Technical articles from the PulsusDB team
PulsusDB
Engineering blog
Detailed articles about query compilation, telemetry data models and the ClickHouse® database capabilities used by PulsusDB
engineering.notesVOL 01
01QUERY LANGUAGESPromQL · LogQL · TraceQL
02DATA MODELSMetrics · logs · traces
03ARCHITECTUREStateless APIs · SQL pushdown
04CLICKHOUSE DATABASEExecution · storage · scale
OPEN SOURCE ENGINEERINGdigitalis.io
01 / FEATUREDLatest technical article
PROMQL.ENGINE / 001 rate()sum by()quantile()PROMQL QUERY PLAN
PromQL11 min read
PromQL query execution with a ClickHouse® database
PulsusDB implements PromQL and the Prometheus query API over a storage model and execution path designed for large metric datasets
Read the article →02 / LATESTMore technical
More technical
Articles
Implementation details covering the storage models and query planning used for observability data in PulsusDB
02DATA.MODEL / 002
Signal-specific data models for observability telemetry
Metrics, logs and traces may share an ingestion protocol, but storing them in one generic shape makes the queries people actually run more expensive
8 min readRead article →
03METRICS.ROLLUP / 003
Raw metric and rollup selection in PulsusDB
A rollup only improves a query when its resolution and stored aggregates can preserve the meaning of the original PromQL expression
7 min readRead article →
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