DORA metrics failure

Failure needs to be treated as a learning opportunity with the four key metrics

Published: Tuesday, Jul 18, 2023 Last modified: Monday, Apr 8, 2024

For measuring the maturity of a DevOps organisation, there are 4KM:

  1. Lead time
  2. Frequency of deployment
  3. Change failure rate aka MTBF
  4. Mean time to recovery (MTTR)

These indicators do not have to be accurate! They are a guide to help your software delivery process improve.

Lead time and frequency of deployment

How fast can you deliver a change? How often do you deploy?

Closely related since the smaller the change, the quicker you can deliver.

Low performers can take months to roll out a change! 🤦

Change failure rate

Days since last failure

This is often misunderstood, what we are looking for is customer impact.

When a CI pipelines fails, the customer is not impacted, then this is not a failure. Pipeline failures and general slowness should negatively affect your lead time.

If we do a canary deployment which fails, but the customer by & large is not impacted, then this should not be considered a failure.

This is not quite the same as a constructions site’s X days since failure, since we want to set a period of time, so we can work on improving our processes and deliver!

Mean time to recovery from a failure

How quickly can you recover from a failure, in which a customer was impacted.

Should be a small as possible, as it would lessen the impact of the failure.

In practice you roll forward, therefore MTTR should be the same as lead time in high performers.

What good looks like

High performers:

  1. Lead time is less than an hour - how long does it take to get a change into production?
  2. Deploy multiple times a day - how often do you deploy?
  3. Change fail rate is less than 10% - when a change is deployed, want percentage negatively impacts the customer?
  4. Mean time to recovery is less than a minute - how quickly can we make a fix?

Change fail rate as noted by the book Accelerate, might be higher in medium/high performers, since they are more likely to be experimenting than low performers. 😳

If you are not failing, you are not trying hard enough. However if you are making the same mistake, you are missing tests!