Episode 50 — High Availability Patterns: active-active vs active-passive tradeoffs
High availability patterns are a recurring CloudNetX decision point because they determine whether a service continues through failures, how complex synchronization must be, and how recovery behaves under stress. This episode defines active-active as multiple instances serving traffic simultaneously, often improving capacity and reducing failover impact, and it defines active-passive as maintaining a standby instance that takes over when the active instance fails, often simplifying state but potentially increasing recovery time. The first paragraph focuses on the architectural tradeoffs behind each pattern, including how stateful components complicate active-active designs, how session and data consistency requirements shape feasibility, and why detection and transition behavior must be precise to avoid oscillation or split-brain outcomes. It also clarifies that “high availability” is not a single feature, but the result of correct redundancy scope, accurate health determination, and tested failover behavior across all dependencies, not just the compute instances.
