- What is DevOps? - Culture, practices, and philosophy
- DevOps vs Traditional IT - Breaking down silos
- DevOps Principles: Continuous Integration, Continuous Deployment, Automation
- The DevOps Lifecycle: Plan, Code, Build, Test, Release, Deploy, Operate, Monitor
- Cultural transformation and collaboration mindset
- Git fundamentals: Repositories, branches, merges, rebases, conflict resolution
- Git workflows: GitFlow, GitHub Flow, Trunk-based development
- GitHub/GitLab: Issues, Projects, Pull/Merge requests, code review workflows
- Branch protection: Merge strategies, status checks, CODEOWNERS
- Open source contributions: Fork-clone-PR workflow, community collaboration
- Python basics: Variables, loops, functions, data structures, error handling
- DevOps automation: File operations, system interactions, process management
- API integration: REST APIs, JSON/YAML parsing, HTTP requests
- AWS automation: Boto3 for AWS resource management and automation
- CLI development: Building command-line tools for DevOps workflows
- Linux architecture: Understanding processes, systemd, filesystem hierarchy
- Essential commands: File operations, text processing, system monitoring
- User management: File permissions, sudo, user/group administration
- Process management: ps, top, htop, kill, systemctl, job control
- Log management: System logs, log rotation, journalctl
- Network troubleshooting: netstat, ss, tcpdump, curl
- Bash scripting fundamentals: Variables, conditionals, loops, functions
- Automation scripts: Cleanup scripts, log rotation, system monitoring
- Alerting systems: Email notifications, webhook integrations
- Cron jobs: Scheduling automated tasks, system maintenance
- Error handling: Exit codes, debugging, logging best practices
- OSI Model: Understanding the 7-layer network model
- TCP/IP Stack: IP addressing, subnetting, CIDR notation
- DNS: Domain resolution, DNS records (A, CNAME, MX, TXT)
- HTTP/HTTPS: Status codes, headers, SSL/TLS certificates
- Load balancing: Round-robin, least connections, health checks
- Firewalls: iptables, ufw, security groups, NACLs
- VPN: Site-to-site, client-to-site, WireGuard, OpenVPN
- Network protocols: SSH, FTP/SFTP, NTP, DHCP
- Troubleshooting tools: ping, traceroute, nslookup, dig, wireshark
- Build automation concepts: Dependency management, artifact creation, build optimization
- CI Platforms: GitHub Actions, GitLab CI, Jenkins for pipeline orchestration
- Testing frameworks: Unit testing patterns, integration testing strategies, test data management
- Code quality analysis: Static code analysis, security scanning, dependency vulnerability checks
- DevSecOps integration: SAST tools (SonarQube), DAST scanning, dependency scanning
- Artifact repositories: Binary storage, versioning strategies, artifact promotion pipelines
- Build environments: Containerized builds, reproducible environments, build caching
- Deployment strategies: Blue-green deployments, canary releases, feature flags, A/B testing
- Release orchestration: Multi-environment promotion, automated rollbacks, deployment windows
- Configuration management: Environment-specific configs, secrets management, configuration drift detection
- Database deployment: Schema migrations, data migrations, zero-downtime database updates
- Infrastructure provisioning: Environment creation, resource scaling, cleanup automation
- Deployment verification: Health checks, smoke tests, automated validation, monitoring integration
- IaC Platforms: Terraform, CloudFormation, Pulumi for infrastructure provisioning
- Declarative infrastructure: Resource definitions, state management, idempotency principles
- Infrastructure templating: Modularization, parameterization, reusable components
- State management: Remote state storage, state locking, state migration, team collaboration
- Change management: Plan-apply workflows, change validation, rollback strategies
- Policy enforcement: Resource compliance, cost controls, security policies, governance
- Configuration management: Ansible, Puppet for desired state configuration
- Docker fundamentals: Process isolation, namespaces, cgroups, filesystem layers
- Image optimization: Multi-stage builds, layer caching, image size reduction, security hardening
- Container networking: Bridge networks, overlay networks, port mapping, network isolation
- Storage management: Volume types, persistent storage, data lifecycle management
- Security practices: Image scanning, runtime security, user permissions, secrets handling
- Container registries: Docker Hub, ECR, ACR for image distribution and vulnerability scanning
- Kubernetes fundamentals: Control plane components, worker nodes, etcd, API server concepts
- Workload management: Deployments, StatefulSets, DaemonSets, Jobs, CronJobs
- Service discovery: DNS-based discovery, Services, Ingress controllers, load balancing
- Configuration management: ConfigMaps, Secrets, environment injection, configuration hot-reloading
- Storage orchestration: Persistent volumes, storage classes, dynamic provisioning, CSI drivers
- Network policies: Micro-segmentation, ingress/egress rules, east-west traffic control
- Auto-scaling: Horizontal Pod Autoscaler, Vertical Pod Autoscaler, cluster autoscaling
- Helm package management: Application templating, dependency management, release lifecycle
- Service mesh: Istio, Linkerd for traffic management, security policies, observability
- GitOps: ArgoCD, FluxCD for declarative deployments, git-based workflows
- Multi-cluster management: Cluster federation, cross-cluster networking, workload distribution
- Runtime security: Pod security standards, admission controllers, policy enforcement
- Resource governance: Resource quotas, limit ranges, priority classes, quality of service
- AWS fundamentals: EC2, S3, VPC, IAM, CloudWatch for core infrastructure
- Container services: ECS, EKS, Fargate for container orchestration
- Serverless computing: Lambda, API Gateway, EventBridge, Step Functions
- Database services: RDS, DynamoDB, ElastiCache for data persistence
- Networking services: ALB, NLB, Route 53, CloudFront for traffic management
- DevOps services: CodeCommit, CodeBuild, CodeDeploy, CodePipeline
- Security services: AWS IAM, Secrets Manager, Parameter Store, GuardDuty
- Cloud abstraction: Vendor-agnostic architectures, API standardization, portability patterns
- Hybrid connectivity: Site-to-site VPNs, dedicated connections, edge computing integration
- Data synchronization: Cross-cloud replication, data lakes, ETL/ELT processes
- Workload distribution: Geographic distribution, disaster recovery, load balancing
- Cost optimization: Resource rightsizing, reserved instances, spot instances, usage analytics
- Compliance management: Data residency, regulatory requirements, audit trails
- Identity federation: Single sign-on, multi-factor authentication, identity providers
- Network security: Zero-trust networking, micro-segmentation, traffic inspection
- Data protection: Encryption at rest, encryption in transit, key management, tokenization
- Compliance frameworks: Automated compliance checking, audit logging, evidence collection
- Threat detection: Behavioral analysis, anomaly detection, incident response automation
- Vulnerability management: Continuous scanning, patch management, risk assessment
- Developer experience platforms: Self-service infrastructure, golden paths, developer portals
- Service catalogs: Template management, standardization, governance, compliance automation
- Abstraction layers: Infrastructure APIs, platform APIs, multi-cloud abstraction
- Workflow automation: Request fulfillment, approval processes, lifecycle management
- Resource provisioning: Dynamic environments, ephemeral infrastructure, cost tracking
- Documentation systems: API documentation, runbooks, knowledge management, searchability
- Metrics: Prometheus for collection, Grafana for visualization, time-series analysis
- Logging: ELK Stack (Elasticsearch, Logstash, Kibana), centralized log management
- Distributed tracing: OpenTelemetry, Jaeger, Zipkin for request flow analysis
- Application Performance Monitoring: DataDog, New Relic for code-level insights
- Alerting systems: Alert fatigue prevention, escalation policies, notification channels
- Service Level Objectives: Error budgets, burn rates, reliability engineering
- Observability correlation: Metrics-logs-traces integration, root cause analysis
- DevSecOps: SAST/DAST tools (SonarQube, Trivy, OWASP ZAP), security in CI/CD pipelines
- Container security: Twistlock, Aqua, Snyk, runtime protection, image scanning
- Infrastructure security: Policy as Code with Open Policy Agent, security compliance
- Supply chain security: SBOM generation, vulnerability management, signed artifacts
- AI/ML Operations: MLOps pipelines, model deployment, monitoring, versioning
- AIOps platforms: Anomaly detection, predictive analytics, intelligent alerting
- GenAI & Agentic AI: GitHub Copilot, code generation, documentation automation
- DevOps Agents: AI agents for log analysis, incident response, automated fixes
- Intelligent automation: Self-healing systems, automated incident response
- Set up a complete Git workflow with feature branches and collaboration
- Python DevOps projects: Log parser with alerting, AWS CLI automation tool
- Linux automation suite: Production backup, monitoring & recovery scripts
- Configure a home lab network with VLANs, firewall rules, and monitoring
- Shell scripting automation: System cleanup, log rotation, monitoring scripts
- DevSecOps Pipeline: End-to-end secure CI/CD with Jenkins + Docker + Trivy + SonarQube
- AWS CodePipeline: Production deployment with blue-green routing
- Create Infrastructure as Code for multi-tier application with Terraform + Ansible
- GitHub Actions: Advanced CI pipeline with SAST, OIDC integration with AWS
- Implement load balancing with health checks and failover testing
- Containerize microservices application with Docker multi-stage builds
- GitOps Continuous Delivery: ArgoCD + Helm + Kubernetes deployment
- Kubernetes production setup: EKS/AKS/GKE with NetworkPolicies and service mesh
- Secure container supply chain: Build pipeline with SBOM & vulnerability scanning
- Set up multi-cluster networking and cross-cluster communication
- Serverless 3-tier application: Lambda + API Gateway + DynamoDB + S3
- AWS Solutions Architect level cloud-native application deployment
- Multi-cloud application with vendor-agnostic architecture
- Design hybrid cloud networking with VPN and private connectivity
- Implement global load balancing with geographic traffic routing
- Observability stack: Prometheus + Loki + Tempo + OpenTelemetry for 3-tier app
- Event-driven microservices: Kafka + Kubernetes with monitoring
- DevOps Copilot Agent: AI agent for log analysis and CI failure fixes
- Cloud-native production platform: Complete microservices platform with enterprise GitOps
- Implement network automation with SDN and programmable infrastructure
- Load balancing: NGINX, HAProxy for algorithm selection, health checking, failover mechanisms
- Service discovery: Consul, etcd for registration patterns, health monitoring, DNS integration
- Content delivery: CloudFlare, AWS CloudFront for edge caching, geographic distribution
- Domain management: Route 53, DNS hierarchy, record types, propagation, failover
- Network monitoring: Nagios, Zabbix for performance metrics, traffic analysis
- CI/CD Platforms: GitHub Actions, GitLab CI, Jenkins for pipeline orchestration
- Build orchestration: Dependency resolution, parallel execution, artifact caching
- Testing strategies: Test pyramid, automation levels, feedback loops
- Artifact management: Nexus, Artifactory for binary repositories, versioning
- Infrastructure as Code: Terraform, CloudFormation for declarative provisioning
- Configuration management: Ansible, Puppet for desired state, drift detection
- Secret management: HashiCorp Vault, encryption, rotation, access patterns
- Policy enforcement: Open Policy Agent, compliance automation, governance
- Containerization: Docker for process isolation, resource management
- Container orchestration: Kubernetes for workload scheduling, service discovery
- Package management: Helm for application templating, dependency resolution
- GitOps: ArgoCD, FluxCD for declarative deployments, git-based workflows
- Monitoring stack: Prometheus + Grafana, ELK Stack for metrics and logs
- Distributed tracing: OpenTelemetry, Jaeger for request flow analysis
- DevSecOps: SAST/DAST tools, container security, vulnerability scanning
- AIOps & GenAI: Anomaly detection, GitHub Copilot, intelligent automation
- Focus on Phase 1-2 fundamentals
- Master Git, Linux, and basic CI/CD
- Gain experience with one cloud platform
- Develop scripting and automation skills
- Complete Phase 3-4 competencies
- Specialize in container orchestration
- Lead infrastructure automation projects
- Develop expertise in monitoring and observability
- Master Phase 5 advanced topics
- Architect complex CI/CD systems
- Lead digital transformation initiatives
- Mentor junior team members
- Platform Engineer: Focus on internal developer platforms
- Site Reliability Engineer: Emphasize monitoring and incident response
- Cloud Architect: Specialize in multi-cloud strategies
- Security Engineer: Focus on DevSecOps practices
- Automation Engineer: Specialize in infrastructure automation
- AWS: Solutions Architect, DevOps Engineer Professional
- Azure: DevOps Engineer Expert, Solutions Architect Expert
- GCP: Professional Cloud DevOps Engineer, Professional Cloud Architect
- Kubernetes: CKA (Certified Kubernetes Administrator), CKAD
- Docker: Docker Certified Associate
- HashiCorp: Terraform Associate, Vault Associate
- Red Hat: Red Hat Certified System Administrator (RHCSA)
- Networking: CCNA, CompTIA Network+, JNCIA
- "The DevOps Handbook" by Gene Kim
- "Continuous Delivery" by Jez Humble
- "Infrastructure as Code" by Kief Morris
- "The Phoenix Project" by Gene Kim
- "Accelerate" by Nicole Forsgren
- "Kubernetes in Action" by Marko Lukša
- "Terraform: Up & Running" by Yevgeniy Brikman
- "Docker Deep Dive" by Nigel Poulton
- "Site Reliability Engineering" by Google
- "Building Microservices" by Sam Newman
- "Computer Networking: A Top-Down Approach" by Kurose & Ross
- "TCP/IP Illustrated" by W. Richard Stevens
- Hands-on labs: A Cloud Guru, Linux Academy, Pluralsight
- Practice environments: KataCoda, Play with Docker/Kubernetes
- Documentation: Official cloud provider docs, Kubernetes docs
| Phase | Primary Focus | Key Technologies | Milestone |
|---|---|---|---|
| 1 | Foundations + Programming | Git, Linux, Python, TCP/IP, DNS | Automation scripting + network basics |
| 2 | CI/CD + Infrastructure | GitHub Actions, Terraform, Ansible | Production deployment pipelines |
| 3 | Containers + Orchestration | Docker, Kubernetes, Helm, GitOps | Production container workloads |
| 4 | Cloud + Architecture | AWS services, multi-cloud, hybrid | Cloud-native applications |
| 5 | Platform + Intelligence | Observability, DevSecOps, AI/ML | Enterprise-grade platforms |
- DevOps culture and mindset transformation
- Git workflow demonstrations
- Linux command line mastery
- Pipeline design and implementation
- Infrastructure as Code walkthrough
- Automated testing integration
- Docker best practices and optimization
- Kubernetes deployment strategies
- GitOps implementation
- Multi-cloud architecture design
- Security and compliance automation
- Cost optimization strategies
- Platform engineering trends
- AI/ML integration in DevOps
- 2026 predictions and career advice
- Deployment frequency: Daily vs weekly vs monthly
- Lead time: Code commit to production deployment
- Mean time to recovery: How quickly you can fix issues
- Change failure rate: Percentage of deployments causing issues
- Certifications earned: Target 2-3 relevant certifications
- Projects completed: Hands-on portfolio development
- Contributions: Open source or internal tool contributions
- Mentoring: Knowledge sharing and team leadership
This roadmap provides a structured path to becoming a proficient DevOps engineer by 2026. Adapt the timeline based on your current experience and focus on hands-on practice alongside theoretical learning.