We noticed that secondary databases in our MongoDB cluster were falling minutes behind the primary database. In write-heavy setups, secondary nodes read from the primary node's oplog and apply writes locally. If oplog application is slower than primary writes, lag occurs.
The issue was disk I/O bottlenecks on secondary nodes, combined with index build locks. Queries executed against the secondaries read stale data, which corrupted user dashboard metrics.
We resolved this by upgrading the secondary instances' IOPS limits, optimizing write concerns to 'w: majority', and adding indexes in a rolling fashion to avoid write lockups. We learned to monitor replica lag metrics closely.
From a systems perspective, implementing this solution required auditing our telemetry structures. We mapped key transactions across our distributed database queries and evaluated the locking overheads under heavy load. By setting up strict validation rules in Prisma, we isolated runtime query errors before they could trickle up to the client view.
Ultimately, building durable systems means choosing boring abstractions and documenting architectural decisions (ADRs) meticulously. When infrastructure behaves predictably, your team can deploy with high confidence. We enforce these performance and security budgets in our continuous integration (CI) workflows, ensuring that every merge maintains the same standard.