure Rate
    • DevOps Transformation Roadmap
    • Introduction to AI in DevOps: Overview & Use Cases
    • Essential Linux Commands for DevOps

    skillHands-on

    • Set up DevOps learning environment
    • Create DevOps maturity assessment for a sample organization
    • Design a DevOps transformation roadmap
    • Calculate and analyze DORA metrics from case studies
    • Practice essential Linux commands for daily DevOps tasks
    • Explore AI tools landscape for DevOps

    skillSkills

    • Understanding DevOps philosophy, principles, and lifecycle
    • Differentiating between traditional and DevOps approaches
    • Identifying key DevOps metrics and KPIs (DORA)
    • Recognizing AI's transformative role in DevOps
    • Mapping DevOps career paths

    Module 2: GitHub Copilot & AI-Assisted Development

    9 Topics

    Topics

    • Introduction to GitHub Copilot & AI Coding Assistants
    • Setting up Copilot in VS Code & JetBrains IDEs
    • Copilot for Shell Script & Bash Generation
    • AI-Assisted Python Scripting for Automation
    • Prompt Engineering Best Practices for DevOps
    • Copilot Chat for Code Explanation & Debugging
    • AI Code Review & Suggestions
    • Copilot for Documentation Generation
    • Ethical AI Usage & Best Practices

    skillHands-on

    • Install and configure GitHub Copilot in VS Code
    • Generate shell scripts for system automation using Copilot
    • Create Python automation scripts with AI assistance
    • Use Copilot Chat for code explanation and debugging
    • Practice prompt engineering for DevOps tasks
    • Generate documentation using Copilot
    • Compare AI-generated code with manual coding

    skillSkills

    • Setting up and configuring GitHub Copilot
    • Leveraging AI for code and script generation
    • Using Copilot for infrastructure code generation
    • Applying prompt engineering techniques for DevOps
    • Accelerating development with AI assistance throughout course

    Module 3: Version Control with Git & GitHub

    10 Topics

    Topics

    • Git Fundamentals: Architecture & Workflow
    • Git Installation & Configuration
    • Repository Operations: Clone, Commit, Push, Pull
    • Branching Strategies: GitFlow, Trunk-Based Development
    • Merging, Rebasing & Conflict Resolution
    • GitHub: Pull Requests, Code Reviews, Issues
    • Git Tags, Stash & Advanced Commands
    • Git Hooks & Pre-commit Automation
    • GitHub Actions Introduction
    • Using Copilot for Git Commands & Workflows

    skillHands-on

    • Initialize Git repository for a project
    • Create feature branches and merge workflows
    • Resolve merge conflicts in team scenarios
    • Set up GitHub repository with branch protection
    • Implement GitFlow workflow with Copilot assistance
    • Create and manage pull requests with code reviews
    • Configure Git hooks for code quality

    skillSkills

    • Implementing version control workflows
    • Managing branches and resolving conflicts
    • Collaborating using GitHub (with Copilot assistance)
    • Applying Git best practices in team environments
    • Implementing Git hooks and automation

    Module 4: CI/CD Fundamentals & Pipeline Design

    10 Topics

    Topics

    • Continuous Integration Principles & Benefits
    • Continuous Delivery vs Continuous Deployment
    • CI/CD Pipeline Architecture & Stages
    • Build Automation & Artifact Management
    • Automated Testing in CI/CD (Unit, Integration, E2E)
    • Code Quality Gates & Static Analysis
    • Deployment Strategies: Blue-Green, Canary, Rolling
    • Pipeline as Code Concepts
    • CI/CD Security Considerations
    • Metrics & KPIs for CI/CD

    skillHands-on

    • Design multi-stage CI/CD pipeline architecture
    • Create a simple CI pipeline with automated builds
    • Implement automated testing in pipeline
    • Set up artifact repository
    • Simulate blue-green deployment strategy
    • Build a deployment pipeline decision tree
    • Design pipeline for microservices application

    skillSkills

    • Designing CI/CD pipelines for various scenarios
    • Understanding pipeline stages and best practices
    • Implementing automated testing strategies
    • Applying CI/CD patterns and anti-patterns
    • Planning deployment strategies

    Module 5: Jenkins CI/CD Implementation

    10 Topics

    Topics

    • Jenkins Architecture & Installation
    • Jenkins UI & Job Configuration
    • Freestyle vs Pipeline Jobs
    • Declarative Pipeline Syntax
    • Jenkinsfile & Pipeline as Code
    • Jenkins Plugins: Git, Maven, Docker, SonarQube
    • Distributed Builds & Jenkins Agents
    • Jenkins Security & Access Control
    • Jenkins Shared Libraries
    • Jenkins Integration with Cloud Platforms

    skillHands-on

    • Install Jenkins on Linux server
    • Create freestyle job with Git integration
    • Build Java/Python application pipeline
    • Write Jenkinsfile for multi-stage pipeline using Copilot
    • Configure Jenkins agents for distributed builds
    • Implement parameterized builds
    • Set up Jenkins credentials and role-based access
    • Create shared library for reusable pipeline code

    skillSkills

    • Installing and configuring Jenkins
    • Creating declarative and scripted pipelines
    • Integrating Jenkins with Git, Docker, and build tools
    • Implementing advanced Jenkins features
    • Using Copilot for Jenkinsfile generation

    Module 6: GitHub Actions & Modern CI/CD

    10 Topics

    Topics

    • GitHub Actions Architecture & Concepts
    • Workflow Syntax & Triggers
    • Jobs, Steps & Actions
    • Secrets & Environment Variables
    • Matrix Builds & Strategy
    • Caching & Artifacts
    • Reusable Workflows & Composite Actions
    • Self-Hosted Runners
    • GitHub Actions Marketplace
    • Security Best Practices for Actions

    skillHands-on

    • Create first GitHub Actions workflow
    • Build multi-platform application with matrix builds
    • Implement caching for faster builds
    • Create reusable workflow for deployment
    • Set up self-hosted runner
    • Integrate Docker build and push
    • Implement security scanning with CodeQL
    • Compare workflow with equivalent Jenkins pipeline

    skillSkills

    • Building workflows using GitHub Actions
    • Implementing matrix builds and caching
    • Creating reusable workflows and actions
    • Integrating security scanning in workflows
    • Comparing GitHub Actions with Jenkins

    Module 7: Docker Fundamentals & Best Practices

    10 Topics

    Topics

    • Introduction to Containerization & Benefits
    • Docker Architecture: Images, Containers, Registry
    • Docker Installation & Configuration
    • Docker Images: Building, Tagging, Pushing
    • Dockerfile Best Practices & Multi-Stage Builds
    • Container Lifecycle Management
    • Docker Networking: Bridge, Host, Overlay
    • Docker Volumes & Data Persistence
    • Container Resource Management
    • Docker Logging & Debugging

    skillHands-on

    • Install Docker on Linux
    • Run your first container
    • Create custom Dockerfile for web application with Copilot
    • Build multi-stage Docker images
    • Push images to Docker Hub
    • Configure container networking
    • Implement volume mounting for data persistence
    • Containerize a 3-tier application
    • Debug container issues

    skillSkills

    • Understanding containerization concepts
    • Building and managing Docker images
    • Running and orchestrating containers
    • Implementing Docker networking and storage
    • Using Copilot for Dockerfile generation

    Module 8: Docker Advanced, Compose & Registry

    10 Topics

    Topics

    • Docker Image Optimization Techniques
    • Docker Compose: Architecture & Syntax
    • Multi-Container Application Management
    • Docker Compose for Development & Testing
    • Docker Security: Image Scanning, Secrets
    • Vulnerability Scanning with Trivy
    • Docker Registry: Harbor, ECR, ACR
    • Docker in CI/CD Integration
    • Docker Buildx & Multi-Platform Images
    • Container Runtime Security

    skillHands-on

    • Optimize Docker image size (reduce by 70%+)
    • Create Docker Compose file for microservices with Copilot
    • Deploy multi-tier application with Docker Compose
    • Configure custom networks and service discovery
    • Implement Docker secrets management
    • Scan images for vulnerabilities using Trivy
    • Build automated Docker image pipeline
    • Set up private Docker registry

    skillSkills

    • Optimizing Docker images for production
    • Orchestrating multi-container applications
    • Implementing Docker security best practices
    • Managing private Docker registries
    • Integrating Docker in CI/CD pipelines

    Module 9: Kubernetes Fundamentals

    10 Topics

    Topics

    • Kubernetes Architecture: Control Plane, Nodes
    • Kubernetes Objects: Pods, Services, Deployments
    • Kubernetes Installation: Minikube, kind, kubeadm
    • kubectl Commands & Operations
    • YAML Manifests for Kubernetes
    • ReplicaSets & Deployments
    • Services & Networking in Kubernetes
    • ConfigMaps & Secrets Management
    • Labels, Selectors & Annotations
    • Kubernetes Namespaces

    skillHands-on

    • Set up Minikube cluster locally
    • Deploy first pod using kubectl
    • Create deployment for web application with Copilot
    • Expose application using Services (ClusterIP, NodePort, LoadBalancer)
    • Scale deployments horizontally
    • Implement rolling updates and rollbacks
    • Configure ConfigMaps and Secrets
    • Deploy multi-tier application on Kubernetes

    skillSkills

    • Deploying and managing Kubernetes clusters
    • Understanding Kubernetes architecture
    • Deploying applications on Kubernetes
    • Implementing basic Kubernetes operations
    • Using Copilot for K8s YAML manifest generation

    Module 10: Kubernetes Advanced & Helm

    10 Topics

    Topics

    • StatefulSets & DaemonSets
    • Persistent Volumes & Persistent Volume Claims
    • Storage Classes & Dynamic Provisioning
    • Ingress Controllers & Ingress Rules (NGINX, Traefik)
    • Horizontal & Vertical Pod Autoscaling
    • Resource Quotas & Limits
    • Multi-Tenancy & Namespaces
    • Helm: Package Manager for Kubernetes
    • Helm Charts: Structure & Best Practices
    • Kubernetes RBAC & Security

    skillHands-on

    • Deploy stateful application using StatefulSets
    • Configure persistent storage for database
    • Set up NGINX Ingress Controller
    • Create Ingress rules for multiple services
    • Implement Horizontal Pod Autoscaler (HPA)
    • Set up resource quotas and limits
    • Package application using Helm charts with Copilot
    • Deploy microservices with Helm
    • Configure RBAC for cluster security

    skillSkills

    • Implementing advanced Kubernetes patterns
    • Configuring persistent storage solutions
    • Setting up ingress controllers
    • Packaging applications with Helm
    • Applying resource management and autoscaling

    Module 11: Terraform for Infrastructure Automation

    10 Topics

    Topics

    • Introduction to Infrastructure as Code
    • Terraform Architecture & Workflow
    • HCL (HashiCorp Configuration Language)
    • Terraform Providers (AWS, Azure, GCP)
    • Resources, Variables & Outputs
    • Terraform State Management
    • Remote State & Backend Configuration
    • Terraform Modules & Reusability
    • Terraform Workspaces for Environments
    • Terraform Cloud & Enterprise

    skillHands-on

    • Install and configure Terraform
    • Provision EC2 instances on AWS with Copilot assistance
    • Create VPC, subnets, and security groups
    • Build reusable Terraform modules
    • Implement remote state with S3 backend
    • Provision Azure resources using Terraform
    • Create multi-environment infrastructure with workspaces
    • Implement Terraform pipeline in CI/CD

    skillSkills

    • Provisioning infrastructure using code
    • Managing cloud resources declaratively
    • Implementing Terraform best practices
    • Version controlling infrastructure changes
    • Using Copilot for Terraform code generation

    Module 12: Ansible for Configuration Management

    12 Topics

    Topics

    • Introduction to Configuration Management
    • Ansible Architecture: Control Node, Managed Nodes
    • Ansible Installation & Configuration
    • Inventory Management (Static & Dynamic)
    • Ad-hoc Commands
    • Ansible Playbooks: YAML Syntax
    • Ansible Modules & Collections
    • Variables, Facts & Conditionals
    • Ansible Roles & Galaxy
    • Ansible Vault for Secrets
    • Ansible Tower/AWX

    skillHands-on

    • Install Ansible and configure inventory
    • Execute ad-hoc commands on multiple servers
    • Write playbook to install web server with Copilot
    • Deploy application using Ansible
    • Create reusable Ansible roles
    • Implement multi-tier application deployment
    • Use Ansible Vault for credentials
    • Integrate Ansible with Jenkins pipeline
    • Combine Terraform + Ansible workflow

    skillSkills

    • Automating configuration management
    • Writing Ansible playbooks
    • Managing multiple servers efficiently
    • Integrating Ansible with CI/CD pipelines
    • Combining Terraform and Ansible

    Module 13: AWS DevOps Services & Implementation

    11 Topics

    Topics

    • AWS Cloud Fundamentals for DevOps
    • AWS CodePipeline: Architecture & Setup
    • AWS CodeBuild: Build Automation
    • AWS CodeDeploy: Deployment Strategies
    • AWS CodeCommit & CodeArtifact
    • EC2, VPC, S3, RDS for DevOps
    • AWS ECS & EKS: Container Orchestration
    • AWS Lambda & Serverless DevOps
    • AWS CloudFormation for IaC
    • AWS CloudWatch: Monitoring & Logging
    • AWS Systems Manager & Parameter Store

    skillHands-on

    • Build end-to-end pipeline with AWS CodePipeline
    • Configure AWS CodeBuild for multi-language builds
    • Deploy application using AWS CodeDeploy
    • Provision AWS infrastructure with Terraform
    • Set up EKS cluster and deploy containerized apps
    • Implement blue-green deployment on AWS
    • Build serverless CI/CD pipeline with Lambda
    • Configure CloudWatch dashboards and alarms

    skillSkills

    • Deploying DevOps solutions on AWS
    • Utilizing AWS native DevOps services
    • Implementing CI/CD on AWS platform
    • Managing AWS infrastructure with DevOps tools

    Module 14: Azure DevOps & Cloud Integration

    11 Topics

    Topics

    • Introduction to Azure DevOps Services
    • Azure Pipelines Architecture (Classic vs YAML)
    • Multi-Stage Pipelines & Templates
    • Azure Repos, Boards & Test Plans
    • Azure Kubernetes Service (AKS) Deep Dive
    • Azure Container Instances (ACI)
    • Azure Functions & Serverless
    • Azure Resource Manager (ARM) Templates & Bicep
    • Azure Monitor & Application Insights
    • Azure Key Vault Integration
    • GitHub Copilot for Azure DevOps

    skillHands-on

    • Create Azure DevOps organization and project
    • Build YAML-based multi-stage pipeline
    • Deploy application to Azure App Service
    • Create and manage AKS cluster
    • Deploy ARM/Bicep templates for infrastructure
    • Configure Azure Monitor for comprehensive monitoring
    • Integrate Application Insights for APM
    • Set up Azure Key Vault for secrets management

    skillSkills

    • Building CI/CD pipelines in Azure DevOps
    • Implementing YAML pipelines
    • Deploying to Azure cloud services
    • Integrating Azure services with DevOps workflows

    Module 15: Monitoring, Logging & Observability

    11 Topics

    Topics

    • Monitoring vs Observability: Three Pillars (Metrics, Logs, Traces)
    • Prometheus: Architecture & Installation
    • Metrics Collection & PromQL
    • Grafana: Dashboards & Visualizations
    • ELK Stack: Elasticsearch, Logstash, Kibana
    • Loki for Log Aggregation
    • Application Performance Monitoring (APM)
    • Distributed Tracing with Jaeger/Zipkin
    • Alerting & Incident Management
    • SLIs, SLOs, SLAs & Error Budgets
    • OpenTelemetry Overview

    skillHands-on

    • Install Prometheus and exporters
    • Configure metrics collection for applications
    • Create Grafana dashboards for system metrics
    • Set up ELK/Loki for centralized logging
    • Configure log shipping from applications
    • Create log parsing and analysis queries
    • Implement alerting rules in Prometheus
    • Set up distributed tracing for microservices
    • Define SLOs and create error budget dashboards

    skillSkills

    • Implementing comprehensive monitoring solutions
    • Setting up centralized logging
    • Creating dashboards and alerts
    • Applying observability best practices
    • Understanding the three pillars of observability

    Module 16: DevSecOps & Security Automation

    11 Topics

    Topics

    • Introduction to DevSecOps & Shift-Left Security
    • Static Application Security Testing (SAST)
    • Dynamic Application Security Testing (DAST)
    • Software Composition Analysis (SCA)
    • Container Security Scanning (Trivy, Clair)
    • Infrastructure Security: CIS Benchmarks
    • Secrets Management: HashiCorp Vault, Azure Key Vault
    • Policy as Code: OPA, Kyverno
    • Security in CI/CD Pipelines
    • Compliance as Code
    • AI-Powered Security Analysis

    skillHands-on

    • Integrate SonarQube for code quality & security
    • Implement SAST scanning in pipeline
    • Scan Docker images for vulnerabilities
    • Configure Trivy/Snyk for container scanning
    • Set up HashiCorp Vault for secrets
    • Implement policy as code with OPA/Kyverno
    • Scan infrastructure code with Checkov/tfsec
    • Create security-hardened CI/CD pipeline
    • Implement automated compliance checks

    skillSkills

    • Integrating security into DevOps pipelines
    • Implementing security scanning tools
    • Applying shift-left security practices
    • Managing secrets and credentials securely
    • Automating compliance checks

    Module 17: GitOps & Progressive Delivery

    11 Topics

    Topics

    • Introduction to GitOps Principles
    • GitOps vs Traditional DevOps
    • ArgoCD: Architecture & Installation
    • Flux CD: Setup & Configuration
    • Declarative Infrastructure with GitOps
    • Application Sets & Multi-Cluster Management
    • Progressive Delivery: Canary, Blue-Green
    • Argo Rollouts for Advanced Deployments
    • Feature Flags & A/B Testing
    • Rollback Strategies & Self-Healing
    • GitOps Best Practices & Security

    skillHands-on

    • Install and configure ArgoCD
    • Deploy application using GitOps workflow
    • Set up automated sync from Git to Kubernetes
    • Implement canary deployment with Argo Rollouts
    • Create blue-green deployment strategy
    • Configure progressive delivery pipelines
    • Implement feature flags with Flagsmith
    • Manage multi-environment deployments with GitOps
    • Build self-healing infrastructure

    skillSkills

    • Implementing GitOps workflows
    • Using ArgoCD for continuous delivery
    • Applying progressive delivery techniques
    • Automating Kubernetes deployments
    • Implementing self-healing infrastructure

    Module 18: AIOps: Intelligent IT Operations

    11 Topics

    Topics

    • Introduction to AIOps: Concepts & Benefits
    • AIOps Platforms Overview (Dynatrace, Datadog, Splunk)
    • Machine Learning for IT Operations
    • Anomaly Detection in Monitoring
    • Predictive Analytics for System Failures
    • AI-Powered Log Analysis & Pattern Recognition
    • Intelligent Alerting & Noise Reduction
    • Root Cause Analysis with AI
    • Automated Incident Triage & Response
    • Capacity Planning with ML
    • AIOps Integration with Existing Tools

    skillHands-on

    • Implement anomaly detection with Prometheus & ML
    • Build AI-powered log analysis system
    • Create intelligent alerting with reduced false positives
    • Implement predictive failure analysis
    • Set up automated root cause analysis
    • Build ML model for capacity prediction
    • Automate incident triage with AI
    • Create intelligent dashboard with ML insights
    • Integrate AIOps with existing monitoring stack

    skillSkills

    • Applying AI/ML in IT operations
    • Implementing predictive analytics for failures
    • Automating incident detection and response
    • Reducing alert noise with AI
    • Building intelligent monitoring systems

    Module 19: AI-Powered Software Engineering

    11 Topics

    Topics

    • AI in Software Engineering: Overview & Trends
    • AI Coding Assistants: Copilot, CodeWhisperer, Tabnine
    • AI-Powered Code Review & Analysis
    • Automated Test Generation with AI
    • AI for Code Refactoring & Optimization
    • Natural Language to Code Conversion
    • AI-Powered Documentation Generation
    • Code Security Analysis with AI
    • AI for Bug Detection & Resolution
    • ChatOps & Conversational AI for DevOps
    • Building AI-Enhanced CI/CD Pipelines

    skillHands-on

    • Compare different AI coding assistants
    • Implement AI-powered code review in pipeline
    • Use AI for test case generation
    • Generate unit tests automatically with AI
    • Build AI-powered documentation workflow
    • Create ChatOps bot with Slack/Teams integration
    • Implement AI-based code quality gates
    • Build natural language to infrastructure workflow
    • Create AI-enhanced debugging system

    skillSkills

    • Leveraging AI for software development lifecycle
    • Implementing AI-assisted code review
    • Using AI for automated testing
    • Applying AI for code quality and documentation
    • Building AI-enhanced development workflows

    Module 20: GenAI for DevOps and Platform Engineering

    9 Topics

    Topics

    • Generative AI in DevOps: Advanced Use Cases
    • LLMs for Infrastructure Code Generation
    • AI Agents for DevOps Automation
    • Custom GPT/Claude for DevOps Tasks
    • Platform Engineering & Internal Developer Platforms (IDP)
    • Self-Service Infrastructure Portals (Backstage)
    • FinOps: AI-Driven Cost Optimization
    • Emerging Trends: WebAssembly, eBPF, Service Mesh
    • Building AI-Native DevOps Culture

    skillHands-on

    • Build custom AI assistant for DevOps tasks
    • Generate infrastructure code using LLMs
    • Create AI agent for pipeline optimization
    • Design Internal Developer Platform architecture
    • Implement self-service portal with Backstage
    • Build cost optimization dashboard with AI

    skillSkills

    • Leveraging Generative AI for DevOps automation
    • Designing internal developer platforms
    • Implementing FinOps practices
    • Building end-to-end DevOps pipeline

    Module 21: Advanced Kubernetes Operations & Service Mesh (Self-Paced)

    12 Topics

    Topics

    • Kubernetes Operators: Concepts & Use Cases
    • Custom Resource Definitions (CRDs)
    • Building Custom Operators with Operator SDK
    • Service Mesh Introduction: Why Service Mesh?
    • Istio Architecture: Control Plane & Data Plane
    • Istio Installation & Configuration
    • Traffic Management: Virtual Services, Destination Rules
    • mTLS & Security Policies
    • Observability with Istio: Kiali, Jaeger Integration
    • Linkerd Overview & Comparison
    • Multi-Cluster Service Mesh
    • Service Mesh Best Practices

    skillHands-on

    • Create Custom Resource Definition (CRD)
    • Build simple Kubernetes Operator
    • Install Istio on Kubernetes cluster
    • Configure traffic splitting (Canary with Istio)
    • Implement circuit breaker pattern
    • Enable mTLS between services
    • Set up Kiali dashboard for mesh visualization
    • Implement rate limiting with Istio
    • Configure fault injection for testing
    • Deploy application across multiple clusters

    skillSkills

    • Implementing Kubernetes Operators and Custom Resources
    • Configuring service mesh with Istio/Linkerd
    • Implementing advanced traffic management
    • Applying mTLS and zero-trust security
    • Managing multi-cluster Kubernetes deployments

    Module 22: Chaos Engineering & Site Reliability Engineering (SRE) (Self-Paced)

    14 Topics

    Topics

    • Introduction to Chaos Engineering
    • Chaos Engineering Principles & Practices
    • Chaos Monkey & Netflix Simian Army
    • Chaos Toolkit & LitmusChaos
    • Gremlin for Enterprise Chaos
    • Designing Chaos Experiments
    • Site Reliability Engineering (SRE) Fundamentals
    • SRE vs DevOps: Complementary Practices
    • Service Level Indicators (SLIs)
    • Service Level Objectives (SLOs)
    • Error Budgets & Budget Policies
    • Incident Management & Postmortems
    • Toil Reduction Strategies
    • On-Call Best Practices

    skillHands-on

    • Install LitmusChaos on Kubernetes
    • Design and run pod failure experiment
    • Implement network chaos scenarios
    • Create CPU/Memory stress tests
    • Define SLIs for sample application
    • Calculate and implement SLOs
    • Set up error budget tracking dashboard
    • Conduct chaos experiment on microservices
    • Write postmortem document for incident
    • Implement automated rollback on chaos detection

    skillSkills

    • Applying chaos engineering principles
    • Implementing reliability testing in production
    • Designing and implementing SRE practices
    • Creating error budgets and SLOs
    • Building resilient systems through controlled failure

    Module 23: Advanced Terraform & Multi-Cloud IaC (Self-Paced)

    14 Topics

    Topics

    • Advanced Terraform Patterns & Anti-Patterns
    • Terraform Functions & Expressions
    • Dynamic Blocks & For Each
    • Terragrunt: DRY Infrastructure Code
    • Terragrunt Configuration & Best Practices
    • Multi-Cloud Infrastructure Management
    • Terraform Cloud & Enterprise Features
    • Sentinel Policy as Code
    • Writing Sentinel Policies
    • Infrastructure Testing with Terratest
    • Terraform Import & State Surgery
    • Terraform CDK (CDKTF) Introduction
    • Pulumi Overview & Comparison
    • Cost Estimation with Infracost

    skillHands-on

    • Implement complex Terraform with dynamic blocks
    • Set up Terragrunt for multi-environment
    • Create reusable Terragrunt modules
    • Deploy infrastructure to AWS and Azure simultaneously
    • Write Sentinel policies for compliance
    • Implement Terratest for module testing
    • Import existing infrastructure to Terraform
    • Perform state migration between backends
    • Use Infracost for cost estimation
    • Create CDKTF infrastructure in Python

    skillSkills

    • Implementing advanced Terraform patterns
    • Using Terragrunt for DRY infrastructure
    • Managing multi-cloud infrastructure
    • Implementing policy as code with Sentinel
    • Automating infrastructure testing

    Module 24: Cloud Cost Optimization & FinOps (Self-Paced)

    15 Topics

    Topics

    • Introduction to FinOps: Framework & Principles
    • FinOps Lifecycle: Inform, Optimize, Operate
    • Cloud Cost Fundamentals: Pricing Models
    • Reserved Instances & Savings Plans
    • Spot/Preemptible Instances Strategies
    • AWS Cost Explorer & Cost Anomaly Detection
    • Azure Cost Management & Budgets
    • Kubecost for Kubernetes Cost Management
    • Right-sizing Resources
    • Idle Resource Detection & Cleanup
    • Tagging Strategies for Cost Allocation
    • Showback & Chargeback Models
    • AI-Powered Cost Optimization
    • Cost Governance & Policies
    • Building FinOps Culture

    skillHands-on

    • Analyze cloud costs using AWS Cost Explorer
    • Set up Azure budgets and alerts
    • Implement tagging strategy for cost allocation
    • Install and configure Kubecost
    • Identify and terminate idle resources
    • Calculate potential savings from Reserved Instances
    • Implement Spot instances for non-critical workloads
    • Create cost optimization recommendations report
    • Build cost dashboard with Grafana
    • Implement automated cost alerts and actions

    skillSkills

    • Implementing FinOps practices and principles
    • Optimizing cloud costs across AWS and Azure
    • Using AI for cost prediction and optimization
    • Implementing cost governance and allocation
    • Designing cost-aware architectures

    DevOps Training Course with Gen AI Description

    What will I learn in the Advanced DevOps Certification Training with GenAI?

    This industry-leading program covers the complete DevOps lifecycle integrated with Generative AI capabilities. You'll master essential DevOps tools including Docker, Kubernetes, Jenkins, Terraform, Ansible, and cloud platforms like AWS, Azure, and GCP. What sets this course apart is the GenAI integration. You'll learn to leverage AI-powered tools for intelligent automation, code generation, predictive monitoring, and self-healing infrastructure. By completion, you'll have hands-on experience with 30+ industry tools, GenAI-assisted DevOps workflows, and 10 real-world projects.

      What is DevOps?

      DevOps is a cultural philosophy and a set of practices supported by tools that bring together software development (Dev) and IT operations (Ops). Its goal is to automate and accelerate the software delivery lifecycle by improving collaboration, communication, and continuous integration, resulting in faster, more reliable releases.
      By breaking down traditional silos between teams, DevOps enables developers and operations teams to work together across the entire lifecycle; from planning and development to deployment and monitoring to ensure that high-quality software can be delivered quickly and consistently to meet customer needs.

        How is Generative AI integrated into this DevOps training program?

        GenAI is woven throughout the curriculum, not treated as an afterthought. You'll learn to use AI coding assistants like GitHub Copilot for writing Infrastructure as Code and automation scripts. The course covers AI-powered monitoring and AIOps platforms for intelligent alerting and root cause analysis. You'll explore ChatOps integration, natural language infrastructure queries, and GenAI tools for documentation generation, incident summarization, and automated runbook creation. This prepares you for the future of DevOps where AI augments every stage of the software delivery lifecycle.

          Is this Advanced DevOps course suitable for beginners with no prior experience?

          This course is designed with a progressive learning path that welcomes motivated beginners while also challenging experienced professionals. We start with DevOps fundamentals and Linux basics before advancing to complex topics and GenAI integration. If you have basic programming knowledge and understand how software applications work, you're ready to begin. Our hands-on labs break down complex concepts into practical exercises, and no prior DevOps or AI experience is require

            Is it worth learning DevOps with GenAI?

            Yes, learning DevOps with GenAI is absolutely worth it. As a rapidly growing field with significant potential to revolutionize how organizations build, deploy, and manage software, it is regarded as one of the most valuable skill combinations for the future of work. GenAI is transforming DevOps by automating complex tasks, enabling intelligent decision-making, and facilitating seamless human-AI collaboration across CI/CD pipelines, infrastructure management, and incident response. Professionals with both DevOps and GenAI skills are commanding premium salaries across industries.

              What are the prerequisites for this Advanced DevOps Certification Training with GenAI?

              In order to complete this course successfully, participants need to have a basic understanding of programming concepts (preferably Python or Shell scripting), Linux fundamentals, and general IT operations. Familiarity with cloud computing basics is helpful but not mandatory. However, learners will be provided with self-learning refresher material on Linux, Git, and foundational DevOps concepts before beginning the live classes. No prior experience with Generative AI is required as GenAI fundamentals are covered within the course.

                Why should professionals become DevOps Engineers with GenAI skills?

                Upon completing the Advanced DevOps Certification Training with GenAI, participants will learn to design and build automated CI/CD pipelines using tools like Jenkins, GitHub Actions, and ArgoCD. They will implement containerization with Docker, orchestration with Kubernetes, and Infrastructure as Code using Terraform and Ansible.
                The course covers GenAI integration with tools like GitHub Copilot and Amazon CodeWhisperer for intelligent code generation, AIOps platforms for predictive monitoring, and ChatOps for natural language automation. Participants will also learn cloud deployment on AWS, Azure, and GCP, along with observability using Prometheus, Grafana, and ELK Stack. Hands-on projects ensure practical expertise in building scalable, real-world DevOps solutions powered by AI.

                  Who should take this Advanced DevOps Certification Training with GenAI?

                  The Advanced DevOps Certification Training with GenAI is ideal for IT enthusiasts, developers, and professionals looking to build automated, intelligent software delivery pipelines. It is best suited for:
                  • Software Developers wanting to expand into DevOps
                  • System Administrators transitioning to cloud and automation roles
                  • IT Operations professionals seeking modern DevOps practices
                  • DevOps Engineers looking to upgrade their skills with GenAI
                  • Cloud Engineers wanting to integrate AI into infrastructure management
                  • Freshers who want to leverage DevOps and GenAI for career growth

                    Is GenAI-powered DevOps the future?

                    Yes, GenAI-powered DevOps is shaping the future of software delivery by enabling intelligent, automated systems that can reason, predict, and act independently. Unlike traditional DevOps, which relies heavily on manual scripting and rule-based automation, GenAI-powered DevOps dynamically adapts, learns from patterns, and interacts with infrastructure intelligently.

                      As industries move toward faster releases, zero-downtime deployments, and self-healing infrastructure, GenAI will play a crucial role in revolutionizing CI/CD pipelines, incident management, security automation, and infrastructure optimization.

                        How will I execute the practicals in this Advanced DevOps Certification Training with GenAI?

                        A step-by-step guide for setting up environments, configuring DevOps tools, and integrating GenAI assistants will be provided in the Learning Management System (LMS). Participants will have access to cloud-based lab environments for practicing Docker, Kubernetes, Terraform, CI/CD pipelines, and GenAI tools without complex local setups. Edureka's Support Team will be available 24/7 to assist learners in case they have any questions or face any technical issues during the practicals.

                          What are the system requirements for this Advanced DevOps Certification Training with GenAI?

                          The system requirements for this Advanced DevOps Certification Training with GenAI include:

                            Hardware Requirements:
                            • CPU: Multi-core processor (minimum 2 cores, 4 or more recommended)
                            • Memory (RAM): At least 8 GB (16 GB recommended for running Docker and Kubernetes locally)
                            • Storage: Minimum 50 GB of free disk space for container images and tools
                            • GPU: Not required for this course

                            Software Requirements:
                            • Operating System: Windows 10/11, macOS, or Linux (Ubuntu 20.04+ recommended for DevOps development)
                            • Programming Language: Basic proficiency in Python or Shell scripting
                            • Development Tools: VS Code, Terminal/Command Line
                            • Virtualization: Docker Desktop (installation guided in course)
                            • Browser: Chrome or Firefox for accessing cloud consoles and GenAI tools
                            • Package Management: Familiarity with pip, npm, or apt is helpful

                            DevOps Training Projects

                             certification projects

                            Build an AI-Powered CI/CD Pipeline Generator

                            Develop an intelligent CI/CD pipeline generator using GitHub Copilot and LLMs that automatically creates optimized Jenkins and GitHub Actions pipelines based on project requireme....
                             certification projects

                            Create an AIOps-Powered Incident Response System

                            Build an intelligent incident management system that uses machine learning to detect anomalies in production environments, predict system failures, and automatically trigger reme....
                             certification projects

                            Design a GitOps-Based Multi-Cloud Deployment Platform

                            Develop a comprehensive GitOps platform using ArgoCD and Flux CD that enables declarative, automated deployments across AWS, Azure, and GCP. Implement progressive delivery strate....
                             certification projects

                            Build a Kubernetes Resource Optimization Agent with AI

                            Create an AI-powered agent using Python and Kubernetes APIs that continuously monitors cluster resource utilization, identifies over-provisioned and under-utilized resources, and....
                             certification projects

                            Develop an Intelligent Security Scanning Pipeline

                            Build a comprehensive DevSecOps pipeline that integrates multiple security scanning tools (SonarQube, Trivy, Snyk, Checkov) with AI-powered vulnerability prioritization. The syst....
                             certification projects

                            Create a Self-Service Infrastructure Portal with Backstage

                            Design and implement an Internal Developer Platform (IDP) using Backstage that provides self-service infrastructure provisioning, template-based application scaffolding, and AI-a....
                             certification projects

                            Build an AI-Powered Log Analysis and Troubleshooting System

                            Develop an intelligent log analysis platform using ELK Stack and machine learning that automatically identifies patterns in application and infrastructure logs, correlates events....
                             certification projects

                            Design a Container Image Security and Compliance Scanner

                            Create an automated container security solution that scans Docker images for vulnerabilities, malware, and compliance violations before deployment. Use AI to assess risk scores, ....
                             certification projects

                            Develop a Multi-Region Disaster Recovery Automation System

                            Build an automated disaster recovery (DR) system for Kubernetes applications that uses Terraform and ArgoCD to maintain synchronized infrastructure across multiple regions. Imple....
                             certification projects

                            Create an Infrastructure-as-Code Testing and Validation Framework

                            Develop a comprehensive testing framework for Terraform and Ansible code using Terratest, Molecule, and AI-powered test generation. The system automatically generates test scenar....

                            DevOps Certification

                            Edureka provides the Advanced DevOps GenAI certification upon successful course completion. The certification is valid for lifetime with no renewal required.

                            Complete all 20 live modules, pass quizzes, finish hands-on DevOps assignments and complete the capstone project with CI/CD pipeline, GitOps deployment, and AI integration.

                            This certification validates expertise in CI/CD automation, Kubernetes orchestration, infrastructure as code (Terraform/Ansible), cloud platforms (AWS/Azure), GitOps, AIOps, and AI-powered DevOps workflows. It opens opportunities in DevOps Engineering, SRE, Platform Engineering, and Cloud Architecture roles across finance, healthcare, retail, and technology industries.

                            You can apply for multiple job roles which includes: DevOps Engineer, Site Reliability Engineer (SRE), Platform Engineer, Cloud DevOps Engineer, Kubernetes Administrator, Infrastructure Automation Engineer, DevSecOps Engineer, AIOps Engineer, CI/CD Engineer, Cloud Solutions Architect, and more.

                            The certification requires understanding CI/CD, containerization, Kubernetes, infrastructure as code, and cloud platforms. With structured learning across 20 modules, 80+ hours of hands-on practice with Docker, Jenkins, Terraform, and GitHub Copilot, plus expert guidance, it's achievable for dedicated learners.

                            Yes, you receive lifetime access to all course materials including 20 live module recordings, 5 self-paced modules, hands-on labs, project templates, and regular updates on DevOps tools and AI automation trends.

                            Edureka Certification
                            John Doe
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                            with Grade X
                            XYZ123431st Jul 2024
                            The Certificate ID can be verified at www.edureka.co/verify to check the authenticity of this certificate
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                            Vijay KalkundriPrincipal Engineer at Reflektion, former Senior Test Engineer at Nokia

                            I had a great experience in taking the Hadoop course from Edureka. It is the only course in the market which facilitates the people from the Non development background to plug themselves into the Hadoop ecosystem. Edureka has provided a unique opportunity for the students around the world to connect to some of the best tutors. The tutors not only provide a very good theoretical explanation , but also help us to co-relate it with some real time examples. This gives a edge to the students and the working professional who attend the course.The best advantage of the Edureka course is the fact that we can attend the course from the comfort of our home as well as download the courses and listen to it over again and again. I am sure that Edureka will be playing a key role in filling the Gap of the Professionals which the Cloud ecosystem is currently facing. Cheers,Vijay Kalkundri - Good Session and one of the best instructor to have interfaced with at online.

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                            Awesome faculty. Awesome explanation on topics. I really appreciate Edureka Support team. They are really doing a fantastic job. All my queries were answered in no time. I also approached your support team for a change in class and the instructor. They allowed me to choose instructor of my choice and now my learning is much at its peak. Thanks to one and all sitting out there in the support team. They even provide a prompt response during weekends. That's a good feature. We professionals get time only during the weekend to focus on studies and when we do so we get stuck into problems; but no way have we had a good Edureka support Team. Thanks once again.

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                            I have been using Edureka for learning different topics related to Big Data -Hadoop, PIG, HIVE, Cassandra. I am very happy with the training and the help they are providing and I feel better than another online training where I registered for Cassandra. One of great thing is we can download the videos and references for later use, I use these in my commute to work (usually spend 2.5 hrs in train). Thank you for being flexible and proving great opportunity to learn cutting edge technologies - Cheers

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                            edureka! is efficiently able to provide effective e-learning for Big Data. All the required material for learning is kept online in the Learning Management System (LMS) along with the recordings of class so that we can refer back any part of the class. Also, edureka! 24x7 support is very helping and prompt in its service. Thanks edureka! for providing great and effective way of learning.

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                            The courses are top rate. The best part is live instruction, with playback. You get all the presentations and labs. Great instructions. But my favorite feature is viewing a previous class. They provide a set of videos from a previous session, so you can watch the course before you participate. This way you can get the most out of the course. Also, they are always there to answer questions, and prompt when you open an issue if you are having any trouble. Added bonus ~ you get lifetime access to the course you took!!! I have taken so many courses and then not really gotten to work with a technology until I forgot most of what was taught. Edureka lets you go back later, when your boss says I want this ASAP!" ~ This is the killer education app... I've take two courses and I'm taking two more. Love these guys."

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                            I have taken Informatica, Hadoop, R-programming, Spark and Scala and several other training's from past 3 years. There is no way to say that these courses are bad.. this is the exceptional institute with so many senior people who spend lot of their efforts for a cause. Because i know the pain as a trainer as well. Hats off to to team and the person who started edureka. I'm posting my personal experience and i do lot of social service. Good luck to others.

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                            DevOps Training FAQs

                            What are the key features of Advanced DevOps Certification Training with GenAI training?

                            AI-First approach with GitHub Copilot from Module 2, coverage of 35+ tools (Jenkins, Kubernetes, Docker, Terraform, ArgoCD, AWS, Azure), dedicated AIOps and AI Software Engineering modules, platform engineering with Backstage, GitOps workflows, 10+ industry projects, and comprehensive capstone with microservices deployment.

                            Why should I enroll in Advanced DevOps Certification Training with GenAI training?

                            Master AI-powered DevOps automation with GitHub Copilot, Kubernetes, Terraform, ArgoCD, and AIOps platforms. Get hands-on experience with 20 comprehensive modules, 10+ industry projects, expert-led instruction, and lifetime access. Opens doors to high-demand DevOps Engineer, SRE, and Platform Engineer roles with competitive salaries across technology, finance, healthcare, and retail industries.

                            What are the objectives of Advanced DevOps Certification Training with GenAI certification course?

                            Learn to design and deploy production-ready DevOps pipelines with AI automation using Jenkins, GitHub Actions, Docker, Kubernetes, Terraform, Ansible, and ArgoCD. Gain expertise in CI/CD, container orchestration, infrastructure as code, AWS/Azure cloud platforms, observability with Prometheus/Grafana, DevSecOps, GitOps, AIOps, and platform engineering with real-world projects and cost optimization (FinOps).

                            What is the role of a DevOps Engineer with AI expertise?

                            Design automated CI/CD pipelines, manage Kubernetes clusters, provision infrastructure with Terraform, use GitHub Copilot for code generation, implement AIOps for predictive monitoring, build self-service developer platforms, ensure DevSecOps practices, deploy with GitOps methodologies, and optimize cloud costs using AI-driven recommendations on AWS and Azure.

                            What if I miss a live Advanced DevOps Certification Training with GenAI class?

                            Access recorded sessions of all 20 live modules anytime. All hands-on Docker, Kubernetes, Jenkins, Terraform labs and demonstrations are available for review at your convenience.

                            What support is available after completing DevOps GenAI training?

                            Contact Edureka's support team for queries and access active community forums for DevOps best practices, networking, and ongoing help. Receive regular updates on new DevOps tools, Kubernetes features, and AI automation trends.

                            What skills will I acquire in Advanced DevOps Certification Training with GenAI training?

                            Master CI/CD with Jenkins and GitHub Actions, Docker containerization, Kubernetes orchestration, Terraform and Ansible for infrastructure as code, AWS and Azure cloud platforms, GitOps with ArgoCD, monitoring with Prometheus and Grafana, DevSecOps, GitHub Copilot for AI-assisted coding, AIOps for intelligent operations, and platform engineering.

                            How does DevOps GenAI certification help career advancement?

                            DevOps GenAI certification provides specialized skills in CI/CD automation, Kubernetes, cloud platforms, and AI-powered DevOps. Opens doors to DevOps Engineer, SRE, and Platform Engineer roles with 20-40% salary increases. Demonstrates expertise in Jenkins, Terraform, ArgoCD, AIOps, and GitHub Copilot for faster career progression to senior and leadership positions.

                            What tools and technologies are covered in DevOps GenAI certification?

                            Python, Bash scripting, YAML, Jenkins, GitHub Actions, Docker, Kubernetes, Helm, Terraform, Ansible, ArgoCD, Flux CD, Prometheus, Grafana, ELK Stack, AWS (EKS, CodePipeline), Azure (AKS, DevOps), GitHub Copilot, SonarQube, Trivy, HashiCorp Vault, and AIOps platforms.

                            Can beginners with minimal DevOps experience take this course?

                            Yes, if you have basic software development, Linux, and programming fundamentals (Python/scripting). The course starts with DevOps fundamentals and progresses systematically through Docker, Kubernetes, CI/CD, and cloud platforms, making it accessible for those transitioning from development, system administration, or IT operations roles.

                            Is DevOps Engineering a good career choice in 2026?

                            Yes, DevOps Engineering is highly promising with exponential demand across all industries. DevOps Engineers with AI automation skills command salaries of $100K-$180K+ in the US. The role offers clear progression to Senior DevOps Engineer, SRE, Platform Engineer, DevOps Architect, and leadership positions with excellent job security.

                            What is the future of AI in DevOps and automation?

                            AI is revolutionizing DevOps through AIOps (predictive monitoring, automated incident response), GitHub Copilot for infrastructure code generation, intelligent testing, self-healing systems, and automated cost optimization. AI-powered DevOps enables faster deployment, improved reliability, reduced manual intervention, and significant efficiency gains across CI/CD pipelines, Kubernetes management, and cloud operations.

                            What industries hire DevOps professionals with AI skills?

                            Technology and SaaS companies, financial services and banking (BFSI), healthcare and life sciences, e-commerce and retail, telecommunications, media and entertainment, manufacturing, government and public sector, and startups building cloud-native applications with Kubernetes and microservices architectures.

                            When do I get access to Advanced DevOps Certification Training with GenA course content?

                            Immediate access after signup to course materials, pre-requisite resources, community forums, and environment setup guides. Live sessions start as per your selected batch schedule.

                            Is lifetime access included for course materials?

                            Yes, lifetime access to all 20 live module recordings, 5 self-paced modules (Service Mesh, Chaos Engineering, FinOps, Advanced Terraform, Career Development), lab environments, project templates, code repositories, infrastructure templates, and documentation with regular updates.

                            What is the difference between DevOps and Platform Engineering?

                            DevOps focuses on CI/CD pipelines, automation, and collaboration between development and operations. Platform Engineering builds Internal Developer Platforms (IDP) with self-service infrastructure, standardized workflows, and developer experience optimization. Module 20 covers platform engineering with Backstage, enabling you to pursue both DevOps and Platform Engineer career paths.

                            Have more questions?
                            Course counsellors are available 24x7
                            For Career Assistance :