System Design Good Practices Library

Core principles, quality attributes, trade-off analysis, ADRs, and reference architectures that underpin every system design decision.

Monolith, microservices, event-driven, hexagonal, CQRS, event sourcing, serverless, and more — with deep comparisons and when to apply each.

Sagas, consensus algorithms, distributed locking, leader election, vector clocks, and partition tolerance for multi-node architectures.

Request-response, pub/sub, message queues, event streaming, webhooks, fan-out, and brokered integration patterns.

Retries, circuit breakers, bulkheads, dead letter queues, chaos engineering, and exactly-once delivery semantics.

Horizontal and vertical scaling, caching strategies, sharding, rate limiting, connection pooling, and materialized views.

REST, GraphQL, gRPC, API versioning, gateways, BFF pattern, OpenAPI, pagination, idempotency keys, and contract testing.

ESB, canonical data models, anti-corruption layers, CDC, ETL/ELT, orchestration vs choreography, and file-based integration.

Relational, NoSQL, document, graph, and time-series databases. Data lakes, warehouses, lakehouses, and schema evolution.

Full-text search, relevance ranking, faceted search, semantic search, vector search, and hybrid retrieval architectures.

Authentication, authorization, zero trust, OAuth2, secrets management, encryption, WAF, supply chain security, and compliance.

Logging, metrics, tracing, alerting, SLOs, dashboards, runbooks, incident management, and feature flags.

CI/CD, blue-green, canary, rolling, progressive delivery, IaC, GitOps, database migrations, and rollback strategies.

Landing zones, multi-region, active-active/passive, cloud networking, service mesh, Kubernetes, FinOps, and autoscaling.

Internal developer platforms, golden paths, self-service infrastructure, service catalogs, and policy as code.

Clean architecture, DDD, SOLID, TDD/BDD, contract testing, refactoring strategy, code review standards, and dependency management.

MVC/MVP/MVVM, offline-first, sync engines, push notifications, mobile API design, and app lifecycle management.

Device identity, telemetry ingestion, edge processing, device management, and IoT protocol selection.

Batch processing, stream processing, data pipelines, data quality, BI/reporting, feature stores, and lakehouse governance.

Model training pipelines, model serving, RAG architecture, vector databases, prompt management, AI guardrails, and observability.

Technology standards, exception management, architecture review boards, documentation standards, and risk management.

Common architectural mistakes — distributed monoliths, big ball of mud, chatty services, premature optimization, and more.

Structured comparisons for common architectural choices: SQL vs NoSQL, REST vs GraphQL, monolith vs microservices, and more.

ADR templates, system design review checklists, production readiness checklists, threat modeling templates, and more.