High Availability (HA)

High availability engineering eliminates single points of failure so that systems remain accessible even when individual components fail.

Why it matters

• Modern businesses depend on 24/7 system availability.
• Downtime costs range from thousands to millions per hour.
• SLAs often require 99.9% or higher uptime guarantees.
• Customer experience suffers from even brief outages.

The "nines" of availability

• 99% (two nines): 3.65 days downtime/year
• 99.9% (three nines): 8.76 hours downtime/year
• 99.99% (four nines): 52.6 minutes downtime/year
• 99.999% (five nines): 5.26 minutes downtime/year
• 99.9999% (six nines): 31.5 seconds downtime/year

HA design principles

• Redundancy: Duplicate critical components (servers, storage, network paths).
• Failover: Automatic switching to standby systems when primary fails.
• Load balancing: Distribute traffic across multiple instances.
• Geographic distribution: Spread across data centers/regions.
• Health monitoring: Detect failures quickly to trigger failover.

Common HA patterns

• Active-passive: Standby takes over only when primary fails.
• Active-active: All nodes serve traffic simultaneously.
• N+1 redundancy: One extra instance beyond minimum required.
• 2N redundancy: Double the required capacity.

Implementation considerations

• Database replication and clustering.
• Stateless application design for easy scaling.
• Session management across instances.
• DNS failover or global load balancing.
• Chaos engineering to test failure scenarios.
• Monitoring and alerting for rapid incident response.

Trade-offs

• Higher complexity and operational overhead.
• Increased infrastructure costs.
• Potential for split-brain scenarios in distributed systems.
• Need for thorough testing of failover mechanisms.