Understanding Distributed Systems: What every developer should know about large distributed applications

Understanding Distributed Systems
Copyright
About the author
Acknowledgements
Preface
	0.1 Who should read this book
1 Introduction
	1.1 Communication
	1.2 Coordination
	1.3 Scalability
	1.4 Resiliency
	1.5 Operations
	1.6 Anatomy of a distributed system
(PART) Communication
Introduction
2 Reliable links
	2.1 Reliability
	2.2 Connection lifecycle
	2.3 Flow control
	2.4 Congestion control
	2.5 Custom protocols
3 Secure links
	3.1 Encryption
	3.2 Authentication
	3.3 Integrity
	3.4 Handshake
4 Discovery
5 APIs
	5.1 HTTP
	5.2 Resources
	5.3 Request methods
	5.4 Response status codes
	5.5 OpenAPI
	5.6 Evolution
(PART) Coordination
Introduction
6 System models
7 Failure detection
8 Time
	8.1 Physical clocks
	8.2 Logical clocks
	8.3 Vector clocks
9 Leader election
	9.1 Raft leader election
	9.2 Practical considerations
10 Replication
	10.1 State machine replication
	10.2 Consensus
	10.3 Consistency models
		10.3.1 Strong consistency
		10.3.2 Sequential consistency
		10.3.3 Eventual consistency
		10.3.4 CAP theorem
	10.4 Practical considerations
11 Transactions
	11.1 ACID
	11.2 Isolation
		11.2.1 Concurrency control
	11.3 Atomicity
		11.3.1 Two-phase commit
	11.4 Asynchronous transactions
		11.4.1 Log-based transactions
		11.4.2 Sagas
		11.4.3 Isolation
(PART) Scalability
Introduction
12 Functional decomposition
	12.1 Microservices
		12.1.1 Benefits
		12.1.2 Costs
		12.1.3 Practical considerations
	12.2 API gateway
		12.2.1 Routing
		12.2.2 Composition
		12.2.3 Translation
		12.2.4 Cross-cutting concerns
		12.2.5 Caveats
	12.3 CQRS
	12.4 Messaging
		12.4.1 Guarantees
		12.4.2 Exactly-once processing
		12.4.3 Failures
		12.4.4 Backlogs
		12.4.5 Fault isolation
		12.4.6 Reference plus blob
13 Partitioning
	13.1 Sharding strategies
		13.1.1 Range partitioning
		13.1.2 Hash partitioning
	13.2 Rebalancing
		13.2.1 Static partitioning
		13.2.2 Dynamic partitioning
		13.2.3 Practical considerations
14 Duplication
	14.1 Network load balancing
		14.1.1 DNS load balancing
		14.1.2 Transport layer load balancing
		14.1.3 Application layer load balancing
		14.1.4 Geo load balancing
	14.2 Replication
		14.2.1 Single leader replication
		14.2.2 Multi-leader replication
		14.2.3 Leaderless replication
	14.3 Caching
		14.3.1 Policies
		14.3.2 In-process cache
		14.3.3 Out-of-process cache
(PART) Resiliency
Introduction
15 Common failure causes
	15.1 Single point of failure
	15.2 Unreliable network
	15.3 Slow processes
	15.4 Unexpected load
	15.5 Cascading failures
	15.6 Risk management
16 Downstream resiliency
	16.1 Timeout
	16.2 Retry
		16.2.1 Exponential backoff
		16.2.2 Retry amplification
	16.3 Circuit breaker
		16.3.1 State machine
17 Upstream resiliency
	17.1 Load shedding
	17.2 Load leveling
	17.3 Rate-limiting
		17.3.1 Single-process implementation
		17.3.2 Distributed implementation
	17.4 Bulkhead
	17.5 Health endpoint
		17.5.1 Health checks
	17.6 Watchdog
(PART) Testing and operations
Introduction
18 Testing
	18.1 Scope
	18.2 Size
	18.3 Practical considerations
19 Continuous delivery and deployment
	19.1 Review and build
	19.2 Pre-production
	19.3 Production
	19.4 Rollbacks
20 Monitoring
	20.1 Metrics
	20.2 Service-level indicators
	20.3 Service-level objectives
	20.4 Alerts
	20.5 Dashboards
		20.5.1 Best practices
	20.6 On-call
21 Observability
	21.1 Logs
	21.2 Traces
	21.3 Putting it all together
22 Final words