BITS WILP Cloud Computing Knowledge Base: Semester 1 Resources

Big Data Systems involves thinking rigorously in terms of distributed systems, storage paradigms, and architectures highly relevant in the modern AI and cloud engineering era. An end-to-end understanding of HDFS, MapReduce execution, Spark Resilient Distributed Datasets (RDDs), NoSQL columnar models, partitioning strategies, and replication dynamics will anchor your understanding across the entire Cloud Computing program.

The flagship course of the program. Cloud Computing covers the complete architecture of modern enterprise cloud platforms: Virtualization technologies, hypervisor internals, containerization with Docker and Kubernetes, storage architectures (Object, Block, File), multi-tenant security frameworks, SLA calculations, high availability, and auto-scaling patterns.

Mastering Distributed Computing is universally considered the toughest academic hurdle in Semester 1, but pays off tremendously in senior cloud architect roles. The course demands algorithmic mastery of Interprocess Communication (IPC, RPC), Logical Clocks, Lamport timestamps, Vector clocks, Distributed Mutual Exclusion (Ricart-Agrawala, Maekawa), Leader Election (Bully, Ring), Consensus protocols (2PC, Paxos, Raft), and Consistency Models.

Not everyone's favorite subject initially, but an absolute prerequisite for building and operating scalable cloud backends. Network Fundamentals for Cloud unpacks the modern data center fabric: Spine-and-Leaf Clos topologies, Software-Defined Networking (SDN with OpenFlow), Network Function Virtualization (NFV), Virtual Private Clouds (VPC, CIDR, Subnets, Route Tables), overlay network protocols (VXLAN, GENEVE), and cloud load balancer design.