DORA Metrics

DORA (DevOps Research and Assessment) metrics provide a standardized way to measure software delivery performance. GuideMode implements all four key DORA metrics through the Deployment Flow cube.

What is DORA?

DORA is a research program that identified four key metrics that distinguish high-performing technology organizations. These metrics measure both speed (deployment frequency, lead time) and stability (change failure rate, MTTR).

The Four Key Metrics

DORA Metric	GuideMode Measure	Source Cube
Deployment Frequency	`productionDeploymentCount`	Deployment Flow
Lead Time for Changes	`avgMergeToDeployMinutes`	Deployment Flow
Change Failure Rate	`changeFailureRate`	Deployment Flow
Mean Time to Recovery	`medianMttrHours`	Deployment Flow

Deployment Frequency

What it measures: How often code deploys to production.

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

How to calculate: Filter by time dimension (day, week, month) to calculate frequency.

Benchmarks:

Level	Frequency
Elite	Multiple deploys per day
High	Between once per day and once per week
Medium	Between once per week and once per month
Low	Between once per month and once every six months

Lead Time for Changes

What it measures: Time from code commit to production deployment.

GuideMode provides two lead time measures:

Merge to Deploy (Pipeline Lead Time)

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

Measures:

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

Issue to Deploy (Full Lead Time)

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

Measures:

avgIssueToDeployDays - Average from issue to deploy

Benchmarks:

Level	Lead Time
Elite	Less than 1 hour
High	Between 1 hour and 1 day
Medium	Between 1 day and 1 week
Low	More than 1 week

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
productionDeploymentCount - Total production deployments

What counts as a failure:

Build failures
Test failures
Deployment errors
Health check failures
Successful rollbacks (the initial deployment still failed)

Benchmarks:

Level	Failure Rate
Elite	0-15%
High	16-30%
Medium	31-45%
Low	46-60%

Note: This metric only counts completed deployments. In-progress deployments are excluded to avoid skewing the rate.

Mean Time to Recovery (MTTR)

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

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

Measures:

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

Benchmarks:

Level	Recovery Time
Elite	Less than 1 hour
High	Less than 1 day (24 hours)
Medium	Less than 1 week
Low	More than 1 week

Note: MTTR measures how quickly the system recovers, not how quickly the root cause is fixed. A successful deployment indicates the system is working again.

Industry Benchmarks Summary

Metric	Elite	High	Medium	Low
Deployment Frequency	On-demand (multiple/day)	Weekly to daily	Monthly to weekly	Monthly to 6-monthly
Lead Time for Changes	< 1 hour	1 day - 1 week	1 week - 1 month	1 - 6 months
Change Failure Rate	0-15%	16-30%	31-45%	46-60%
MTTR	< 1 hour	< 1 day	< 1 week	> 1 week

Source: DORA State of DevOps Reports

Building a DORA Dashboard

Basic DORA Dashboard

Measures:
- productionDeploymentCount (Deployment Frequency)
- medianMergeToDeployMinutes (Lead Time)
- changeFailureRate (Change Failure Rate)
- medianMttrHours (MTTR)

Filter: isProduction = true
Time: Last 30/90 days

Elite Team Indicators

An elite team typically shows:

Deployment Frequency: > 1 per day
Lead Time: < 60 minutes
Change Failure Rate: < 15%
MTTR: < 60 minutes

Improvement Priorities

When metrics are poor, prioritize improvements in this order:

Change Failure Rate - Reduce failures first (quality)
MTTR - Recover faster from failures (resilience)
Lead Time - Speed up the pipeline (efficiency)
Deployment Frequency - Deploy more often (throughput)

This order ensures you build stability before speed.

FAQ

Q: Why is MTTR calculated from first failure to first success, not to resolution?

MTTR measures how quickly the system recovers, not how quickly the root cause is fixed. A successful deployment indicates the system is working again, even if follow-up work is needed.

Q: My change failure rate seems too high - what’s counted as a failure?

A deployment is counted as a failure if its status ever reaches ‘failure’ or ‘error’. This includes build failures, test failures, deployment errors, and health check failures. Successful rollbacks are still counted as failures (the initial deployment failed).

Q: Why does Merge to Deploy use minutes instead of hours?

Modern CI/CD pipelines often complete in minutes. Using minutes provides better granularity for elite teams while still being meaningful for slower pipelines.

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: Can I get MTTR for specific failure types?

Currently, MTTR is calculated for all failures. Future versions may support filtering by failure type or error category.

Q: Why do some deployments show NULL for MTTR?

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

Deployment Flow - Complete deployment cube reference
Delivery Flow - Work item delivery metrics
SPACE Framework - Alternative productivity framework