Deployment Flow Metrics

The Deployment Flow tracks individual deployments through your CI/CD pipeline. Use these metrics to analyze deployment timing, reliability, and the relationship between deployments and other work items.

Overview

Grain: One row per deployment Refresh: Every 15 minutes Primary Use Case: Deployment pipeline analytics, release tracking, incident response

Duration Measures

Deployment Duration

What it measures: Time for a deployment to complete.

Aspect	Value
Start Point	Deployment created
End Point	First success status
Unit	Minutes
NULL when	Deployment hasn’t succeeded yet

Available aggregations:

avgDeploymentDurationMinutes - Average deployment execution time

Interpretation:

Measures the deployment pipeline execution time
Long durations indicate slow CI/CD pipelines or manual steps

Merge to Deploy

What it measures: Time from code merge to deployment.

Aspect	Value
Start Point	PR merged
End Point	Deployment created
Unit	Minutes
NULL when	No linked merged PR

Available aggregations:

avgMergeToDeployMinutes - Average pipeline time
medianMergeToDeployMinutes - Median pipeline time (recommended)

Issue to Deploy

What it measures: Time from issue creation to deployment.

Aspect	Value
Start Point	Issue created
End Point	Deployment created
Unit	Days
NULL when	No linked issue

Available aggregations:

avgIssueToDeployDays - Average from issue to deploy

Interpretation: This is a broader lead time measure including all work before coding begins.

Recovery Time

What it measures: How quickly the team recovers from a deployment failure.

Aspect	Value
Start Point	First failure status
End Point	First success status
Unit	Hours
NULL when	No failure occurred, or no recovery yet

Available aggregations:

avgMttrHours - Average recovery time
medianMttrHours - Median recovery time (recommended)

Note: Only calculated for deployments that experienced a failure. Successful deployments have NULL recovery time.

Status Measures

Change Failure Rate

What it measures: Percentage of production deployments that result in failure.

Aspect	Value
Measure	`changeFailureRate`
Numerator	Production deployments that failed
Denominator	Completed production deployments (success + failure)
Unit	Percentage

Related counts:

changeFailureCount - Number of failed production deployments

Note: Only counts completed deployments. In-progress deployments are excluded.

Count Metrics

Basic Counts

Measure	Description
`count`	Total deployments (all environments)
`productionDeploymentCount`	Production environment only
`successfulProductionDeploymentCount`	Successful production deployments
`changeFailureCount`	Failed production deployments

Relationship Counts

Measure	Description
`avgLinkedPrCount`	Average PRs per deployment
`avgLinkedIssueCount`	Average issues per deployment
`totalLinkedFeatures`	Total features deployed
`totalLinkedBugs`	Total bug fixes deployed

Dimensions (Filters)

Deployment Attributes

Dimension	Description
`provider`	Deployment provider (GitHub Actions, etc.)
`environment`	Target environment name
`currentStatus`	Current deployment status
`sha`	Git commit SHA
`ref`	Git ref (branch/tag)

Status Flags

Dimension	Description
`isProduction`	Production environment deployment
`isSuccessful`	Current status is success
`isFailed`	Current status is failure/error
`isInProgress`	Deployment still running
`hadFailure`	Had a failure at some point
`hadSuccess`	Had a success at some point
`isChangeFailure`	Production deployment that failed
`isSuccessfulProductionDeployment`	Successful production deployment

Time Dimensions

Dimension	Description
`deploymentCreatedAt`	When deployment was triggered
`deploymentUpdatedAt`	Last status update
`firstSuccessAt`	First success timestamp
`firstFailureAt`	First failure timestamp

Via Joins

Projects.id / Projects.name - Filter by project
Teams.id / Teams.name - Filter by team
Users.id / Users.name - Filter by deployment creator

Common Analysis Patterns

Deployment Reliability

Measures:
- productionDeploymentCount
- successfulProductionDeploymentCount
- changeFailureRate

Analysis: Track failure rate trends over time

Pipeline Performance

Measures:
- avgDeploymentDurationMinutes
- medianMergeToDeployMinutes

Analysis: Identify slow pipeline stages

Incident Recovery

Measures:
- changeFailureCount (incidents)
- medianMttrHours (recovery time)

Filter: hadFailure = true
Analysis: Identify patterns in failures

Deployment Content

Measures:
- avgLinkedPrCount (batch size)
- totalLinkedFeatures (feature throughput)
- totalLinkedBugs (bug fix throughput)

Analysis: Understand what's being deployed

FAQ

Q: How is production determined?

The isProduction flag is set based on the environment name matching production patterns (e.g., “production”, “prod”, “prd”). Check your deployment configuration if unexpected.

Q: Why do some deployments show NULL for recovery time?

Recovery time is only calculated for deployments that experienced a failure. Successful deployments (no failure at any point) have NULL recovery time - this is correct, not a data issue.

Q: What’s the difference between isFailed and hadFailure?

isFailed reflects the current status. hadFailure indicates whether the deployment ever failed at any point, even if it later succeeded (after recovery).

Analytics Overview - Understanding the three flows
Discovery Flow - Track research validation
Delivery Flow - Track work item delivery
DORA Metrics - DevOps performance framework
SPACE Framework - Developer productivity framework