Chapter 4: Infrastructure Architecture Principles
Learning Objectives
After completing this chapter, you will be able to:
- Apply core infrastructure architecture principles to design decisions
- Select appropriate design patterns for different requirements
- Create reference architectures for common scenarios
- Document architecture decisions using Architecture Decision Records (ADRs)
- Conduct effective architecture reviews
- Design scalable, reliable, and secure infrastructure
- Apply the Well-Architected Framework to infrastructure design
Introduction
Infrastructure architecture provides the blueprint for building and operating IT systems. Good architecture enables scalability, reliability, security, and cost efficiency. Poor architecture creates technical debt that constrains future options, increases operational burden, and fails to meet business needs.
This chapter establishes the architectural principles and patterns that guide infrastructure design decisions. These principles apply whether you’re building in the cloud, on-premises, or in hybrid environments.
The Role of Infrastructure Architecture
Architecture Definition
Infrastructure architecture defines the structure of IT infrastructure including:
- Physical and logical components
- Relationships between components
- Principles guiding design decisions
- Standards and patterns to follow
Architecture Goals
| Goal | Description | Measures |
|---|---|---|
| Reliability | Systems work correctly and consistently | Availability, error rates |
| Scalability | Handle growing workloads | Throughput, response times under load |
| Security | Protect against threats | Vulnerabilities, incidents |
| Performance | Meet response time requirements | Latency, throughput |
| Cost Efficiency | Optimize spending | Cost per transaction, utilization |
| Maintainability | Easy to operate and change | Change success rate, time to deploy |
| Compliance | Meet regulatory requirements | Audit findings, compliance scores |
Architecture Levels
┌─────────────────────────────────────────────────────────────────────────────┐
│ INFRASTRUCTURE ARCHITECTURE LEVELS │
├─────────────────────────────────────────────────────────────────────────────┤
│ │
│ ┌─────────────────────────────────────────────────────────────────────┐ │
│ │ ENTERPRISE ARCHITECTURE │ │
│ │ Business capability alignment, portfolio management │ │
│ └─────────────────────────────────────────────────────────────────────┘ │
│ │ │
│ ▼ │
│ ┌─────────────────────────────────────────────────────────────────────┐ │
│ │ SOLUTION ARCHITECTURE │ │
│ │ Application design, service integration, data flows │ │
│ └─────────────────────────────────────────────────────────────────────┘ │
│ │ │
│ ▼ │
│ ┌─────────────────────────────────────────────────────────────────────┐ │
│ │ INFRASTRUCTURE ARCHITECTURE │ │
│ │ Compute, network, storage, security, platforms │ │
│ └─────────────────────────────────────────────────────────────────────┘ │
│ │ │
│ ▼ │
│ ┌─────────────────────────────────────────────────────────────────────┐ │
│ │ DETAILED DESIGN │ │
│ │ Component specifications, configurations, implementations │ │
│ └─────────────────────────────────────────────────────────────────────┘ │
│ │
└─────────────────────────────────────────────────────────────────────────────┘
Core Architecture Principles
Principle 1: Design for Failure
Statement: Assume components will fail. Design systems to continue operating despite failures.
Rationale: No component is 100% reliable. Hardware fails, software has bugs, networks partition, humans make mistakes. Systems must be designed to handle these failures gracefully.
| Guidance | Implementation | Example |
|---|---|---|
| Eliminate single points of failure | Redundant components, multiple availability zones | Active-active database across AZs |
| Implement graceful degradation | Fallback modes, circuit breakers | Return cached data when API unavailable |
| Automate recovery | Auto-healing, automatic failover | Kubernetes pod restart on failure |
| Test failure scenarios | Chaos engineering, DR testing | Regularly simulate AZ failures |
| Blast radius containment | Isolation, bulkheads | Separate failure domains |
Anti-patterns to Avoid:
- Single database without replication
- Single network path
- Monolithic applications without circuit breakers
- Untested disaster recovery plans
Principle 2: Design for Scale
Statement: Build infrastructure that can grow (and shrink) with demand efficiently.
Rationale: Business needs change. Workloads grow. Peak demand exceeds average. Infrastructure must scale without redesign.
| Guidance | Implementation | Example |
|---|---|---|
| Use horizontal scaling | Add instances rather than larger instances | Auto-scaling groups |
| Implement auto-scaling | Scale based on metrics | Scale on CPU > 70% |
| Design stateless where possible | Enable instance replacement | Session state in Redis |
| Decouple components | Allow independent scaling | Separate web and app tiers |
| Use asynchronous processing | Queue work for processing | Message queues for background jobs |
Scaling Strategies:
| Strategy | Description | Use Case |
|---|---|---|
| Vertical Scaling | Larger instances | Limited options, legacy apps |
| Horizontal Scaling | More instances | Modern, stateless apps |
| Auto-scaling | Automatic adjustment | Variable workloads |
| Pre-scaling | Scale before known demand | Scheduled events |
| Geographic Scaling | Multiple regions | Global user base |
Principle 3: Secure by Default
Statement: Security is foundational, not an afterthought. Every design decision considers security implications.
Rationale: Security breaches are costly and damaging. Retrofitting security is expensive and incomplete. Security must be built in from the start.
| Guidance | Implementation | Example |
|---|---|---|
| Apply least privilege | Minimum necessary permissions | IAM roles with specific policies |
| Encrypt everything | Data at rest and in transit | TLS, KMS encryption |
| Defense in depth | Multiple security layers | WAF + security groups + NACLs |
| Automate security | Security as code | Security scanning in CI/CD |
| Zero trust | Verify explicitly, never trust | Identity-based access |
Security Controls by Layer:
┌─────────────────────────────────────────────────────────────────────────────┐
│ DEFENSE IN DEPTH │
├─────────────────────────────────────────────────────────────────────────────┤
│ │
│ ┌─────────────────────────────────────────────────────────────────────┐ │
│ │ PERIMETER: DDoS protection, WAF, Edge security │ │
│ └─────────────────────────────────────────────────────────────────────┘ │
│ ┌─────────────────────────────────────────────────────────────────────┐ │
│ │ NETWORK: Segmentation, NACLs, Security Groups, VPN, Private Link │ │
│ └─────────────────────────────────────────────────────────────────────┘ │
│ ┌─────────────────────────────────────────────────────────────────────┐ │
│ │ IDENTITY: IAM, MFA, SSO, PAM, Conditional Access │ │
│ └─────────────────────────────────────────────────────────────────────┘ │
│ ┌─────────────────────────────────────────────────────────────────────┐ │
│ │ COMPUTE: Hardened images, patching, endpoint protection │ │
│ └─────────────────────────────────────────────────────────────────────┘ │
│ ┌─────────────────────────────────────────────────────────────────────┐ │
│ │ APPLICATION: Code scanning, runtime protection, API security │ │
│ └─────────────────────────────────────────────────────────────────────┘ │
│ ┌─────────────────────────────────────────────────────────────────────┐ │
│ │ DATA: Encryption, DLP, classification, access controls │ │
│ └─────────────────────────────────────────────────────────────────────┘ │
│ │
└─────────────────────────────────────────────────────────────────────────────┘
Principle 4: Automate Everything
Statement: Manual processes don’t scale, introduce errors, and slow delivery. Automation is the default.
Rationale: Humans make mistakes, especially under pressure. Manual processes create bottlenecks. Automation enables consistency, speed, and auditability.
| Guidance | Implementation | Example |
|---|---|---|
| Infrastructure as Code | Define infrastructure in code | Terraform modules |
| Configuration as Code | Manage configuration in code | Ansible playbooks |
| Policy as Code | Define policies in code | OPA/Rego policies |
| Testing as Code | Automated validation | Terratest, InSpec |
| Documentation as Code | Generate from code | Terraform-docs |
Automation Hierarchy:
| Level | Description | Tools |
|---|---|---|
| Provisioning | Create infrastructure | Terraform, CloudFormation |
| Configuration | Configure systems | Ansible, Puppet, Chef |
| Deployment | Deploy applications | ArgoCD, Spinnaker |
| Operations | Day-to-day tasks | Runbook automation |
| Remediation | Auto-fix issues | Self-healing systems |
Principle 5: Optimize for Cost
Statement: Right-size infrastructure, eliminate waste, and continuously optimize spending.
Rationale: Infrastructure costs can spiral without discipline. Every dollar spent on infrastructure is a dollar not spent on innovation.
| Guidance | Implementation | Example |
|---|---|---|
| Right-size resources | Match capacity to demand | Use m5.large not m5.xlarge |
| Use appropriate tiers | Select cost-effective options | gp3 instead of io2 for most workloads |
| Implement lifecycle policies | Archive and delete appropriately | S3 lifecycle rules |
| Reserve for predictable | Commit for discounts | Reserved instances, savings plans |
| Spot for flexible | Use spare capacity | Spot instances for batch |
Cost Optimization Framework:
┌─────────────────────────────────────────────────────────────────────────────┐
│ COST OPTIMIZATION FRAMEWORK │
├─────────────────────────────────────────────────────────────────────────────┤
│ │
│ ┌─────────────┐ ┌─────────────┐ ┌─────────────┐ │
│ │ INFORM │────►│ OPTIMIZE │────►│ OPERATE │ │
│ └─────────────┘ └─────────────┘ └─────────────┘ │
│ │ │ │ │
│ ▼ ▼ ▼ │
│ • Visibility • Right-sizing • Governance │
│ • Allocation • Reserved • Accountability │
│ • Forecasting • Spot/Preempt • Continuous │
│ • Benchmarking • Storage tiers • Culture │
│ │
└─────────────────────────────────────────────────────────────────────────────┘
Principle 6: Keep It Simple
Statement: Complexity is the enemy of reliability, security, and maintainability. Choose simplicity.
Rationale: Every component adds failure modes, attack surface, and operational burden. Simple systems are easier to understand, secure, and operate.
| Guidance | Implementation | Example |
|---|---|---|
| Use managed services | Reduce operational burden | RDS instead of self-managed MySQL |
| Minimize components | Each component adds risk | Do you really need that service? |
| Standardize patterns | Reduce variation | One way to do each thing |
| Document decisions | Enable understanding | ADRs for significant decisions |
| Avoid premature optimization | Build what’s needed | YAGNI principle |
Principle 7: Design for Observability
Statement: Build systems that can be understood through their external outputs.
Rationale: You cannot improve what you cannot see. Complex systems require deep visibility to operate effectively.
| Guidance | Implementation | Example |
|---|---|---|
| Instrument everything | Metrics, logs, traces | Prometheus metrics in every service |
| Correlate data | Link metrics, logs, traces | Trace IDs across systems |
| Build dashboards | Visualize system state | Grafana dashboards |
| Implement alerting | Detect problems automatically | PagerDuty integration |
| Enable exploration | Support ad-hoc analysis | Log aggregation, query tools |
Architecture Design Patterns
High Availability Pattern
Purpose: Ensure systems remain available despite component failures.
Implementation:
┌─────────────────────────────────────────────────────────────────────────────┐
│ HIGH AVAILABILITY PATTERN │
├─────────────────────────────────────────────────────────────────────────────┤
│ │
│ ┌────────────────────┐ │
│ │ Global Load │ │
│ │ Balancer │ │
│ └─────────┬──────────┘ │
│ │ │
│ ┌─────────────────┼─────────────────┐ │
│ │ │ │ │
│ ▼ ▼ ▼ │
│ ┌──────────┐ ┌──────────┐ ┌──────────┐ │
│ │ AZ-A │ │ AZ-B │ │ AZ-C │ │
│ ├──────────┤ ├──────────┤ ├──────────┤ │
│ │ ┌──────┐ │ │ ┌──────┐ │ │ ┌──────┐ │ │
│ │ │ Web │ │ │ │ Web │ │ │ │ Web │ │ │
│ │ └──┬───┘ │ │ └──┬───┘ │ │ └──┬───┘ │ │
│ │ │ │ │ │ │ │ │ │ │
│ │ ┌──▼───┐ │ │ ┌──▼───┐ │ │ ┌──▼───┐ │ │
│ │ │ App │ │ │ │ App │ │ │ │ App │ │ │
│ │ └──┬───┘ │ │ └──┬───┘ │ │ └──┬───┘ │ │
│ │ │ │ │ │ │ │ │ │ │
│ │ ┌──▼───┐ │ │ ┌──▼───┐ │ │ ┌──▼───┐ │ │
│ │ │ DB │ │ │ │ DB │ │ │ │ DB │ │ │
│ │ │(Pri) │◄┼──────┼─┤(Rep) │◄┼──────┼─┤(Rep) │ │ │
│ │ └──────┘ │ │ └──────┘ │ │ └──────┘ │ │
│ └──────────┘ └──────────┘ └──────────┘ │
│ │
│ Key Elements: │
│ • Multiple availability zones │
│ • Redundant components at each tier │
│ • Database replication │
│ • Health checks and automatic failover │
│ │
└─────────────────────────────────────────────────────────────────────────────┘
Design Considerations:
| Consideration | Recommendation |
|---|---|
| Minimum AZs | 3 for production workloads |
| Load Balancer | Application Load Balancer with health checks |
| Database | Multi-AZ with automatic failover |
| Session State | Externalize to Redis/ElastiCache |
| Health Checks | Multiple levels (network, application, business) |
N-Tier Architecture Pattern
Purpose: Separate concerns into logical tiers for independent scaling and security.
| Tier | Purpose | Components | Security |
|---|---|---|---|
| Presentation | User interface | Web servers, CDN | WAF, DDoS protection |
| Application | Business logic | App servers, APIs | Security groups, service mesh |
| Data | Data storage | Databases, caches | Encryption, access controls |
Communication Between Tiers:
| From | To | Method | Security |
|---|---|---|---|
| Presentation | Application | HTTPS/REST | TLS, authentication |
| Application | Data | Database protocol | Encryption, IAM |
| Application | Application | gRPC/REST | mTLS, service mesh |
Microservices Infrastructure Pattern
Purpose: Support distributed, independently deployable services.
┌─────────────────────────────────────────────────────────────────────────────┐
│ MICROSERVICES INFRASTRUCTURE │
├─────────────────────────────────────────────────────────────────────────────┤
│ │
│ ┌─────────────────────────────────────────────────────────────────────┐ │
│ │ API GATEWAY │ │
│ │ Authentication │ Rate Limiting │ Routing │ Transformation │ │
│ └─────────────────────────────────────────────────────────────────────┘ │
│ │ │
│ ▼ │
│ ┌─────────────────────────────────────────────────────────────────────┐ │
│ │ SERVICE MESH │ │
│ │ Traffic Management │ Security │ Observability │ │
│ └─────────────────────────────────────────────────────────────────────┘ │
│ │ │
│ ┌───────────┬───────────┬───┴───────┬───────────┬───────────┐ │
│ │ │ │ │ │ │ │
│ ▼ ▼ ▼ ▼ ▼ ▼ │
│ ┌─────────┐ ┌─────────┐ ┌─────────┐ ┌─────────┐ ┌─────────┐ ┌─────────┐ │
│ │Service A│ │Service B│ │Service C│ │Service D│ │Service E│ │Service F│ │
│ └─────────┘ └─────────┘ └─────────┘ └─────────┘ └─────────┘ └─────────┘ │
│ │ │
│ ▼ │
│ ┌─────────────────────────────────────────────────────────────────────┐ │
│ │ PLATFORM SERVICES │ │
│ │ Config │ Secrets │ Discovery │ Messaging │ Databases │ Caching │ │
│ └─────────────────────────────────────────────────────────────────────┘ │
│ │
└─────────────────────────────────────────────────────────────────────────────┘
Components:
| Component | Purpose | Technologies |
|---|---|---|
| Container Platform | Run microservices | Kubernetes, ECS |
| Service Mesh | Service communication | Istio, Linkerd |
| API Gateway | External access | Kong, AWS API Gateway |
| Service Discovery | Dynamic location | Kubernetes DNS, Consul |
| Config Management | Centralized config | ConfigMaps, Consul |
| Secret Management | Secure secrets | Vault, AWS Secrets Manager |
| Message Bus | Async communication | Kafka, RabbitMQ |
Event-Driven Architecture Pattern
Purpose: Enable loose coupling through asynchronous messaging.
| Pattern | Description | Use Case |
|---|---|---|
| Event Notification | Notify subscribers of events | Order placed notification |
| Event-Carried State Transfer | Include state in events | Customer profile updated |
| Event Sourcing | Store events as source of truth | Financial transactions |
| CQRS | Separate read and write models | High-read applications |
Implementation Components:
| Component | Purpose | Technologies |
|---|---|---|
| Event Bus | Event distribution | Kafka, EventBridge |
| Message Queue | Point-to-point | SQS, RabbitMQ |
| Stream Processing | Real-time processing | Kinesis, Kafka Streams |
| Event Store | Event persistence | EventStoreDB, DynamoDB |
Disaster Recovery Patterns
| Pattern | RPO | RTO | Cost | Description |
|---|---|---|---|---|
| Backup & Restore | Hours | Hours | $ | Backup data, restore when needed |
| Pilot Light | Minutes | Minutes-Hours | $$ | Core components running |
| Warm Standby | Minutes | Minutes | $$$ | Scaled-down copy running |
| Multi-Site Active-Active | Near-zero | Near-zero | \(\) | Full capacity in multiple regions |
Reference Architectures
Web Application Reference Architecture
┌─────────────────────────────────────────────────────────────────────────────┐
│ WEB APPLICATION REFERENCE ARCHITECTURE │
├─────────────────────────────────────────────────────────────────────────────┤
│ │
│ INTERNET │
│ │ │
│ ▼ │
│ ┌───────────────────────────────────────────────────────────────────┐ │
│ │ CDN (CloudFront/CloudFlare) │ │
│ │ • Static content caching │ │
│ │ • DDoS protection │ │
│ │ • Edge security │ │
│ └───────────────────────────────────────────────────────────────────┘ │
│ │ │
│ ▼ │
│ ┌───────────────────────────────────────────────────────────────────┐ │
│ │ WAF (Web Application Firewall) │ │
│ │ • OWASP rule sets │ │
│ │ • Rate limiting │ │
│ │ • Bot protection │ │
│ └───────────────────────────────────────────────────────────────────┘ │
│ │ │
│ ▼ │
│ ┌───────────────────────────────────────────────────────────────────┐ │
│ │ Application Load Balancer │ │
│ │ • SSL termination │ │
│ │ • Health checks │ │
│ │ • Path-based routing │ │
│ └───────────────────────────────────────────────────────────────────┘ │
│ │ │
│ ┌───┴───────────────────────────────────────────────────────────┐ │
│ │ PUBLIC SUBNETS │ │
│ │ ┌─────────────────┐ ┌─────────────────┐ │ │
│ │ │ NAT Gateway │ │ NAT Gateway │ │ │
│ │ │ (AZ-A) │ │ (AZ-B) │ │ │
│ │ └─────────────────┘ └─────────────────┘ │ │
│ └───────────────────────────────────────────────────────────────┘ │
│ │ │
│ ┌───┴───────────────────────────────────────────────────────────┐ │
│ │ PRIVATE SUBNETS - APPLICATION │ │
│ │ ┌─────────────────┐ ┌─────────────────┐ │ │
│ │ │ Web Tier │ │ Web Tier │ │ │
│ │ │ Auto-scaling │ │ Auto-scaling │ │ │
│ │ │ Group (AZ-A) │ │ Group (AZ-B) │ │ │
│ │ └─────────────────┘ └─────────────────┘ │ │
│ │ ┌─────────────────┐ ┌─────────────────┐ │ │
│ │ │ App Tier │ │ App Tier │ │ │
│ │ │ Auto-scaling │ │ Auto-scaling │ │ │
│ │ │ Group (AZ-A) │ │ Group (AZ-B) │ │ │
│ │ └─────────────────┘ └─────────────────┘ │ │
│ └───────────────────────────────────────────────────────────────┘ │
│ │ │
│ ┌───┴───────────────────────────────────────────────────────────┐ │
│ │ PRIVATE SUBNETS - DATA │ │
│ │ ┌─────────────────┐ ┌─────────────────┐ │ │
│ │ │ RDS Primary │◄─────────►│ RDS Standby │ │ │
│ │ │ (AZ-A) │ Sync │ (AZ-B) │ │ │
│ │ └─────────────────┘ Repl └─────────────────┘ │ │
│ │ ┌─────────────────┐ ┌─────────────────┐ │ │
│ │ │ ElastiCache │◄─────────►│ ElastiCache │ │ │
│ │ │ Primary (AZ-A) │ │ Replica (AZ-B) │ │ │
│ │ └─────────────────┘ └─────────────────┘ │ │
│ └───────────────────────────────────────────────────────────────┘ │
│ │
└─────────────────────────────────────────────────────────────────────────────┘
Data Platform Reference Architecture
┌─────────────────────────────────────────────────────────────────────────────┐
│ DATA PLATFORM REFERENCE ARCHITECTURE │
├─────────────────────────────────────────────────────────────────────────────┤
│ │
│ DATA SOURCES │
│ ┌─────────┐ ┌─────────┐ ┌─────────┐ ┌─────────┐ ┌─────────┐ │
│ │Databases│ │ APIs │ │ Files │ │Streaming│ │ IoT │ │
│ └────┬────┘ └────┬────┘ └────┬────┘ └────┬────┘ └────┬────┘ │
│ │ │ │ │ │ │
│ └───────────┴───────────┴─────┬─────┴───────────┘ │
│ │ │
│ ▼ │
│ ┌─────────────────────────────────────────────────────────────────────┐ │
│ │ INGESTION LAYER │ │
│ │ Kinesis │ Kafka │ API Gateway │ SFTP │ Database Migration Service │ │
│ └─────────────────────────────────────────────────────────────────────┘ │
│ │ │
│ ▼ │
│ ┌─────────────────────────────────────────────────────────────────────┐ │
│ │ STORAGE LAYER │ │
│ │ ┌───────────────┐ ┌───────────────┐ ┌───────────────┐ │ │
│ │ │ Raw Zone │ │Processed Zone │ │ Curated Zone │ │ │
│ │ │ (Landing) │──►│ (Cleaned) │──►│ (Business) │ │ │
│ │ │ S3 │ │ S3 │ │ S3 │ │ │
│ │ └───────────────┘ └───────────────┘ └───────────────┘ │ │
│ └─────────────────────────────────────────────────────────────────────┘ │
│ │ │
│ ▼ │
│ ┌─────────────────────────────────────────────────────────────────────┐ │
│ │ PROCESSING LAYER │ │
│ │ EMR │ Glue │ Lambda │ Databricks │ Spark │ Data Pipeline │ │
│ └─────────────────────────────────────────────────────────────────────┘ │
│ │ │
│ ▼ │
│ ┌─────────────────────────────────────────────────────────────────────┐ │
│ │ ANALYTICS LAYER │ │
│ │ Redshift │ Athena │ OpenSearch │ Timestream │ Neptune │ │
│ └─────────────────────────────────────────────────────────────────────┘ │
│ │ │
│ ▼ │
│ ┌─────────────────────────────────────────────────────────────────────┐ │
│ │ CONSUMPTION LAYER │ │
│ │ QuickSight │ Tableau │ APIs │ ML Models │ Notebooks │ │
│ └─────────────────────────────────────────────────────────────────────┘ │
│ │ │
│ ┌─────────────────────────────────────────────────────────────────────┐ │
│ │ GOVERNANCE LAYER │ │
│ │ Data Catalog │ Data Quality │ Lineage │ Security │ Compliance │ │
│ └─────────────────────────────────────────────────────────────────────┘ │
│ │
└─────────────────────────────────────────────────────────────────────────────┘
Container Platform Reference Architecture
| Component | Purpose | Options |
|---|---|---|
| Control Plane | Kubernetes API, scheduler, controllers | EKS, AKS, GKE, self-managed |
| Worker Nodes | Run container workloads | EC2, managed node groups, Fargate |
| Networking | Pod networking, services | VPC CNI, Calico, Cilium |
| Storage | Persistent storage | EBS CSI, EFS CSI, S3 |
| Ingress | External access | ALB Ingress, NGINX, Traefik |
| Service Mesh | Service-to-service | Istio, Linkerd, App Mesh |
| Observability | Monitoring, logging | Prometheus, Grafana, Fluentd |
| Security | Policy, secrets | OPA/Gatekeeper, Vault |
Architecture Decision Records (ADRs)
Purpose and Value
Architecture Decision Records document significant architecture decisions including context, options considered, decision made, and consequences. They provide:
- Institutional memory: Why decisions were made
- Onboarding aid: Help new team members understand architecture
- Change assessment: Context for evaluating changes
- Audit trail: History of architectural evolution
ADR Template
# ADR-NNN: [Short Title]
## Status
[Proposed | Accepted | Deprecated | Superseded by ADR-XXX]
## Date
YYYY-MM-DD
## Context
[Describe the situation requiring a decision. What is the problem?
What constraints exist? What requirements must be met?]
## Decision
[State the decision clearly and concisely.]
## Options Considered
### Option 1: [Name]
**Description**: [What is this option?]
**Pros**:
- [Advantage 1]
- [Advantage 2]
**Cons**:
- [Disadvantage 1]
- [Disadvantage 2]
### Option 2: [Name]
**Description**: [What is this option?]
**Pros**:
- [Advantage 1]
- [Advantage 2]
**Cons**:
- [Disadvantage 1]
- [Disadvantage 2]
## Rationale
[Explain why this option was selected over alternatives.]
## Consequences
### Positive
- [Benefit 1]
- [Benefit 2]
### Negative
- [Drawback 1]
- [Drawback 2]
### Risks
- [Risk 1 and mitigation]
- [Risk 2 and mitigation]
## Related Decisions
- [ADR-XXX: Related decision]
## References
- [Link to related documentation]
ADR Example
# ADR-003: Use Kubernetes for Container Orchestration
## Status
Accepted
## Date
2024-01-15
## Context
We need a container orchestration platform to run our microservices
workloads. We have 50+ microservices that need to be deployed,
scaled, and managed across multiple environments.
## Decision
We will use Amazon EKS (Elastic Kubernetes Service) as our
container orchestration platform.
## Options Considered
### Option 1: Amazon EKS
**Description**: Managed Kubernetes service from AWS
**Pros**:
- Industry-standard Kubernetes
- Large ecosystem and community
- AWS integration (IAM, networking, storage)
- Portable skills and workloads
**Cons**:
- Complexity of Kubernetes
- Learning curve for team
- Management overhead for add-ons
### Option 2: Amazon ECS
**Description**: AWS proprietary container orchestration
**Pros**:
- Simpler than Kubernetes
- Tighter AWS integration
- Lower operational overhead
**Cons**:
- AWS-specific, not portable
- Smaller ecosystem
- Limited to AWS
### Option 3: Self-managed Kubernetes
**Description**: Kubernetes on EC2 instances
**Pros**:
- Full control
- No managed service costs
**Cons**:
- High operational overhead
- Requires deep Kubernetes expertise
- Responsibility for upgrades and security
## Rationale
EKS provides the industry-standard Kubernetes platform while
reducing operational overhead through managed control plane.
The portability and ecosystem benefits outweigh the complexity.
## Consequences
### Positive
- Industry-standard platform with large talent pool
- Portable workloads and skills
- Rich ecosystem of tools and integrations
### Negative
- Team needs Kubernetes training
- Additional complexity compared to ECS
- Need to manage add-ons (monitoring, ingress, etc.)
### Risks
- Kubernetes complexity may slow initial delivery
Mitigation: Training and start with simpler workloads
- Add-on management overhead
Mitigation: Use managed add-ons where available
Architecture Review Process
Review Types
| Type | Trigger | Scope | Participants |
|---|---|---|---|
| Design Review | New project, major change | Full architecture | Architects, security, ops |
| Security Review | Security-impacting change | Security aspects | Security team, architects |
| Cost Review | Significant spending | Cost implications | FinOps, architects |
| Operational Review | Pre-production | Operational readiness | Operations, SRE |
| Post-Implementation | After deployment | Actual vs. designed | All stakeholders |
Architecture Review Checklist
| Category | Questions |
|---|---|
| Requirements | Are functional and non-functional requirements clearly defined? |
| Are SLAs/SLOs defined and achievable? | |
| Are compliance requirements identified? | |
| Standards | Does design follow architecture standards? |
| Are approved patterns and technologies used? | |
| Are there exceptions that need approval? | |
| Reliability | What is the availability design? |
| How are single points of failure addressed? | |
| What is the disaster recovery strategy? | |
| Security | Are security controls appropriate for data classification? |
| Is encryption implemented correctly? | |
| Are access controls properly designed? | |
| Scalability | Can the design handle expected growth? |
| Is scaling automatic or manual? | |
| Are bottlenecks identified and addressed? | |
| Performance | Are performance requirements defined? |
| Is the design validated against requirements? | |
| Is monitoring in place to detect issues? | |
| Cost | Are costs estimated and acceptable? |
| Are cost optimization measures implemented? | |
| Is the cost model sustainable? | |
| Operations | Is the design operationally supportable? |
| Is monitoring and alerting comprehensive? | |
| Are runbooks and documentation planned? |
Review Questions
Principle Application: A startup is designing their first production infrastructure. They want to move fast but also build a solid foundation. Which three principles should they prioritize and why?
Pattern Selection: A financial services company needs to ensure their trading platform has near-zero downtime. Which availability pattern should they choose and what are the key implementation considerations?
ADR Practice: Your team decided to use PostgreSQL over MongoDB for a new application. Write an ADR documenting this decision, including at least two options considered with pros/cons.
Reference Architecture: How would you modify the web application reference architecture to support a global user base with users in North America, Europe, and Asia?
Architecture Review: During an architecture review, you notice the design has a single NAT gateway for all traffic. What concerns would you raise and what alternatives would you suggest?
Principle Trade-offs: Sometimes principles conflict. How would you handle a situation where “Optimize for Cost” conflicts with “Design for Failure”?
Key Takeaways
- Core principles guide all architecture decisions and provide consistency
- Design for failure is essential—assume everything will fail eventually
- Security by default embeds protection from the start, not as an afterthought
- Design patterns provide proven solutions for common requirements
- Reference architectures accelerate design for common scenarios
- ADRs document decisions for future understanding and institutional memory
- Architecture reviews validate designs before costly implementation
Summary
Infrastructure architecture establishes the foundation for reliable, secure, and cost-effective IT systems. By applying consistent principles, using proven patterns, leveraging reference architectures, documenting decisions, and conducting thorough reviews, architects create infrastructure that supports business needs while remaining maintainable and adaptable.
The principles and patterns in this chapter apply across cloud providers and deployment models. In the following chapters, we’ll explore specific aspects of architecture in more detail, starting with cloud platform architecture.