Shaun Abram
Technology and Leadership Blog
Subscribe to RSS FeedHow much is your slow lead time costing you?
In a previous blog post, I discussed slow build times and estimated the associated costs. The build process is only one part of getting software out the door however.
Lead time is the time it takes to go from code committed to successfully running in production. This will include the build time we covered in the previous blog post, as well as all the other things required to get your code into users hands such as testing & deployments. This article focuses on the costs of that lead time.
Using the example of a team of 10 engineers, I estimate that the costs of a slow (one week) lead time could be the approximate equivalent of more than 3 engineers, or $400,000 per year. And I think it’s entirely possible that is on the low side since there are other costs that are just difficult to estimate. Imagine how much more you could achieve with 3+ extra engineers on the team.
Charity Majors goes further (discussed below) and suggests that reducing the lead time to hours could save the cost of 5 engineers on such a team. I was initially skeptical on that claim, but after trying out these estimates, she think may well be more accurate that my possibly over-conservative math.
Thanks
A big thank you to my former colleagues Dave Taubler, Abhijit Karpe, Josh Outwater and Steve Mauro for providing feedback and input on this article.
Most of the feedback took issue with some aspect of the estimates, which is fair, but the common theme seemed to be that everyone agreed that there is a very real cost to slow lead times, that it is high, and that using data where you can and estimates where needed is a good way to surface and highlight that cost.
Tags: accelerate, ci, cicd, continuousdelivery, continuousdeployment, continuousintegration, deliverypipeline, devops, metrics, stateofdevops
How much is your slow build costing you?
Slow builds are a pain, but how much do they really cost? How do you compare the benefits of reducing your build times against a new user-facing feature that generates real revenue, for example?
Your slow build could be costing you up to $1 per minute per build per engineer, based on the estimates shown below. So, even before you factor in CI infrastructure costs, slow build times can very quickly add up. In the example below, a team size of 10, each doing 5 builds a day, and each with a 30 minute build time, we calculate the cost could be up to $375,000 per year in waste.
This post and the calculations used in it are based on the approach taken by “Prioritizing with Cost of Delay” by Jeff Palmer. “Quantifying the Costs of Builds“, by Hans Dockter @ Gradle, also covers some of the same ground in similar and more comprehensive ways.
Tags: build, ci, cicd, continuousdelivery, continuousdeployment, continuousintegration, devops, metrics
Book Summary: Accelerate
Accelerate: Building and Scaling High Performing Technology Organizations is a book by by Nicole Forsgren, Jez Humble and Gene Kim. It is a follow on from the State of DevOps Reports that Forsgren and Humble used to publish (and which I wrote about before in Development and delivery practices for team success). I highly recommend buying the book, but here are some chapter summaries for the highlights.
Tags: accelerate, books, cicd, devops, metrics, mttr, stateofdevops, summary
SRE Metrics
A very quick post on some of the most commonly used SRE metrics: The Four Golden Metrics, and RED & USE.
Tags: 4goldenmetrics, metrics, sitereliabilityengineering, sre
Book summary: Distributed Systems Observability
“Distributed Systems Observability” is a book from Cindy Sridharan (find her on twitter, and medium), available as a free download here (registration required). At a little over 30 pages and 8,000 words, it is not a difficult read, and I definitely recommend it.
Tags: itestinprod, logs, metrics, observability, production, summary, Testing, testinginproduction, tracing