Flow Metrics
Work in progress, flow time and flow efficiency — where a change waits rather than moves.
5 to work through
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intermediate
A platform team reports deployment frequency of 12 per day, lead time for changes of 40 minutes, change failure rate of 2% and recovery time of 18 minutes - elite on every band. Incidents have risen 40% over two quarters. Review the measurement.
3 min answer -
intermediate
A team's lead time from commit to production is three days. Which component is usually the largest, and how is it found?
2 min answer -
intermediate
An engineering director tells you that team A has a change failure rate of 2% and team B's is 18%, and asks you to find out what team A is doing right so the practice can be spread. Walk me through how you would answer.
3 min answer -
intermediate
Which delivery flow metrics reveal where the constraint actually is, and what do they typically show?
2 min answer -
advanced
Delivery leadership says releases are too slow and wants the engineering team to "move faster". Lead time from commit to production is 21 days. How do you investigate, and what do you expect to find?
2 min answer
4 terms in this topic
Approval Wait
The portion of lead time spent waiting for a human rather than for a machine - frequently the largest single component and invisible inside the aggre…
metricLead Time for Changes
The elapsed time from code committed to code running in production.
metricPipeline Change Coverage
The share of changes reaching production that the delivery pipeline actually measures - the denominator that decides whether elite delivery metrics d…
metricQueue Time Attribution
Splitting elapsed lead time into work and waiting, and naming which queue each wait sat in.
1 artifact you would hand over
Neighbouring topics
Delivery & Release Engineering
General material on getting a change from commit to production safely and often.
Pipeline Architecture
Stages, fan-out, caching, and the difference between a pipeline and a long script.
Build Reproducibility
Pinned inputs and hermetic builds, so one commit cannot produce two different artifacts.
Artifact Management
Immutable versioned outputs, promotion between repositories, and retention policy.
Environment Strategy
How many environments earn their cost, what each proves, and what none of them prove.
Branching Models
GitFlow, trunk and release branches as delivery constraints rather than Git preferences.
Continuous Integration Discipline
Integrating to the mainline daily, and the test speed and review culture that requires.
Deployment Strategies
Rolling, blue-green, canary and shadow, and the traffic and state each one assumes.
Progressive Delivery
Separating deploy from release, and exposing a change to users in controlled increments.
Rollback & Forward Fix
When reversing is genuinely possible, and designing so that it usually is.
Database Migration Under CD
Expand-contract, backwards-compatible schema change, and migrations that cannot roll back.
GitOps
Declared desired state in version control, with a reconciler closing the gap continuously.
IaC Modules & Drift
Reusable infrastructure modules, state ownership, and detecting what changed out of band.
Policy as Code
Encoding standards as automated admission and plan-time checks instead of review comments.
Pipeline Secrets
Short-lived credentials, workload identity, and why the CI system is a prime target.
Supply-Chain Provenance
SBOMs, signed artifacts, attestation, and knowing what actually went into a build.
Deployment Gates
Automated verification between stages, and the difference between a gate and a delay.
Change Management vs CD
Reconciling CAB-era controls with continuous delivery without pretending either away.
Multi-Region Rollout
Ordering regions, bake time, and stopping a bad change before it becomes global.