DORA and DevOps

Pull request to production time

Also known as Pull request to production time metric, Pull request to production time in DevOps

By WeavePublished 2 min read

Definition

Pull request to production time is a software delivery concept used to describe a specific event, interval, control, or operating condition in the path from source change to production behavior. A useful definition names the boundary, unit, and decision the measure supports.

How to use the concept

Use pull request to production time as a lens on the delivery system rather than as an isolated score. Segment by service, environment, release path, and change type when those distinctions affect risk or waiting. The same label can describe different operational realities if teams do not document the counting rule.

A concrete delivery example

Suppose a service records 100 relevant events during a month and 8 meet the condition represented by pull request to production time. Under that explicit rule, the reported share is 8 percent. The team then reviews the eight cases individually, because the aggregate says how often the condition appeared but not why it appeared.

Limitations and interpretation

This signal is sensitive to instrumentation. Missing deployments, duplicate webhooks, hidden retries, and inconsistent labels can make pull request to production time look better or worse. Preserve event-level evidence and record the policy used to include or exclude cases.

Before acting on pull request to production time, compare the current observation with a compatible baseline and ask which underlying event produced it. Keep the raw records, counting policy, and ownership visible. When the signal changes, inspect the surrounding workflow for queueing, rework, failed checks, or recovery work. That practice makes the glossary term useful for diagnosis rather than a label attached to a dashboard.

How this relates to Weave

Weave's Engineering Intelligence can help teams examine pull request to production time alongside code, pull request, quality, and delivery context. That view is useful for finding the workflow behind a result and deciding what to investigate next. The underlying repository, deployment, incident, or observability system remains the source of truth for the event, and teams should confirm the available integrations before relying on any field.

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Sources and further reading

  1. DORA software delivery performance metrics