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Cloud Architecture: Scenario-Based Questions

35. How do you design a highly available architecture in the cloud?

High Availability (HA) ensures your system can operate continuously without failure for a long time. In cloud environments, HA relies on redundancy, fault tolerance, and smart distribution of resources.

🧱 Core Principles

  • Redundancy: Duplicate critical components (e.g., multiple web servers, DB replicas).
  • Failover: Automatic switching to backup systems during failure (e.g., multi-AZ DB failover).
  • Load Balancing: Distribute requests evenly to avoid overloading any node.
  • Health Checks: Continuously monitor component status and remove unhealthy ones.

🏗️ Cloud Design Patterns

  • Deploy across multiple Availability Zones (AZs) within a region.
  • Use managed services with built-in HA (e.g., RDS Multi-AZ, DynamoDB, Cloud Spanner).
  • Design stateless services behind autoscaling groups and ALBs.
  • Use regional or global load balancers (e.g., AWS ALB/ELB, GCP Load Balancer).

📦 Example Architecture

  • Frontend in AWS behind an ALB with EC2 or Fargate instances in 2+ AZs.
  • RDS or Aurora with Multi-AZ failover and read replicas.
  • Redis or Memcached with replication and failover nodes.
  • CI/CD to roll out updates gradually and avoid downtime.

🧰 Supporting Tools

  • Route 53 / GCP Cloud DNS: For DNS-based failover across regions.
  • Terraform: Codify HA setups with reusable modules.
  • Monitoring: Use CloudWatch, Stackdriver, or Datadog to detect and alert on downtime.

✅ Best Practices

  • Test failover regularly using chaos testing or blue/green deployments.
  • Keep services loosely coupled and resilient to downstream outages.
  • Use SLA-backed managed services where HA is mission-critical.

🚫 Common Pitfalls

  • Single AZ deployments — vulnerable to outages or data center failures.
  • Hard dependencies on stateful services that don’t replicate well.
  • No clear RTO/RPO definitions — leading to surprise during failure.

📌 Real-World Insight

High availability is not just about “uptime.” It’s about designing failure into your architecture — assuming components will break, and preparing your system to recover automatically and gracefully.