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Guided learning journeys that build knowledge step by step.
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7812 Paths · page 406 / 782
A structured learning path covering message brokers (Kafka, RabbitMQ), publish-subscribe patterns, and stream processing frameworks (Flink, Spark Streaming). Starting with distributed systems fundamentals, it progresses through messaging paradigms to hands-on stream processing, ensuring a solid understanding of how modern data pipelines are built.
This path systematically introduces Distributed Hash Tables (DHTs), starting with fundamental networking and hashing concepts, then covering key DHT algorithms (Chord, Pastry, Tapestry, Kademlia), and concluding with practical applications in P2P systems. It is designed for university students in distributed systems courses.
A systematic path covering the fundamentals of ACID, distributed transaction coordination, and the two-phase commit protocol, including failure handling and comparisons with alternatives like 3PC.
This learning path guides students through the foundational concepts of data replication and consistency in distributed systems. Starting with distributed systems basics, it covers replication strategies, consistency models, the CAP theorem, and practical trade-offs, culminating in an understanding of how to choose appropriate consistency guarantees for real-world applications.
This learning path guides students and developers through the fundamentals of distributed consensus, focusing on the Raft algorithm. It covers the core components of Raft—leader election, log replication, safety, and membership changes—while building on basic distributed systems concepts and contrasting with Paxos.
A structured learning path for advanced university students to understand the Paxos consensus algorithm, covering the consensus problem, system model, Paxos roles, phases, safety and liveness, and Multi-Paxos.
This path introduces the fundamental challenges of distributed coordination and how services like Apache ZooKeeper address them. It covers ZooKeeper's architecture, data model, sessions, watches, and practical use cases such as leader election and configuration management. Designed for university-level students and developers, it builds from distributed systems basics to intermediate coordination concepts.
This learning path guides CS students through the fundamental concepts and practical architectures of distributed file systems. Starting with core networking and file system basics, it progresses through classic systems like NFS and AFS, and culminates in a deep dive into Google File System (GFS), covering caching, consistency, and fault tolerance.
This path introduces the foundational concepts and algorithms for capturing and coordinating global state in distributed systems. It covers time and ordering, distributed snapshots, consensus, leader election, and mutual exclusion, providing a systematic understanding of how distributed processes coordinate.
This learning path introduces the fundamental challenges of time and ordering in distributed systems. It covers the limitations of physical clocks, the concept of logical time, and the key algorithms—Lamport timestamps and vector clocks—used to order events without global time. Designed for high school students with basic knowledge of distributed systems and communication.