The constraint
Sustain rapid daily growth without allowing hot shards, index sprawl, or analytical reads to degrade operations.
Case study · Data · Infrastructure
High-volume Data Platform
A write-heavy operational data platform supporting gaming, financial, and analytical workloads while daily data volume grows rapidly.
request lifecycle
architecture.flowEvents
Ingestion
Partition
Index
Read Model
The solution
Designed shard keys around dominant access patterns, introduced compound indexes for bounded queries, separated analytical consumers from the operational path, and used cache-backed projections for frequent reads.
architecture highlights
- Sharded MongoDB
- Compound indexing
- Event ingestion
- Read projections
- Retention pipelines
scalability considerations
- Avoid hot shard keys
- Bound all production queries
- Track index memory cost
- Move analytics off the operational cluster
project outcomes
- 10M+ new records daily
- Sub-second operational queries
- Stable write-heavy workloads
- Cache-aware read models
runtime.dependencies
Technology stack
MongoDBRedisPostgreSQLEvent HubKubernetes
engineering ownership
My contribution
Designed sharding keys, compound indexes, retention paths, and cache-aware query models.