Cloud Computing Concepts: Part 2

University of Illinois at Urbana-Champaign via Coursera

Go to Course: https://www.coursera.org/learn/cloud-computing-2

Introduction

## Course Review: Cloud Computing Concepts: Part 2 ### Overview In the world of technology, cloud computing has emerged as a vital component of how organizations manage their data and applications today. Coursera’s course, **Cloud Computing Concepts: Part 2**, takes a comprehensive look into the fundamental principles that power cloud systems. This course delves into the algorithms, design philosophies, and essential techniques central to effective distributed systems. From classical distributed algorithms to modern trends in data management, this course offers a thorough understanding of how cloud computing works under the hood—equipping learners with the concepts that inform cloud architecture and application design. ### Course Structure The course is structured into five weeks, each focusing on critical areas of cloud computing: #### **Week 1: Course Orientation and Classical Distributed Algorithms Continued** This week lays the foundational knowledge of leader election algorithms, such as the Ring and Bully algorithms. It also introduces students to Google’s Chubby and Apache Zookeeper, two critical tools in leader election processes. Understanding **mutual exclusion** is essential for maintaining correctness in distributed systems, and this week covers classical algorithms like the Ricart-Agrawala and Maekawa algorithms, as well as practical applications through Google’s Chubby. #### **Week 2: Concurrency and Replication Control** Here, students dive into the mechanics of transactions, learning about Remote Procedure Calls (RPCs) and the crucial concepts of optimistic and pessimistic concurrency control, alongside techniques for deadlock avoidance. The replication of data for availability is explored in-depth, providing insights into how distributed systems maintain operations effectively. #### **Week 3: Emerging Paradigms** The third week introduces the exciting domain of **stream processing** and its architectural aspects through tools like Apache Storm. It also touches on how to handle large graph data within cloud systems, leading to discussions about natural and artificial networks. This week culminates with classical scheduling algorithms and their adaptations for platforms like Hadoop. #### **Week 4: Classical Systems** Students learn about distributed file systems, such as NFS and AFS, and how they operate over the network. The course further examines Distributed Shared Memory systems and sensor networks, elaborating on their functionalities and challenges. #### **Week 5: Real-Life Behaviors** The final week focuses on security concepts within distributed systems, covering fundamental aspects like encryption, authentication, and authorization. Case studies of datacenter outages provide practical lessons, reinforcing the importance of robust cloud architectures. ### Strengths of the Course 1. **Comprehensive Curriculum**: The course content is well-structured, moving from basic to advanced topics, making it suitable for both beginners and those with some grounding in cloud computing. 2. **Practical Insights**: The use of real-world examples, especially in the final week, allows students to connect theoretical concepts to practical applications, enhancing understanding. 3. **Diverse Learning Materials**: The course employs a mix of lectures, reading materials, and case studies, catering to various learning preferences. 4. **Strong Focus on Distributed Systems**: Given that many cloud solutions rely on distributed systems, the course's emphasis on this area is highly relevant and beneficial for learners aiming to specialize in cloud computing. ### Areas for Improvement - **Pacing**: Some learners may find certain topics complex and could benefit from additional resources or extended support. - **Hands-On Exercises**: While the course is rich in theoretical knowledge, incorporating hands-on labs or projects could deepen understanding and facilitate practical skills. ### Recommendation **Cloud Computing Concepts: Part 2** is a highly recommended course for anyone looking to advance their knowledge of cloud technologies and distributed systems. Whether you're a student, a mid-career professional, or someone looking to transition into the cloud computing field, this course offers valuable insights and skills. Participants will finish the course with a solid grasp of the tools and concepts that are integral to modern cloud infrastructures, preparing them for real-world challenges. Enroll today to bolster your understanding of cloud computing and position yourself for success in this rapidly evolving field!

Syllabus

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.

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.

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.

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.

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.

Overview

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 the

Skills

Distributed Computing C++ Cloud Computing NoSQL

Reviews

The course gives an advanced overview of the distributed system. The programming assignment was hard to crack but there was a lot of learning involved.

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

This is great to understand some of the most important underlying challenges of distributed computing. I'd say this is a mind-opener for fundational knowledge about cloud computing.

Awesome class for software engineers. If you haven't take it in college, or need a refresher, this is a great way to do so.

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.