Mastering Distributed Computing: A Comprehensive Guide to Learn Distributed Computing

✍ Scribed by Hermans, Kris; Ltd, Cybellium

• Publisher: Cybellium
• Year: 2023
• Tongue: English
• Leaves: 187
• Category: Library

✦ Synopsis

Uncover the Art of Seamless Distributed Computing with "Mastering Distributed Computing"

In the dynamic realm of modern computing, the ability to harness the power of distributed systems is paramount. "Mastering Distributed Computing" is your definitive guide to mastering the art of seamlessly orchestrating distributed resources for optimal performance and scalability. Whether you're an experienced software engineer or a newcomer to the world of distributed computing, this book equips you with the knowledge and skills needed to navigate the intricacies of distributed systems.

About the Book

"Mastering Distributed Computing" takes you on an enlightening journey through the intricacies of distributed computing, from foundational concepts to advanced techniques. From distributed architectures to consensus algorithms, this book covers it all. Each chapter is meticulously designed to provide both a deep understanding of the concepts and practical applications in real-world scenarios.

Key Features

Foundational Principles: Build a strong foundation by understanding the core principles of distributed systems, including scalability, fault tolerance, and data consistency.

Distributed Architectures: Explore a range of distributed architectures, including client-server, peer-to-peer, microservices, and serverless, understanding their strengths and applications.

Consistency and Replication: Dive into the complexities of data consistency and replication strategies, including eventual consistency, strong consistency, and distributed databases.

Distributed Algorithms: Master fundamental distributed algorithms, such as leader election, distributed locking, and distributed transactions, for coordinating actions across nodes.

Scaling Strategies: Discover strategies for scaling distributed systems horizontally and vertically, ensuring optimal performance as workloads grow.

Fault Tolerance: Understand mechanisms for building fault-tolerant systems, including redundancy,
…

✦ Table of Contents

1. The Foundations of Distributed Computing
   1.1. Understanding the Concepts of Distribution and Concurrency
   1.2. The Evolution of Distributed Systems
   1.3. Importance of Distributed Computing in Modern Applications
2. Challenges and Benefits of Distributed Computing
   2.1. Scalability, Fault Tolerance, and High Availability
   2.2. Balancing Performance and Consistency
   2.3. The Business Case for Distributed Computing
3. Architectural Models for Distributed Systems
   3.1. Client-Server Architecture and Variations
   3.2. Peer-to-Peer Networks and Decentralized Systems
   3.3. Microservices and Containerization in Distributed Systems
4. Communication Protocols and Middleware
   4.1. Message Passing and Remote Procedure Call (RPC)
   4.2. Publish-Subscribe and Event-Driven Communication
   4.3. Middleware Technologies for Distributed Computing
5. Distributed Data Storage Models
   5.1. Replication and Consistency Models
   5.2. Partitioning and Sharding Strategies
   5.3. Trade-offs in Data Distribution and Storage
6. Distributed Databases and NoSQL Systems
   6.1. Relational vs. NoSQL Databases in Distributed Environments
   6.2. CAP Theorem and Database Design Considerations
   6.3. Scaling and Performance Tuning of Distributed Databases
7. Parallel and Distributed Computing Paradigms
   7.1. Shared Memory vs. Message Passing Models
   7.2. Parallel Algorithms and MapReduce Framework
   7.3. Bulk Synchronous Parallel (BSP) Computing
8. Cloud Computing and Virtualization
   8.1. Infrastructure as a Service (IaaS), Platform as a Service (PaaS)
   8.2. Virtual Machines and Containerization Technologies
   8.3. Orchestrating Distributed Applications in the Cloud
9. Consistency Models in Distributed Systems
   9.1. Strong vs. Eventual Consistency
   9.2. CAP Theorem and Consistency Trade-offs
   9.3. Implementing Consistency in Distributed Databases
10. Replication and Fault Tolerance Strategies
    10.1. Active-Active and Active-Passive Replication
    10.2. Techniques for Detecting and Handling Failures
    10.3. Checkpointing and Recovery Mechanisms
11. Event Sourcing and CQRS
    11.1. Event Sourcing as a Data Storage Pattern
    11.2. Command Query Responsibility Segregation (CQRS)
    11.3. Implementing Event Sourcing and CQRS in Distributed Systems
12. Microservices Architecture and Orchestration
    12.1. Principles of Microservices Architecture
    12.2. Service Discovery and Load Balancing
    12.3. Container Orchestration with Kubernetes
13. Security Challenges in Distributed Systems
    13.1. Authentication, Authorization, and Encryption
    13.2. Denial of Service (DoS) Attacks and Prevention
    13.3. Protecting Data in Transit and at Rest
14. Privacy and Ethical Considerations in Distributed Computing
    14.1. Data Privacy Regulations and Compliance
    14.2. Ethical Implications of Data Collection and Processing
    14.3. Balancing Privacy and Innovation in Distributed Systems
15. Emerging Technologies in Distributed Computing
    15.1. Blockchain and Decentralized Applications (DApps)
    15.2. Edge Computing and IoT Integration
    15.3. Quantum Computing and Distributed Algorithms
16. The Future of Distributed Computing
    16.1. Trends Shaping the Future of Distributed Systems
    16.2. Challenges and Opportunities in Distributed Computing
    16.3. Preparing for the Next Generation of Distributed Applications
17. Appendix
    17.1. Glossary of Key Terms
    17.2. Distributed Computing Specifications
    17.3. Additional Resources and References
    17.4. About the author