Distributed Systems for practitioners
Learn the basic principles that govern how distributed systems work and how you can design your systems for increased performance, availability and scalability. Understand the basic algorithms and protocols used to solve the most common problems in the space of distributed systems.
About
About the Book
Distributed systems are everywhere nowadays, from the chat applications we use to communicate with our friends to the online stores we use for our shopping. However, distributed systems are by nature complicated. In order to design and build a distributed system that will work properly, one has to understand a lot of different concepts and nuances and the literature of distributed systems can be quite big and chaotic at times.
This book makes an effort to collate the basic principles, algorithms and protocols in the field of distributed systems. It introduces the basic problems that are inherent in distributed systems, the main approaches to tackle them and any associated complications one needs to keep in mind. You will have the chance to get an overview of the seminal papers in the field, while also understanding how the associated algorithms and protocols can be used in real life. As implied by the title, the goal of this book is to maintain a practical perspective, by explaining algorithms in the simplest terms possible and demonstrating how implementations of them can be used in real systems.
Who is this book for
This book is aimed at software engineers that have some experience in building software systems and have no or some experience in distributed systems. It assumes no knowledge around concepts and algorithms for distributed systems. This book attempts to gradually introduce the terms and explain the basic algorithms in the simplest way possible, providing many diagrams and examples. As a result, this book can also be useful to people that don't develop software, but want to get an introduction to the field of distributed systems.
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Author
About the Author
Dimos Raptis
Dimos is a software engineer who has been designing, building and operating software systems over the last decade. He holds an MEng in Electrical and Computer Engineering from the National Technical University of Athens and an MSc in Software Engineering from Imperial College London. His endless curiosity usually leads him down big rabbit holes and when he's lucky, he re-emerges with a big bucket of knowledge. When he finds some time, he enjoys sharing this knowledge with others either through his blog or by writing books. He's the author of the books Distributed Systems for Practitioners and Computer Science for kids.
Contents
Table of Contents
Introduction
What is a distributed system and why we need it
The fallacies of distributed computing
Why distributed systems are hard
Correctness in distributed systems
System models
The tale of exactly-once semantics
Failure in the world of distributed systems
Stateful and Stateless systems
Basic concepts and theorems
Partitioning
Algorithms for horizontal partitioning
Replication
Single-master replication
Multi-master replication
Quorums in distributed systems
Safety guarantees in distributed systems
ACID transactions
The CAP Theorem
Consistency models
Isolation Levels
Consistency and Isolation - Differences and Similarities
Why all the formalities
Distributed Transactions
What is a distributed transaction
Achieving Isolation
2-phase locking (2PL)
Optimistic concurrency control (OCC)
Multi-version concurrency control (MVCC)
Achieving atomicity
2-phase commit (2PC)
3-phase commit (3PC)
A quorum-based commit protocol
How it all fits together
Long-lived transactions & Sagas
Consensus
Defining consensus
Some use-cases of consensus
FLP impossibility
The Paxos algorithm
Intricacies of Paxos
Paxos in real-life
Replicated state machine via consensus
Distributed transactions via consensus
Raft
Standing on the shoulders of giants
Time
What is different in a distributed system
A practical perspective
A theoretical perspective
Logical clocks
Order
Total and partial ordering
The concept of causality
Lamport clocks
Vector clocks
Version vectors & Dotted version vectors
Distributed snapshots
Physical & Logical time: closing thoughts
Networking
The physical layer
The link layer
The network layer
The transport layer
The application layer
Taking a step back
Security
Authentication
Confidentiality
Integrity
A cryptography primer
Example protocols
Case studies
Distributed file systems (HDFS/GFS)
Distributed coordination service (Zookeeper/Chubby/etcd)
Distributed datastores
BigTable/HBase
Cassandra
Spanner
FaunaDB
Distributed messaging system (Kafka)
Distributed cluster management (Kubernetes)
Distributed ledger (Corda)
Distributed data processing systems
MapReduce
Apache Spark
Apache Flink
Practices & Patterns
Communication Patterns
Coordination Patterns
Data synchronisation
Shared-nothing architectures
Distributed locking
Compatibility patterns
Dealing with failure
Distributed tracing
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Causes
Causes Supported
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