Bucket Timeseries Storage
Timeseries storage is optimized for timestamped values and trend analysis.
Use this for performance metrics, counters, confidence levels, and operational telemetry.
Best Use Cases
- defect/event count over time
- processing latency tracking
- quality score and confidence trends
Data Modeling Guidance
- normalize metric keys (
defect_count,avg_latency_ms) - keep units explicit in naming or metadata
- avoid high-cardinality key explosions
Query Strategy
Retrieve by:
- metric key
- time window
- latest values
Use bounded windows to prevent excessive read load.
Common Problems
- noisy metrics without aggregation strategy
- expensive reads from unbounded query windows
- mixed-unit values under a single key