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Architecting Production Systems

Course Contents

From Design to Production

Client-Server to N-Tier

The Monolith (and When It's Right)

Microservices — and When to Split

Event-Driven Architecture & P2P

Choosing a Style: The Rubric

Checkpoint: Architecture Styles

Service Discovery

API Gateway & BFF

Sidecar & Service Mesh

Externalized Configuration

Strangler Fig & Anti-Corruption Layer

Database per Service

Saga: Orchestration vs Choreography

Checkpoint: Microservices Patterns

VMs vs Containers

Kubernetes: The 20% That Matters

Autoscaling Policies

EC2 vs EKS vs Lambda: The Decision

Multi-Cloud: The Reality Check

Codelab: Containerize & Deploy to K8s

Checkpoint: Compute & Orchestration

Batch vs Stream

MapReduce & Its Descendants

ETL vs ELT & Data Pipelines

Lakes, Warehouses, Lakehouse

Lambda vs Kappa Architecture

Streaming Engines

Windowing & Exactly-Once

Counting at Scale & Top-K

Checkpoint: Big Data & Streaming

CI/CD for Systems

Rolling, Blue-Green, Canary

A/B Testing Infrastructure

Schema Migrations: Expand-Contract

Zero-Downtime Data Migrations

Rollback Strategy

Codelab: Canary Rollout

Checkpoint: Deployment & Evolution

The Three Pillars

Structured Logging & Aggregation

Correlation IDs

Metrics & Cardinality

Distributed Tracing

Alerts & Runbooks in Practice

Observability-Driven Debugging

Codelab: Distributed Tracing

Checkpoint: Observability

TLS & mTLS in Architecture

Encryption at Rest & Secrets Management

RBAC & Zero Trust

DDoS & Abuse Protection

Capacity Planning

Cloud Cost Engineering

Cost-Aware Design Review

The Production-Readiness Checklist

Checkpoint: Security & Cost

Capstone Pass 4: The Marketplace Goes to Production

Lakes, Warehouses, Lakehouse

Lakes, Warehouses, Lakehouse | CodePeet