Guest: Philip Merry
Company: SIOS Technology
Show: Data Driven
Topic: Cloud Native

Split-brain scenarios are the nightmare failure mode that multi-availability zone and multi-region deployments can’t prevent on their own. And when they occur, the consequences can be catastrophic—conflicting data, corrupted writes, and impossible recovery decisions about which copy of your data is the “good” one.

Philip Merry, Solutions Engineer at SIOS Technology, breaks down split-brain in practical terms and explains why geographic distribution alone doesn’t protect against this application-level failure.

“A split-brain, in simplest terms, is when you have two systems—one meant to be active, one meant to be standby—but both systems say they are active,” Merry explains.

In a database context, this means both your US East and US West instances believe they’re the source of truth. Both are accepting writes. Neither is replicating to the other because neither recognizes itself as the standby. The result is data divergence—two versions of your database with conflicting transactions.

“If both systems are saying they’re the active copy, there’s the potential for data to not get copied from one system to another,” Merry says. “Neither is in the role of accepting incoming replicated data.”

Here’s the critical point: clients are still only connecting to one of those databases, so only one is actually receiving live transactions. But both systems think they should be receiving writes, which breaks the replication relationship. When the split-brain condition is eventually resolved, you’re left with an impossible question: which copy contains the correct data?

“There’s difficulty figuring out which copy is the quote-unquote good copy that you want to continue operating with once that situation is resolved,” Merry notes.

Multi-availability zones and multi-region deployments don’t prevent split-brain because it operates at the application level, not the infrastructure level. If communication between regions fails, or if there’s a replication issue that prevents one system from recognizing the other’s state, both can independently decide they need to become active.

“If there’s ever an issue where one system in the first region can’t communicate with its peer system in another region, then there’s that possibility for both systems to try to operate as the source,” Merry explains. “And they’re then competing to provide availability rather than working together.”

The second failure mode is data inconsistency, which persists even when split-brain doesn’t occur. When you’re replicating data across regions, synchronicity isn’t automatic—it must be achieved and maintained.

“Anytime you’re working with a business application and you’re managing customer data or managing business-critical data, you always want to be running with that most current copy of data,” Merry says. “When you introduce replication of data from one site to another, there’s obviously concerns about how long it takes to copy that data from one site to another.”

Replication lag is a reality in multi-region architectures. Geographic distance introduces latency. Network conditions vary. And during that lag, the secondary region is operating with stale data.

“Did node one get writes one, two, and three, and node two only get write one?” Merry asks. “When you spread applications out across regions, you aren’t really mitigating the factors that can contribute to data inconsistency. The time it takes to write data increases a little bit as latency increases, as systems are geographically dispersed.”

Multi-region deployments provide valuable protection against catastrophic infrastructure failures—fires, natural disasters, regional outages. That risk reduction is real. But it doesn’t solve application-level synchronicity challenges.

“You aren’t really gaining any mechanisms that aid in providing data consistency when using a multi-availability zone or a multi-region deployment,” Merry notes. “But you are gaining the peace of mind and the risk reduction knowing that if there were ever an issue in one of those regions, the infrastructure in the other region would not be impacted.”

The solution requires application-aware high availability tools that actively manage active/standby roles, enforce replication, monitor synchronicity, and prevent split-brain conditions through coordinated failover orchestration. Geographic distribution is necessary but not sufficient.

“You still have to make sure that everything is getting copied from one region to another before you’re able to really rely on that as a risk reduction measure,” Merry says.