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.
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