I am having 6 years of hands-on experience in Cloud DevOps, I specialize in AWS, Docker, Kubernetes, CI/CD, and automation. My mission is to simplify complex DevOps concepts and help professionals like you gain the practical skills needed to excel in real-world projects.
Cloud DevOps Essentials – Learn AWS, Linux, and Infrastructure as Code (IaC).
Docker & Kubernetes – Master containerization and Kubernetes orchestration.
CI/CD Pipelines – Automate deployments with Jenkins, GitHub Actions, and GitLab CI.
Infrastructure Automation – Use Terraform and Ansible for cloud provisioning.
Monitoring & Logging – Implement Prometheus, Grafana, and ELK Stack for observability.
Security & Best Practices – Secure cloud environments with IAM, RBAC, and DevSecOps strategies.
Hands-On Approach – Learn by doing with real-world projects and labs.
Industry-Relevant Skills – Aligned with current job market demands.
Step-by-Step Guidance – From beginner to advanced levels.
Job-Ready Training – Resume-building tips, interview preparation, and career guidance.
If you're serious about becoming a Cloud DevOps expert, let’s start your journey today
Experience
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Sr Devops engineer (Jul, 2023
–Present) at NTTdata
Designing and maintaining CI/CD pipelines (using Jenkins, GitHub Actions, GitLab CI, etc.).
Automating build, test, and deployment processes.
Ensuring smooth and fast software delivery.
Managing infrastructure as code (IaC) to improve efficiency and consistency.
Automating repetitive tasks like provisioning and configuration updates.
Creating, managing, and optimizing Docker images and Dockerfiles.
Using Docker Compose for multi-container applications in local development.
Managing container registries (Docker Hub, AWS ECR, Azure ACR, GCR).
Ensuring container security by scanning for vulnerabilities.
Integrating Docker and Kubernetes into CI/CD pipelines using Jenkins, GitHub Actions, GitLab CI, ArgoCD, etc.
Automating container builds, testing, and deployments.
Implementing rolling updates, blue-green deployments, and canary releases in Kubernetes.
Fee details
₹1,200–2,000/hour
(US$12.63–21.05/hour)