Cloud computing systems today, whether open-source or used inside companies, are built using a common set of core techniques, algorithms, and design philosophies – all centered around distributed systems. Learn about such fundamental distributed computing "concepts" for cloud computing.
Cloud Computing Concepts, Part 1
Cloud Computing Concepts, Part 1
This course is part of Cloud Computing Specialization
Taught in English
Some content may not be translated
Instructor: Indranil Gupta
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Gain insight into a topic and learn the fundamentals
4.3
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23 hours (approximately)
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Assessments
8 quizzes
Course
Gain insight into a topic and learn the fundamentals
4.3
(1,049 reviews)
|
92%
Beginner level
No prior experience required
23 hours (approximately)
Flexible schedule
Learn at your own pace
See how employees at top companies are mastering in-demand skills
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This course is part of the Cloud Computing Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 5 modules in this course
This course is oriented towards learners with similar backgrounds as juniors and seniors in a CS undergraduate curriculum. Since learners come from various backgrounds, it is critical you view this lecture AND pass the prerequisite test. This will ensure you have many of the assumed prerequisite pieces of knowledge required to enjoy this course.
What's included
16 videos8 readings3 quizzes2 discussion prompts1 plugin
Lesson 1: This module teaches how the multicast problem is solved by using epidemic/gossip protocols. It also teaches analysis of such protocols. Lesson 2: This module covers the design of failure detectors, a key component in any distributed system. Membership protocols, which use failure detectors as components, are also covered. Lesson 3: This module covers Grid computing, an important precursor to cloud computing.
What's included
14 videos2 readings1 quiz1 discussion prompt
P2P systems: This module teaches the detailed design of two classes of peer to peer systems: (a) popular ones including Napster, Gnutella, FastTrack, and BitTorrent; and (b) efficient ones including distributed hash tables (Chord, Pastry, and Kelips). Besides focusing on design, the module also analyzes these systems in detail.
What's included
10 videos2 readings1 quiz1 discussion prompt
Lesson 1: This module motivates and teaches the design of key-value/NoSQL storage/database systems. We cover the design of two major industry systems: Apache Cassandra and HBase. We also cover the famous CAP theorem. Lesson 2: Distributed systems are asynchronous, which makes clocks at different machines hard to synchronize. This module first covers various clock synchronization algorithms, and then covers ways of tagging events with causal timestamps that avoid synchronizing clocks. These classical algorithms were invented decades ago, yet are used widely in today’s cloud systems.
What's included
12 videos3 readings1 quiz1 discussion prompt
Lesson 1: This module covers how to calculate a distributed snapshot, leveraging causality again to circumvent the synchronization problem. Lesson 2: This lecture teaches how to order multicasts in any distributed system. Algorithms for assigning timestamp tags to multicasts using various flavors of ordering – FIFO, Causal, and Total – are covered. The module also covers virtual synchrony, a paradigm that combines reliable multicasts with membership views. Lesson 3: Consensus is one of the most important problems in a distributed system, enabling multiple machines to agree. This module uses Paxos, one of the most popular consensus solutions used in the industry today. Paxos is not perfect because consensus cannot be solved completely – an optional lecture presents the famous FLP proof of impossibility of consensus.
What's included
16 videos4 readings2 quizzes1 programming assignment3 discussion prompts1 plugin
Instructor
Instructor ratings
4.5 (62 ratings)
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