System Design Learning Hub

High‑Level Design (HLD)

How it works

HLD Overview
How it works
  1. Define components and data paths
  2. Select technologies and SLAs
  3. Plan deployment and scaling
  4. Document risks and mitigations

🧱 What HLD Covers

🏗️

Architecture

  • Core services, data stores, and request/data flows
  • Clear module boundaries and ownership
  • Interfaces between components and external systems
🧩

Technology & Deployment

  • Languages, frameworks, databases, messaging
  • Regions, networks, scaling units, and topology
  • Security, compliance, and data residency constraints
📊

Non‑functional Goals

  • Latency SLOs, throughput targets, and cost bounds
  • Availability, reliability, and consistency trade‑offs
  • Capacity assumptions and growth projections

⚖️ HLD vs. LLD

🧭

HLD

What the system is and where it runs.

  • Architectural choices and trade‑offs (C/A/C, latency, cost)
  • Service boundaries and contracts, data flows, deployment
🧰

LLD

How each component is implemented.

  • APIs, classes, data structures, and algorithms
  • Error handling, validation, and persistence details

🚀 Steps to a Scalable HLD

1

📋 Requirements & Constraints

Functional goals plus non‑functional SLOs (latency, availability, throughput).

2

📏 Capacity Estimation

Traffic projections, storage growth, read/write ratio, and peak patterns.

3

🔌 Interfaces & Protocols

HTTP/HTTPS methods, WebSockets or SSE for realtime, long polling when needed.

4

⚖️ Resiliency & Limits

Rate limiting, retries/timeouts, circuit breakers, redundancy, and failover.

5

⚡ Performance Levers

CDN, caching layers, pagination, async processing with queues, load balancing.

6

🔭 Observability

Structured logging, metrics and tracing, health checks, alerting.

📦 HLD Deliverables

  • Context, component, and deployment diagrams with data paths
  • Interface contracts (APIs) and operational SLAs
  • Capacity/scaling plan and dependency map
  • Risk list with mitigation: hotspots, single‑points‑of‑failure, fallbacks

🔗 Continue Learning

Scalability

Vertical vs horizontal scaling, autoscaling, bottleneck analysis

Availability

Redundancy, load balancing, multi‑region deployments

Consistency

Strong vs eventual consistency and consensus patterns

Load Balancing

Algorithms, health checks, and session management

Caching

Cache layers and patterns: cache‑aside, write‑through, TTLs

CDN

Latency reduction and global distribution for static assets

Message Queues

Asynchronous processing and decoupling with brokers

Microservices

Service boundaries, data ownership, and reliability patterns