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).

Core Concepts

Deployments - Deployment tracking and environments
Pull Requests - PR lifecycle and linking

Analytics

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