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.
This course builds on the material covered in the Cloud Computing Concepts, Part 1 course.
Dieser Kurs ist Teil der Spezialisierung Spezialisierung Cloud Computing
Cloud Computing Concepts: Part 2
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Lehrplan - Was Sie in diesem Kurs lernen werden
Woche
14 Stunden zum Abschließen
Week 1: Course Orientation and Classical Distributed Algorithms Continued
Lesson 1: To coordinate machines in a distributed system, this module first looks at classical algorithms for electing a leader, including the Ring algorithm and Bully algorithm. We also cover how Google’s Chubby and Apache Zookeeper solve leader election. Lesson 2: This module covers solutions to the problem of mutual exclusion, which is important for correctness in distributed systems with shared resources. We cover classical algorithms, including Ricart-Agrawala’s algorithm and Maekawa’s algorithm. We also cover Google’s Chubby support for mutual exclusion.
11 Videos (Gesamt 122 min), 7 Lektüren, 2 Quiz
11 Videos
Orientation Towards Cloud Computing Concepts: Some Basic Computer Science Fundamentals23m
Week 1 Introduction1m
1.1. The Election Problem8m
1.2. Ring Leader Election14m
1.3. Election in Chubby and ZooKeeper9m
1.4. Bully Algorithm9m
2.1. Introduction and Basics12m
2.2. Distributed Mutual Exclusion10m
2.3. Ricart-Agrawala's Algorithm11m
2.4. Maekawa's Algorithm and Wrap-Up16m
7 Lektüren
Orientation Overview10m
Syllabus10m
About the Discussion Forums10m
Course Learning Community and Social Media10m
Week 1 Overview10m
Homework 1 Instructions10m
Programming Assignment Instructions10m
2 praktische Übungen
Orientation Quiz10m
Homework 120m
Woche
22 Stunden zum Abschließen
Week 2: Concurrency and Replication Control
Lesson 1: Transactions are an important component of many cloud systems today. This module presents building blocks to ensure transactions work as intended, from Remote Procedure Calls (RPCs), to serial equivalence for transactions, to optimistic and pessimistic approaches to concurrency control, to deadlock avoidance/prevention. Lesson 2: This module covers how replication – maintaining copies of the same data at different locations – is used to provide many nines of availability in distributed systems, as well as different techniques for replication and for ensuring transactions commit correctly in spite of replication.
8 Videos (Gesamt 95 min), 2 Lektüren, 1 Quiz
8 Videos
1.1. RPCs17m
1.2. Transactions13m
1.3. Serial Equivalence12m
1.4. Pessimistic Concurrency13m
1.5. Optimistic Concurrency Control9m
2.1. Replication14m
2.2. Two-Phase Commit11m
2 Lektüren
Week 2 Overview10m
Homework 2 Instructions10m
1 praktische Übung
Homework 230m
Woche
33 Stunden zum Abschließen
Week 3: Emerging Paradigms
Lesson 1: We study the emerging area of stream processing, touching on key design aspects of Apache Storm. Lesson 2: We study how enormous graphs can be processed in clouds. Lesson 3: We study various types of networks/graphs that are both natural and artificial, and their surprising commonalities. Lesson 4: This module presents classical scheduling algorithms that have been used in operating systems since the inception of computers. We then cover two popular scheduling algorithms for Hadoop.
9 Videos (Gesamt 110 min), 2 Lektüren, 1 Quiz
9 Videos
Stream Processing in Storm15m
Distributed Graph Processing16m
Structure of Networks21m
4.1. Single-processor Scheduling11m
4.2. Hadoop Scheduling11m
4.3. Dominant-Resource Fair Scheduling8m
Storm Demo 9m
Apache Spark by Faria Kalim12m
2 Lektüren
Week 3 Overview10m
Homework 3 Instructions10m
1 praktische Übung
Homework 330m
Woche
43 Stunden zum Abschließen
Week 4: Classical Systems
Lesson 1: When files and directories are stored/accessed over the network, it is called a distributed file system. This module covers the working of distributed file systems like NFS and AFS. Lesson 2: This module covers Distributed Shared Memory systems, their techniques, and pros/cons. Lesson 3: This module looks at the area of sensor networks, starting from what’s inside a sensor mote and how networks of them work.
6 Videos (Gesamt 109 min), 2 Lektüren, 1 Quiz
6 Videos
1.1. File System Abstraction23m
1.2. NFS and AFS14m
Distributed Shared Memory17m
Sensor and Their Networks30m
Interview with Brighten Godfrey23m
2 Lektüren
Week 4 Overview10m
Homework 4 Instructions10m
1 praktische Übung
Homework 420m
Woche
57 Stunden zum Abschließen
Week 5: Real-Life Behaviors
Lesson 1: This module is a primer on basic security concepts, not just applied to distributed systems, but also more generally. We study various policies and mechanisms, including encryption, authentication, and authorization. Lesson 2: This module presents case studies of real datacenter outages, and attempts to draw lessons on how to prevent them and how to better prepare for them.
11 Videos (Gesamt 102 min), 3 Lektüren, 3 Quiz
11 Videos
1.1. Basic Security Concepts9m
1.2. Basic Cryptography Concepts8m
1.3. Implementing Mechanism using Cryptography15m
2.1. What Causes Disasters?6m
2.2. AWS Outage14m
2.3. Facebook Outage5m
2.4. The Planet Outage5m
2.5. Wrap-Up7m
Interview with Paul Kwiat24m
Conclusion to Cloud Computing Concepts, Part 23m
3 Lektüren
Week 5 Overview10m
Homework 5 Instructions10m
Final Exam Instructions10m
2 praktische Übungen
Homework 520m
Final Exam
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.
Very nice and informative course, and the programming assignment in the end of the course is so helpful to understand and apply the theoretical concepts that was introduced during the course
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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