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.
Some of these concepts include: clouds, MapReduce, key-value/NoSQL stores, classical distributed algorithms, widely-used distributed algorithms, scalability, trending areas, and much, much more!
Know how these systems work from the inside out. Get your hands dirty using these concepts with provided homework exercises. In the programming assignments, implement some of these concepts in template code (programs) provided in the C++ programming language. Prior experience with C++ is required.
The course also features interviews with leading researchers and managers, from both industry and academia.
Dieser Kurs ist Teil der Spezialisierung Spezialisierung Cloud Computing
Cloud Computing Concepts, Part 1
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Lehrplan - Was Sie in diesem Kurs lernen werden
Woche
16 Stunden zum Abschließen
Week 1: Orientation, Introduction to Clouds, MapReduce
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.
16 Videos (Gesamt 155 min), 8 Lektüren, 3 Quiz
16 Videos
Orientation Towards Cloud Computing Concepts: Some Basic Computer Science Fundamentals23m
Week 1 Introduction1m
1.1. Why Clouds?6m
1.2. What is a Cloud?5m
1.3. Introduction to Clouds: History7m
1.4. Introduction to Clouds: What's New in Today's Clouds7m
1.5. Introduction to Clouds: New Aspects of Clouds8m
1.6. Introduction to Clouds: Economics of Clouds7m
2.1. A cloud IS a distributed system5m
2.2. What is a distributed system?16m
3.1. MapReduce Paradigm14m
3.2. MapReduce Examples10m
3.3. MapReduce Scheduling12m
3.4. MapReduce Fault-Tolerance8m
Interview with Sumeet Singh16m
8 Lektüren
Orientation Overview10m
Syllabus10m
About the Discussion Forums10m
Instructions for Taking the Prerequisite Quiz10m
Course Learning Community and Social Media10m
Week 1 Overview10m
Homework 1 Instructions10m
Programming Assignment Instructions10m
3 praktische Übungen
Orientation Quiz10m
Prerequisite Quiz50m
Homework 114m
Woche
23 Stunden zum Abschließen
Week 2: Gossip, Membership, and Grids
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.
14 Videos (Gesamt 122 min), 2 Lektüren, 1 Quiz
14 Videos
1.1. Multicast Problem9m
1.2. The Gossip Protocol5m
1.3. Gossip Analysis15m
1.4. Gossip Implementations4m
2.1. What is Group Membership List?8m
2.2. Failure Detectors9m
2.3. Gossip-Style Membership7m
2.4. Which is the best failure detector?4m
2.5. Another Probabilistic Failure Detector9m
2.6. Dissemination and suspicion8m
3.1. Grid Applications6m
3.2. Grid Infrastucture11m
Interview with William Gropp20m
2 Lektüren
Week 2 Overview10m
Homework 2 Instructions10m
1 praktische Übung
Homework 212m
Woche
33 Stunden zum Abschließen
Week 3: P2P Systems
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.
10 Videos (Gesamt 105 min), 2 Lektüren, 1 Quiz
10 Videos
1. P2P Systems Introduction5m
2. Napster7m
3. Gnutella20m
4. FastTrack and BitTorrent7m
5. Chord22m
6. Failures in Chord14m
7. Pastry6m
8. Kelips10m
Blue Waters Supercomputer9m
2 Lektüren
Week 3 Overview10m
Homework 3 Instructions10m
1 praktische Übung
Homework 328m
Woche
44 Stunden zum Abschließen
Week 4: Key-Value Stores, Time, and Ordering
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.
12 Videos (Gesamt 147 min), 3 Lektüren, 1 Quiz
12 Videos
1.1. Why Key-Value/NOSQL?15m
1.2. Cassandra27m
1.3. The Mystery of X-The Cap Theorem19m
1.4. The Consistency Spectrum9m
1.5. HBase10m
2.1. Introduction and Basics10m
2.2. Cristian's Algorithm5m
2.3. NTP4m
2.4. Lamport Timestamps14m
2.5. Vector Clocks12m
Interview with Marcos Aguilera14m
3 Lektüren
Week 4 Overview10m
Optional: Lamport Timestamps (Ukulele Version)10m
Homework 4 Instructions10m
1 praktische Übung
Homework 450m
Woche
58 Stunden zum Abschließen
Week 5: Classical Distributed Algorithms
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.
16 Videos (Gesamt 156 min), 3 Lektüren, 3 Quiz
16 Videos
1.1. What is Global Snapshot?7m
1.2. Global Snapshot Algorithm10m
1.3. Consistent Cuts6m
1.4. Safety and Liveness7m
2.1. Multicast Ordering16m
2.2. Implementing Multicast Ordering 19m
2.3. Implementing Multicast Ordering 27m
2.4. Reliable Multicast5m
2.5. Virtual Synchrony11m
3.1. The Consensus Problem12m
3.2. Consensus In Synchronous Systems8m
3.3. Paxos, Simply13m
3.4. The FLP Proof [OPTIONAL]20m
Interview with Tushar Chandra13m
Conclusion to Cloud Computing Concepts, Part 13m
3 Lektüren
Week 5 Overview10m
Homework 5 Instructions10m
Final Exam Instructions10m
2 praktische Übungen
Homework 530m
Final Exam
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Top-Bewertungen
Great course, I would recommend to everyone who wants to understand the basics of cloud computing. The course material is excellent, the instructor Indy is phenomenal and the exams are marvelous.
This instructor is fantastic. He is exceptionally thorough and his delivery is very good as well. This is a course definitely worth taking if you are interested in learning more about the cloud.
Dozent
Indranil Gupta
ProfessorDepartment of Computer Science
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Über die Spezialisierung Cloud Computing
The Cloud Computing Specialization takes you on a tour through cloud computing systems. We start in in the middle layer with Cloud Computing Concepts covering core distributed systems concepts used inside clouds, move to the upper layer of Cloud Applications and finally to the lower layer of Cloud Networking. We conclude with a project that allows you to apply the skills you've learned throughout the courses.
The first four courses in this Specialization form the lecture component of courses in our online Master of Computer Science Degree in Data Science. You can apply to the degree program either before or after you begin the Specialization.
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