Data Observability

Express a freshness check as a metric and an alert

The first hands-on of the series: declare a freshness SLA, express staleness as a metric, and write an alert rule — including what happens when no data arrives at all.

Hold the observability mental model: infrastructure metrics versus data signals

Two layers live on one data platform: infrastructure metrics (CPU, lag, job success) and data signals (freshness, volume, schema, distribution).

Capstone: the data-platform observability checklist

• Assemble the full stack — metrics, alerts, traces, lineage, catalog
• Gate schedule and column changes pre-merge with SLA and impact checks

Incident drill: a broken upstream caught by freshness and lineage

The source job quietly changed from hourly to daily; the mart's 6h freshness SLA now fails by construction.

Instrument pipelines with OpenTelemetry: traces for data jobs

Traces give every pipeline run a story — which task ran, how long, with what attributes.

Production gotchas: alert fatigue, missing contracts, no-data silence

Three failure modes of a monitoring stack that looks healthy: alerts that page until nobody reads them, metrics with no declared SLA behind them, and no-data windows that pass as health.

Freshness Pre-Merge Check

Warn when a change would silently widen the freshness SLA of a source.

Grafana Documentation

Grafana's official documentation: dashboards, panel queries, alerting (including the unified alerting model), and provisioning. The standard surface where pipeline freshness, volume and job-health dashboards live.

OpenTelemetry Documentation

OpenTelemetry's official documentation: traces, metrics and logs through a vendor-neutral API/SDK, the collector, and semantic conventions. Increasingly the default instrumentation layer for distributed pipelines and services.

Prometheus Documentation

Official Prometheus docs: the pull-based metrics model, PromQL, exporters, service discovery and alerting rules. Data platforms lean on it for infrastructure- and job-level metrics that sit underneath data-quality signals like freshness and volume.