USE CASE · UNIFIED OBSERVABILITY

UNIFIED
OBSERVABILITY.

Your observability stack has three separate storage backends: Loki or Splunk for logs, Prometheus for metrics, Tempo or Jaeger for traces. Three query languages, three retention policies, three scaling stories. XERJ stores all three signal types in one engine with one query language and one bill.

THE THREE-SYSTEM PROBLEM

Three systems means triple the ops. Prometheus needs compactors, Loki needs ingesters, Tempo needs compactors + ingesters. Each has its own storage, its own scaling model, its own failure modes.
Correlation is manual. "Show me the trace for the log that fired the alert that breached the metric threshold" requires copy-pasting IDs across three UIs.
Splunk pricing is unpredictable. Ingest-based pricing penalizes verbosity. Teams suppress logs to control cost, which defeats the purpose of observability.
No unified retention. Metrics keep 15 days, logs keep 30, traces keep 7 — each configured differently, each with its own pruning bugs.

THE XERJ ANSWER

One store for all three signals. Logs, metrics, and traces are just documents with different schemas. XERJ stores them in one engine with one WAL, one compression pipeline, one retention policy.
OTLP in, Prometheus out. Native OTLP log/trace ingest + a Prometheus-compatible /v1/metrics scrape endpoint. Drop-in for existing collectors.
Unified queries. Correlate across signal types with one query language. "Show me logs where trace_id = X and service = Y" is one _search call.
One retention number. [logs] retention_days = 30 applies to everything. No per-signal configuration.

READY?·REQUEST ACCESS

RUN IT ON
YOUR DATA.

Send us a representative OTLP payload (logs + traces) and a Prometheus scrape config. We'll benchmark ingest and show a unified query across all three signal types.

UNIFIEDOBSERVABILITY.

THE THREE-SYSTEM PROBLEM

THE XERJ ANSWER

SEE IT LIVE.

RUN IT ONYOUR DATA.

UNIFIED
OBSERVABILITY.

RUN IT ON
YOUR DATA.