๐ฉ๐ฒ๐น๐๐ฟ๐ถ๐ ๐ง๐ฟ๐ฒ๐ฎ๐๐๐ฟ๐ฒ ๐๐๐ป๐๐ ๐๐ป๐ฑ ๐ฆ๐ฒ๐ฟ๐๐ถ๐ฐ๐ฒ ๐๐ผ๐๐ป๐ฑ๐ฎ๐ฟ๐ถ๐ฒ๐
Our treasure hunt engine failed. MongoDB CPU hit 90 percent. Deadlocks filled our logs. We tied event sourcing to state management. Every find triggered a chain of events. This worked for a few users. It failed as we grew.
We tried quick fixes. We added MongoDB nodes. We added Kafka partitions. We added Redis. These provided short relief. Writes stayed slow. Data became inconsistent.
We changed our service boundaries. We separated event sourcing from state management. We built a Treasure Hunt Orchestrator. This service handles state. It uses asynchronous APIs. We switched to Amazon Neptune. This graph database handles complex queries.
The results came fast.
- CPU dropped to 30 percent.
- Errors fell 5 times.
- Latency dropped from 500ms to 50ms.
- User capacity grew 10 times.
- MongoDB nodes dropped from 10 to 2.
Use these lessons for your systems.
- Define your service boundaries early.
- Avoid premature optimization.
- Use small, iterative changes.
- Invest in automated testing.
- Set up detailed monitoring.