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Who This Program Is For Beginners entering DevOps, Cloud, or SRE — including freshers and non-IT backgrounds Testing, Support, Infra, and App Developers moving into DevOps / SRE / Cloud / Platform Engineering Working DevOps and Cloud Engineers who want to fill gaps and move into senior or product-company roles SREs wanting stronger observability, incident response, and AIOps skills Platform Engineers building Kubernetes, GitOps, and internal developer platforms System / Linux / Network Admins modernising into Cloud and Automation Cloud and Data Engineers adding AI, MLOps, and GenAI Mid-career engineers targeting senior, lead, or architect positions Career switchers from Java, Python, .NET, or Database backgrounds Job seekers and laid-off professionals needing projects, mentorship, mock interviews, and referrals What You Will Achieve Strong fundamentals + advanced skills across DevOps, Cloud, SRE, Platform, and AI 15 production-grade projects on your GitHub Job-ready Resume, LinkedIn, and GitHub portfolio 10+ verified referrals across startups, product companies, and MNCs Mock interviews, system design practice, and continuous interview readiness 1:1 mentorship with a personalized roadmap and weekly progress reviews Live Sessions — Weekly Cadence You are never learning alone. 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Tools covered: Linux, Git, Docker, Kubernetes, Helm, Terraform, Ansible, Jenkins, GitHub Actions, Prometheus, Grafana, ELK, AWS (IAM, EC2, VPC, S3, RDS, Lambda, API Gateway), Azure (Intro), Python and Shell scripting. Phase 2 — 15 Live Industry-Grade Projects You will design, build, demo, and ship every project end-to-end with mentor support. Project 1 — DevOps Workflow & Agile Delivery Setup Why: Every product team runs on Agile and DevOps workflows. Without knowing how Jira, Git branching, releases, and ceremonies actually work, you will struggle from day one. You will learn: How real teams plan sprints, branch and release code, and collaborate across roles. Stack: Jira, Confluence, Git, GitHub, branching strategies, Slack. Project 2 — AWS Multi-Account Governance with Control Tower Why: Companies don't run on a single AWS account — they have separate accounts for dev, QA, prod, security, and billing. You need to set this up and govern it safely. You will learn: Build a secure multi-account landing zone with guardrails, SSO, and centralized billing. Stack: AWS Organizations, Control Tower, IAM Identity Center, SCPs, CloudTrail, Config. Project 3 — Golden AMI Pipeline Why: Enterprises don't launch random images in production. They use hardened, patched, standardized images so every server is secure and consistent. You will learn: Automate the build, hardening, and distribution of secure base images. Stack: Packer, Ansible, Jenkins, AWS EC2, Systems Manager, CIS hardening. Project 4 — Infrastructure Automation with Terraform & Ansible Why: Clicking in the AWS console doesn't scale. Real teams provision and configure everything as code so it's versioned, reviewed, and reproducible. You will learn: Design reusable Terraform modules and use Ansible for configuration in a production-style setup. Stack: Terraform modules, Ansible, AWS VPC / EC2 / RDS / ALB, Remote State (S3 + DynamoDB). Project 5 — Serverless Application Architecture Why: Many modern apps run serverless to cut cost and scale automatically. Engineers who design event-driven systems are in high demand. You will learn: Build a scalable, event-driven app with APIs, storage, and async processing. Stack: AWS Lambda, API Gateway, DynamoDB, S3, EventBridge, SAM / Serverless Framework. Project 6 — Kubernetes + GitOps Deployments Why: Kubernetes is the default for microservices, and GitOps is how serious teams deploy — through Git, not manual kubectl. You will learn: Deploy and manage microservices on Kubernetes using a declarative GitOps workflow. Stack: Kubernetes (EKS), Helm, ArgoCD, Kustomize, Ingress, HPA. Project 7 — Monitoring & Observability Platform Why: If you can't see what's happening in production, you can't fix it. Every serious team invests heavily in metrics, logs, and traces. You will learn: Design a complete observability stack across services. Stack: Prometheus, Grafana, Loki, Alertmanager, CloudWatch, OpenTelemetry. Project 8 — End-to-End CI/CD Pipeline Why: Manual deployments are slow and risky. CI/CD is the heart of DevOps and almost every interview tests it. You will learn: Build multi-stage pipelines for containerized apps with automated build, test, and deploy. Stack: Jenkins / GitHub Actions, Maven / Gradle, Docker, Kubernetes, SonarQube, Slack. Project 9 — MLOps Pipeline on AWS Why: Companies are deploying ML models everywhere, and most data scientists can't operationalize them. Engineers who understand MLOps are paid a premium. You will learn: Train, version, deploy, and monitor ML models in production. Stack: AWS SageMaker, S3, MLflow, Docker, GitHub Actions, Model Registry, CloudWatch. Project 10 — GenAI Application with AWS Bedrock Why: Every company is trying to ship GenAI features. Engineers who can actually build and deploy them safely are rare and highly valued. You will learn: Build a production-ready GenAI app with foundation models, APIs, and guardrails. Stack: AWS Bedrock (Claude / Llama), Lambda, API Gateway, S3, Streamlit / React. Project 11 — Cloud Cost Optimization & FinOps Why: Cloud bills get out of control fast. Engineers who can reduce spend without breaking systems become trusted across the org. You will learn: Analyse and reduce AWS spend through tagging, rightsizing, and automation. Stack: AWS Cost Explorer, Budgets, Compute Optimizer, Trusted Advisor, Lambda, Athena. Project 12 — Automated Testing in CI/CD Why: A pipeline that doesn't test properly is just a fast way to ship bugs. Real teams gate releases on automated quality checks. You will learn: Embed unit, integration, and end-to-end testing into CI/CD with proper reporting. Stack: JUnit / PyTest, Selenium, Postman / Newman, JaCoCo, Allure Reports, Jenkins. Project 13 — Secure DevOps CI/CD (DevSecOps) Why: Security can't be bolted on at the end. Companies expect security checks, secret management, and image scanning baked into the pipeline. You will learn: Add code quality gates, dependency and image scanning, secrets management, and a Dev → QA → Prod artifact promotion flow. Stack: Jenkins / GitHub Actions, SonarQube, Snyk, Trivy, HashiCorp Vault, GitHub Secrets, JFrog / Nexus / ECR, OWASP ZAP, Docker, Kubernetes. Project 14 — AI-Powered Log & Incident Analysis (AIOps) Why: Production generates more logs and alerts than humans can read. LLMs are now used to triage incidents and suggest fixes — a key edge for modern SRE / DevOps. You will learn: Use LLMs and ML to summarise logs, triage incidents, and suggest remediation. Stack: Python, OpenAI / Bedrock, LangChain, OpenSearch / ELK, Prometheus, Slack / PagerDuty. Project 15 — AI-Driven Data Pipeline (Cloud Data Engineering) Why: Data + AI is where the highest-paid roles are heading. Knowing how to feed clean data into LLMs (RAG) is a skill very few engineers have. 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Phase 3 — Interview Preparation Technical drills: DevOps, Cloud, Kubernetes, CI/CD, Terraform, Linux, Scripting Scenario and system design rounds: real production problem-solving SRE and Platform rounds: SLO/SLI design, incident response, on-call readiness Behavioural and HR rounds: STAR method, leadership principles Mock interviews: recorded, reviewed, and debriefed Curated question bank from real hiring loops Resume, LinkedIn, and GitHub optimization Phase 4 — Referrals & Placement Support 10+ verified referrals across startups, product companies, and MNCs Active job leads in the community channel Placement coordinator support and follow-ups Weekly progress tracking until you land the role Continued support post-offer (negotiation and onboarding) Program Highlights Outcome-based, not time-based — stay until you achieve your goal Join anytime — no rigid batches; repeat the program multiple times until you get your result Live weekend sessions + midweek doubt-clearing 1:1 mentorship from a senior DevOps Cloud AI Architect Dedicated Slack community with mentors, peers, and hiring partners Mentorship + Project Completion Certificates (GitHub verified) Work Experience Letter to support your applications Lifetime access to recorded content, project code, and templates UPI Payments as backup- UPI to 9888055959 or direct2sanjeev@icici

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