Active-Active Resilience Across Clouds
An active-active design that serves traffic from two cloud providers at once, backed by a distributed SQL database and mirrored event streams. It delivers near-zero RTO and provider independence at the cost of higher spend and cross-cloud complexity.
What and When
Active-active resilience runs the same workload concurrently across two cloud providers, with live traffic split between them. If one provider suffers a regional or account-wide outage, the other continues serving with no failover delay. Choose this when an outage of a single provider is unacceptable, or when contractual or regulatory requirements demand provider independence.
This is the most demanding resilience pattern. It requires data that can be written in both clouds and applications free of provider-specific lock-in.
Components
- Global load balancer with anycast DNS distributes users to the nearest healthy cloud and steers traffic away from a failing one.
- Kubernetes clusters run identical workloads in each cloud, deployed from the same manifests.
- CockroachDB (or a similar distributed SQL database) provides a single logical database with synchronous replication across clouds.
- Kafka with MirrorMaker keeps event streams consistent between providers.
- Service mesh handles cross-cloud mTLS, retries, and circuit breaking; object storage replication keeps blobs in sync.
Data Flow
A user request hits anycast DNS and is routed to the nearest cloud's load balancer, then to a Kubernetes cluster. The application reads and writes to the distributed database, which replicates the write to the other cloud to maintain consistency. Events published to Kafka are mirrored across providers. If health checks mark one cloud unhealthy, the global load balancer shifts its share of traffic to the surviving cloud within seconds.
Scaling and Resilience
Each cloud is sized to absorb 100% of traffic during a failover, so combined capacity runs near 200%. Cell-based partitioning limits the blast radius of a bad deploy. Regular chaos experiments validate that one cloud can carry the full load. Circuit breakers and retries in the mesh prevent cascading failures when cross-cloud latency rises.
Security
Identity and secrets must be federated so both clouds enforce the same policy. Encrypt all cross-cloud traffic with mTLS and treat the inter-cloud links as untrusted. Replicate audit logging to a neutral location so investigations survive a provider outage. Keep IAM least-privilege and consistent across providers to avoid drift that creates a weak link.
Trade-offs and Alternatives
Active-active across clouds is expensive and operationally heavy: cross-cloud write latency, data-consistency tuning, and avoiding provider-specific services all add cost. The reward is near-zero RTO and true provider independence. Most organizations get sufficient resilience from multi-region within a single provider, which is far simpler. Reserve cross-cloud active-active for systems where a single-provider failure would be catastrophic.