Here is something I will note for Technological Toolbox in the book “System Design Fundamentals”, but I haven’t start :)

1. Back-of-the-Envelope Math

What is the Purpose?

Do I Need to Do Math?

Types of Back-of-the-Envelope Calculations

Back-of-the-Envelope Calculation Techniques

Common Mistakes

2. API Design

Idempotency

Client vs Server Generated Data

Efficiency

Correctness

Focus on the Core

3. Schema Design

Defining Schemas

4. Indexing Strategies

What is Indexing?

Primary Index

Secondary Index

Index Use Cases

Key or Attribute Lookup

Range Lookup

Prefix Search

Composite Index

Geo Index

5. Databases

Definition

Purpose

How Do I Choose a Database?

Types of Databases

Relational Database

Document Store

Columnar Store

Object Store

Wide Column Store

Reverse Index Store

In-Memory Store

Geo-Spatial Databases

ZooKeeper

6. Real-Time Data Update

Use Case

Short Poll

Long Poll

Server-Sent Event

WebSocket

How to Pick a Protocol

How to Scale WebSockets

WebSocket Load Balancer

Is Connection Still Alive?

7. Concurrency Control and Transaction

Definition

Purpose and Examples

Single Thread

Single Thread Micro Batch

Partition Into Multiple Serial Processing

Pessimistic Locking

Optimistic Locking

Change Product Requirement to Simplify

How to Pick a Concurrency Strategy

8. Replication

Definition

Purpose and Examples

Leader-Follower Replication

Leader-Leader Replication

Leaderless Replication

How to Pick a Replication Strategy

What Should Be My Replication Factor?

9. Sharding Strategies

Definition

Purpose and Examples

Vertical Sharding

Horizontal Sharding

Hash Key

Range Key

Other Data Structures

Outlier Keys

Geo-Shards

Sharding Considerations

Making the Final Recommendation

10. Cache Strategies

Definition

Purpose and Examples

Improve Latency

Improve Throughput

Improve Bandwidth

Cache Considerations

Cache Hit Rate

What Are You Caching?

Write to Cache

Cache Invalidation

Cache Eviction

Failure Scenario and Redundancy

Data Structure

Thundering Herd

11. Asynchronous Processing

Definition

Purpose

Synchronous and Asynchronous

Reasons for Asynchronous Processing

The Nature of the Job is Asynchronous

The Processing Time is Indeterministic

The Processing Time is Long-Running

Improve Perceived Latency

12. Batch Processing

Purpose

Build Reverse Index for Search

Word Count for Document

Considerations

13. Stream Processing

Purpose

System is Down

Late and Out of Order Events

Watermark

Checkpointing

Batch Size

14. Lambda Architecture

Batch vs Stream Processing

Data is Enormous

Compute Intensive

Complexity of Streaming

Use Case

Lambda Architecture

15. Queue

Message Queue

Publisher Subscriber

Delivery Semantics and Guarantees

Custom Queue

16. Conflict Resolution

Last Write Wins

Conflict-Free Replicated Data Type (CRDT)

Keep Records of the Conflict

Custom Conflict Resolution

17. Security

API Security Considerations

Man in the Middle Attack

Authentication

18. Timeout

19. Exponential Backoff

20. Buffering

21. Sampling

22. ID Generator

UUID

Auto Increment

Auto Increment Multiple Machines

Strongly Consistent and Fault Tolerant

Distributed Roughly Sorted ID

Offline Generation

Custom ID

23. Compression

Lossless vs Lossy

Compression Efficiency

Quality of File

Computing Time to Compress a File

Compatibility of Devices

Compressed File Usage

24. Pass Only Needed Data

Filtering

Pass Chunk Delta with Rsync

25. Fail to Open

26. Distributed Transaction

Money Transfer

Blob Storage and Metadata Storage

Third Party Data Source

Database and Queue

Cache and Storage Update

Abstract Design Choices

27. Cold Storage

28. Networking

IP and Port

Domain Name System (DNS)

How to Route to the Closest Region

OSI Model

29. API Gateway

30. Content Delivery Network

Improve Latency

Reduce Bandwidth

Better Availability with Redundancy

CDN Considerations

31. Monitoring

Latency

QPS

Error Rate

Storage

Metrics Count

32. Full-Text Search

Text to Token Path

Normalize Step

Tokenize Step

Remove Stop Words Step

Stemming

Indexing

N-Gram

Search Query

Ranking

Data Source and Indexing Pipeline

33. Service Discovery and Request Routing

Load Balancing

Shard Discovery

34. Product Solutions