System-Design

A practical guide to using TLA+ for designing fault‑tolerant systems, covering theory, tooling, and real‑world examples.

Table of Contents Introduction The Problem Space: Why Simple Hashing Fails at Scale Fundamentals of Consistent Hashing 3.1 The Ring Metaphor 3.2 Virtual Nodes (VNodes) 3.3 Hash Functions and Their Role Designing a Consistent Hashing Library from Scratch 4.1 Choosing a Language: Go Example 4.2 Core Data Structures 4.3 Adding & Removing Nodes 4.4 Key Lookup Logic 4.5 Putting It All Together Integrating Consistent Hashing into Real Systems 5.1 Distributed Caching (e.g., Memcached, Redis Cluster) 5.2 NoSQL Databases (Cassandra, DynamoDB) 5.3 Content Delivery Networks (CDNs) and Edge Routing Handling Node Dynamics: Scaling Up & Down Gracefully 6.1 Data Migration Strategies 6.2 Replication & Fault Tolerance Advanced Variants and Optimizations 7.1 Rendezvous (Highest Random Weight) Hashing 7.2 Weighted Nodes & Capacity‑Based Distribution 7.3 Multi‑Probe & Jump Consistent Hashing Performance Considerations & Benchmarks Best Practices, Common Pitfalls, and Gotchas 10 Real‑World Case Studies 10.1 Amazon Dynamo’s Ring Architecture 10.2 Apache Cassandra’s Token Allocation 10.3 Netflix’s EVCache 11 Conclusion 12 Resources Introduction Scalable distributed systems are the backbone of modern web services, from massive key‑value stores to globally replicated caches and content‑delivery networks. One of the most recurring challenges in these environments is load balancing—distributing client requests or data partitions evenly across a dynamic set of nodes while minimizing data movement when the cluster topology changes. ...

Table of Contents Introduction Core Concepts of Payment Processing 2.1 Stakeholders & Actors 2.2 Typical Transaction Flow High‑Level Architecture 3.1 Gateway Layer 3.2 Core Processing Engine 3.3 Risk & Fraud Management 3.4 Settlement & Reconciliation 3.5 Reporting & Analytics Data Modeling & Persistence API Design for Payments 5.1 REST vs. gRPC vs. GraphQL 5.2 Idempotency & Retry Strategies 5.3 Versioning & Extensibility Security & Compliance 6.1 PCI‑DSS Requirements 6.2 Tokenization & Encryption 6.3 Authentication & Authorization Scalability & High Availability 7.1 Horizontal Scaling & Sharding 7.2 Circuit Breakers & Bulkheads 7.3 Event‑Driven Architecture & Messaging Observability & Monitoring Real‑World Example: Building a Minimal Payments API in Python Conclusion Resources Introduction Payments are the lifeblood of any digital commerce platform. Whether you’re building a marketplace, a subscription SaaS, or a fintech startup, the reliability, security, and performance of your payment system directly affect user trust and revenue. Designing a payments system is far more than wiring a credit‑card form to a processor; it is a complex orchestration of network protocols, regulatory compliance, fraud detection, and high‑throughput data pipelines. ...

Table of Contents Introduction The Three Core Challenges of Large-Scale Payment Processing Security: Protecting Sensitive Financial Data Disbursement: Splitting Payments Across Multiple Parties Reliability: Managing External Dependencies Uber’s Unified Checkout Architecture High-Throughput Account Processing Risk Management and Fraud Detection Lessons for Building Your Own Payment System The Future of Payment System Design Resources Introduction In October 2014, a woman named Maria faced a common problem in Prague: she needed a ride but didn’t have cash. She opened the Uber app, requested a ride, and within minutes, a driver arrived. The transaction processed seamlessly—or so it seemed. Behind that simple tap on a smartphone lay an intricate system handling security protocols, fraud detection, multiple payment methods, regulatory compliance, and real-time fund transfers across international borders. ...

Table of Contents Introduction The Scale Problem: Understanding Video Infrastructure Core Architectural Principles Data Flow and Storage Strategy The Transcoding Pipeline: Format Transformation at Scale Content Delivery Networks and Global Distribution Handling Read-Heavy Workloads with Caching Database Architecture for Video Metadata Real-Time Streaming and Latency Optimization Reliability and Fault Tolerance Practical Design Considerations Conclusion Resources Introduction Every minute, creators upload over 500 hours of video content to the internet. Billions of users stream video daily across devices ranging from smartwatches to 4K televisions. Behind this seemingly simple act of watching a video lies one of the most complex engineering challenges in modern software architecture. ...