DORA (DevOps Research and Assessment) is a set of key performance indicators that provide a holistic view of your DevOps capabilities. Originating from academic research and industry insights, DORA metrics aim to quantify the efficiency, speed, and reliability of software delivery and operational processes.
The Four Pillars of DORA Metrics
- Deployment Frequency (DF)
- Lead Time (LT)
- Change Failure Rate (CFR)
- and Mean Time to Recover (MTTR)
Deployment Frequency (DF)
This metric measures how often new code is deployed to production.
- How to measure: Count the number of deployments over a given period. Divide that by the length of the period to get a rate.
- Real-Scenario Example: If you deploy 14 times in a two-week sprint, your DF would be 1 daily deployment.
Lead Time (LT)
The duration from the time code is committed until it is deployed into production.
- How to measure: Track the timestamp when code is committed and when it's deployed. The difference gives you the LT.
- Real-Scenario Example: If it takes 3 days from committing a feature branch to deploying it to production, your LT is 3 days.
Change Failure Rate (CFR)
The percentage of deployments that fail, requiring actions like hotfixes, rollbacks, or feature flag adjustments.
- How to measure: Number of failed deployments divided by the total number of deployments, then multiplied by 100 to get a percentage.
- Real-Scenario Example: If you deployed 100 times last month and had to roll back 5, your CFR would be 5%.
Mean Time to Recover (MTTR)
The average time it takes to recover from a failed deployment or incident.
- How to measure: Sum the recovery time for all incidents over a given period and divide by the number of incidents.
- Real-Scenario Example: If you had 3 incidents last week taking 2, 4, and 6 hours to resolve, your MTTR would be (2+4+6)/3 = 4 hours.
How These Metrics Interact
DF & LT:
A higher DF generally indicates a lower LT. If you deploy frequently, it indicates that you have optimized your pipeline.
DF & CFR:
An optimized DevOps process should aim for a high DF and a low CFR. This ensures you're deploying often without breaking things.
CFR & MTTR:
A lower CFR usually leads to a lower MTTR. If you're failing less often, you probably have a smaller number of unexpected problems to solve or deal with.
LT & MTTR:
A shorter LT often correlates with a shorter MTTR. Efficient pipelines are usually directly related to robust testing and monitoring tools, which help quick recoveries.
Tips and Tricks for Measuring DORA Metrics
1. Automation
Use DevOps tools to automate data collection, so metrics are accurate and up-to-date. Teams often integrate Jenkins or GitLab CI/CD with monitoring tools like Prometheus and Datadog to capture key metrics automatically during each deployment.
2. Define Clear Benchmarks
Don't just say "We want a lower LT" or "higher DF." Assign actual numerical goals that you aim to achieve within a set time frame. Set quarterly objectives, such as reducing LT from 5 days to 3 days or increasing DF from once a week to twice a week.
3. Checkpoints
Create a checkpoint for alignment, and briefly discuss the latest metrics. Is CFR on the rise? What's the trend with MTTR? Keep these numbers top-of-mind for all team members. During alignment, you can have a discussion with you to present the Grafana dashboard displaying the current state of your DORA metrics.
You can Schedule monthly or quarterly reviews of the DORA metrics, comparing them against the goals you set. In your Q2 review, you find that CFR has been reduced from 8% to 4% and align that with objectives for Q3.
4. Correlate with Business Metrics
Whenever possible, map the DORA metrics to business KPIs, like customer satisfaction scores or user engagement metrics. After you sped up deployments (higher DF), you noticed a 15% increase in user engagement because features were released faster. Presenting such correlations can make management understand easier.
6. Incident Retrospectives
After each incident, calculate the MTTR and also reassess how the incident impacted other metrics like CFR. After a severe outage that took 6 hours to resolve, your team analyzed the incident and found that CFR spiked. It becomes a focal point to improve in the next sprint.
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