What is the Wavefront data model and query language (WQL)? [Advanced]
Answer
Wavefront's data model is dimensional time-series data with metric names, sources, and point tags. WQL, or Wavefront Query Language, is used to query, transform, aggregate, and alert on time series, histograms, and events.
Technical explanation
A typical metric has a name, numeric value, timestamp, source, and tags such as env, service, cluster, or region.
WQL functions support filtering, aggregation, alignment, rates, percentiles, joins, and anomaly-style analysis.
Like Prometheus, data shape and tag cardinality are critical for cost and performance.
Hands-on example
Example WQL-style query: ts(app.checkout.request.latency, env=prod and service=checkout) to chart latency. Use aggregate functions by service or region, then build an alert when p95 latency remains above the SLO threshold for a sustained window.
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