Shift Left

Defining the term shift left to mean testing earlier in the development cycle feels antiquated since waiting until development is “complete” before testing is a plain ol’ anti-pattern at this point.

A better definition could be testing earlier and more frequently. Writing tests each sprint, and running those tests with every commit.

Perhaps better still is thinking of shift left as a movement of testing to earlier in the pipeline. Favor unit tests, which typically run in the pipeline first and fast. Heavier-weight tests, such as UI based and end-to-end tests, which are typically harder to write, slower to run, and run later in the pipeline, do have a place but should be used sparingly.

Another way to look at this is that shift left means shifting down the testing pyramid.

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Tags: deliverypipeline, shiftleft, Testing, unittesting

How 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.

 

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Tags: accelerate, ci, cicd, continuousdelivery, continuousdeployment, continuousintegration, deliverypipeline, devops, metrics, stateofdevops