The Limits of Relational Databases
Forcing Postgres or MySQL to act as a system-wide queue or coordinator introduces major performance bottlenecks as traffic grows:
- Write Bottlenecks: Table locks and index updates blocking standard user CRUD operations.
- Slow Rebalances: Misconfigured consumer parameters causing continuous partition rebalances and halting traffic streams.
- Network Congestion: Monolith modules polling database tables repeatedly, consuming network connections.
Our Distributed Systems Playbook
Apache Kafka Broker Tuning
We configure partition distribution, customize segment size guidelines, and optimize AWS GP3 EBS volumes for IOPS. This prevents broker lockups under peak ingestion load.
Resolving Consumer Group Lag
We tune parameters like `max.poll.interval.ms`, `max.poll.records`, and partition counts to match consumer capacities, preventing rebalance loops.
Akka / Pekko Actor Concurrency
We build concurrent, distributed processing engines inside JVM applications to handle millions of state updates in-memory rather than relying on constant database writes.