Data Consistency in Multi-Region Deployments

Data Consistency in Multi-Region Deployments#

When you replicate data across regions, you are forced to choose between consistency, latency, and availability. You cannot have all three. Every multi-region system makes this tradeoff explicitly or, more dangerously, implicitly by ignoring it until production exposes the consequences.

The Fundamental Tension#

Strong consistency means every read sees the most recent write, regardless of which region it comes from. This requires cross-region coordination on every write (30-100ms per round trip). Eventual consistency means reads might see stale data, but replicas converge given enough time – usually milliseconds to seconds, but during partitions it can be minutes.

Cloud Multi-Region Architecture: AWS, GCP, and Azure Patterns with Terraform

Cloud Multi-Region Architecture Patterns#

Multi-region is not just running clusters in two places. It is the networking between them, the data replication strategy, the traffic routing, and the cost of keeping it all running. Each cloud provider has different primitives and different pricing models. Here is how to build it on each.

The three pillars: a Kubernetes cluster per region for compute, a global traffic routing layer to direct users to the nearest healthy region, and a multi-region database for state. Get any one wrong and multi-region gives you complexity without resilience.