Architecture Guide
Design, deploy, and scale resilient cloud-native applications using CloudNexus infrastructure. This guide covers reference architectures, networking, data patterns, and security models.
1. System Overview
CloudNexus is built on a distributed, multi-tenant architecture designed for high availability, low latency, and horizontal scalability. The platform abstracts infrastructure complexity through a unified control plane while providing direct access to underlying compute, storage, and networking resources.
We follow a shared-nothing architecture where each component scales independently. State is externalized, compute is ephemeral, and routing is centralized through an intelligent load-balancing mesh.
Core Design Principles
- Stateless Compute: Application instances are ephemeral and replaceable. State must be persisted to managed services.
- Edge-First Routing: Traffic is routed through the nearest edge node, reducing latency and offloading origin servers.
- Automated Failover: Health checks and self-healing mechanisms ensure zero-downtime during hardware or network failures.
- Immutable Infrastructure: Configuration changes are applied through declarative manifests, never manual edits.
2. Core Infrastructure Components
Understanding the building blocks is essential for designing resilient architectures. CloudNexus provides these core primitives:
Compute Engine
NVMe-backed virtual machines and bare metal instances with live migration and GPU passthrough support.
Managed Kubernetes
Control-plane abstraction with auto-scaling node groups, service mesh integration, and GitOps workflows.
Global CDN & Edge
300+ PoPs with smart caching, WebSocket support, and edge compute functions (Node.js/Python).
Object & Block Storage
S3-compatible object storage with tiered lifecycle policies and ZFS-backed block volumes.
Managed Databases
PostgreSQL, MySQL, Redis, and MongoDB with read replicas, automated backups, and point-in-time recovery.
Network Mesh
Anycast DNS, Layer 4/7 load balancers, private networking (VPC), and zero-trust service mesh.
3. Reference Architectures
We recommend three primary architectural patterns based on workload requirements:
3.1 High-Availability Single Region
Best for workloads requiring redundancy without cross-region latency. Uses multiple availability zones within a single region.
3.2 Active-Active Multi-Region
For global applications requiring sub-100ms latency and regional failover. Uses DNS-based traffic shifting and cross-region replication.
3.3 Edge-First Serverless
For static sites, APIs, and microservices. Computes requests at the edge with fallback to origin clusters only when necessary.
3.1 Network & Routing
CloudNexus uses a flat networking model with logical isolation through VPCs and network policies.
| Component | Protocol | Latency | Use Case |
|---|---|---|---|
| Anycast DNS | UDP/53 | < 15ms | Global resolution, failover routing |
| Layer 7 LB | HTTP/2, gRPC, WebSocket | < 3ms (private) | Path-based routing, SSL termination |
| VPC Peering | TCP/IP | < 1ms | Private service-to-service communication |
| Global Backbone | MPLS/IPoE | Variable | Cross-region data replication |
3.2 Data Flow & Storage
Data architecture follows a tiered pattern: cache → primary → cold storage. All writes go through the primary node; reads are distributed across replicas.
4. Security & Compliance
CloudNexus implements a zero-trust security model with defense-in-depth architecture. All traffic is encrypted in transit (TLS 1.3) and at rest (AES-256).
Never expose database ports directly to the internet. Use CloudNexus Private Networks or Bastion Hosts for administrative access.
Identity & Access Management
RBAC with granular permissions. Service accounts use short-lived JWTs rotated automatically. All API requests are authenticated via OAuth 2.0 or API keys.
Network Security
- Firewall: Stateful inspection at VPC boundary with geo-blocking and rate limiting
- WAF: OWASP Top 10 protection, custom rule sets, bot mitigation
- DDoS: Volumetric mitigation up to 1.5 Tbps, protocol-layer filtering
- Service Mesh: mTLS between pods, mutual authentication, circuit breaking
5. Scaling & Optimization
Horizontal scaling is preferred over vertical scaling. Use auto-scaling policies based on custom metrics, not just CPU/RAM.
Pre-scale during known traffic spikes using cron-triggered scaling policies. Warm instances reduce cold-start latency by up to 80%.
6. Best Practices
- Design for failure: Assume any single node can fail at any time. Use health checks and automatic replacements.
- Keep compute ephemeral: Store logs, sessions, and user data in managed services, not local disks.
- Monitor at the edge: Collect metrics before traffic hits origin servers to catch issues early.
- Use connection pooling: Database and cache connections should be multiplexed to prevent exhaustion under load.
- Implement circuit breakers: Prevent cascading failures when downstream services degrade.
7. Common Anti-Patterns
| Anti-Pattern | Why It Fails | Recommended Alternative |
|---|---|---|
| Stateful Instances | Prevents scaling and auto-healing | Externalize state to managed DB/Cache |
| Synchronous Cross-Region Calls | High latency causes timeouts | Use async messaging or regional read replicas |
| Over-Caching | Stale data, cache stampedes | Use short TTLs with fallback strategies |
| Hardcoded Secrets | Security risk, compliance violations | Use CloudNexus Vault or environment injection |
| Monolithic Deployments | Slow rollouts, high blast radius | Blue/Green or Canary releases |