MCA - Cloud and DevOps
Program Description:
IBM Q²D is a global initiative offering specialized master’s programs in collaboration with top academic institutions. We are offering an advanced 2-year MCA program specializing in Cloud and DevOps.
S - Vyasa Deemed to be University located inside Sattva Global City, Kengeri, which is a NAAC A+, Category 1 University, would be the first university in India to execute this model of student engagement in designed to equip students with cutting-edge skills, real-time exposure, and practical project experience, aligning with future workforce demands.
You've embarked on a cutting-edge master's program, crafted with industry leaders and delivered by IBM subject matter experts in a world-class learning environment.
Program benefits include:
- A Postgraduate Degree awarded by S-VYASA
- An Advanced Certificate Digital Badge from IBM
- Advanced Learning Certificate from Cambridge University Press and Assessment
This strategic academic-industry collaboration is designed to equip students with both foundational knowledge and practical skills in emerging domains, preparing them for high-impact careers in the digital era.
Campus Location:
All programs are conducted at the futuristic S-VYASA Bangalore Campus, located inside Sattva Global City IT Park, Kengeri.
The "IBM ICE Advanced Certificate - Cloud and DevOps" program is a comprehensive program designed to equip learners with the essential knowledge and skills to understand, implement, and manage modern cloud computing and DevOps practices. Spanning approximately 200+ hours, this program covers the fundamentals of cloud computing, containerization and orchestration technologies, the creation and management of CI/CD pipelines, the principles and implementation of Infrastructure as Code, and advanced cloud and DevOps practices including monitoring, optimization, security, and AI/ML workload deployment.
FEE STRUCTURE 2025-26
| Duration: 2 Years | I YEAR | II YEAR |
| Admission fee | 15000 | - |
| Tuition Fee | 295000 | 280000 |
| Other Academic Fee | 5200 | 5200 |
| Total Fee | 315200 | 285200 |
Program Objectives
Upon successful completion of this program, learners will be able to:
- Understand the fundamental concepts of cloud computing, including service and deployment models, and the offerings of major cloud providers.
- Master containerization using Docker for application packaging and isolation.
- Implement and manage container orchestration using Kubernetes for scalable cloud deployments.
- Design, build, and manage automated CI/CD pipelines using industry-standard tools.
- Understand and implement Infrastructure as Code (IaC) using tools like Terraform and Ansible for cloud infrastructure management.
- Set up comprehensive monitoring and logging solutions for cloud environments.
- Implement performance optimization techniques for cloud workloads.
- Apply cloud security best practices to ensure secure deployments.
- Understand the considerations for deploying and managing AI/ML workloads on cloud platforms.
Program Summary
This program is structured into five progressive modules that cover the core aspects of Cloud and DevOps. Module 1 introduces the foundational concepts of cloud computing. Module 2 focuses on containerization with Docker and orchestration with Kubernetes. Module 3 delves into building and managing CI/CD pipelines for automation. Module 4 covers the principles and implementation of Infrastructure as Code. Finally, Module 5 explores advanced cloud and DevOps practices including monitoring, optimization, security, and AI/ML on the cloud.
Flow of Learning Modules:
- Fundamental concepts of cloud computing.
- Cloud service models: Infrastructure as a Service (IaaS), Platform as a Service (PaaS), Software as a Service (SaaS).
- Cloud deployment models: Public cloud, private cloud, hybrid cloud, multi-cloud.
- Key characteristics of cloud computing: On-demand self-service, broad network access, resource pooling, rapid elasticity, measured service.
- Overview of major cloud providers: Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform (GCP) - basic service categories and offerings.
- Containerization concepts and benefits.
- Introduction to Docker: Dockerfiles, images, containers, networking, storage.
- Hands-on experience with Docker commands and basic Dockerfile creation.
- Introduction to Kubernetes: Architecture (master-node, worker-node), pods, deployments, services, namespaces.
- Deploying and managing containerized applications using Kubernetes.
- Scaling and updating applications in Kubernetes.
- Principles of Continuous Integration (CI) and Continuous Delivery (CD).
- Introduction to CI/CD tools: Jenkins, GitLab CI, Azure DevOps (one or more likely emphasized).
- Designing and building CI/CD pipelines for automated build, test, and deployment processes.
- Integrating version control systems (e.g., Git) with CI/CD pipelines.
- Automating software testing within CI/CD pipelines.
- Deployment strategies to cloud environments (e.g., blue/green, canary).
- Principles and benefits of Infrastructure as Code (IaC).
- Introduction to Terraform: Writing Terraform configurations to provision cloud resources (e.g., virtual machines, networks, storage).
- Introduction to Ansible: Writing Ansible playbooks for configuration management and application deployment.
- Comparing and contrasting Terraform and Ansible.
- Automating infrastructure provisioning and management in cloud environments.
Program Outcomes:
Upon successful completion of this program, learners will be able to:
- Explain the fundamental concepts and models of cloud computing.
- Containerize applications using Docker and orchestrate them with Kubernetes.
- Design, build, and manage automated CI/CD pipelines using industry-standard tools.
- Implement Infrastructure as Code using Terraform and Ansible to manage cloud infrastructure.
- Set up basic monitoring and logging for cloud environments.
- Understand performance optimization and security best practices for cloud workloads.
- Identify key considerations for deploying AI/ML workloads on the cloud..
Skills Gained:
Upon completion of this program, learners will gain the following skills:
- Cloud Computing Fundamentals: Understanding cloud models and providers.
- Containerization with Docker: Packaging and managing applications in containers.
- Container Orchestration with Kubernetes: Deploying, scaling, and managing containerized applications.
- CI/CD Pipeline Management: Designing and implementing automated software delivery pipelines.
- Infrastructure as Code (IaC): Provisioning and managing cloud infrastructure using Terraform and Ansible.
- Cloud Monitoring and Logging: Setting up basic monitoring and logging solutions.
- Cloud Performance Optimization: Understanding techniques for improving cloud workload performance.
- Cloud Security Basics: Applying fundamental security best practices in the cloud.
- Awareness of AI/ML on Cloud: Understanding key considerations for deploying AI/ML workloads.