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Measuring Developer Productivity

Most metrics for measuring developer productivity, such as lines of code or issues closed, are notoriously ineffective. But the research in the excellent State of Devops report shows that, rather than focusing on local metrics and individual developer performance, it is better to look at overall development and delivery practices. Specifically, there are metrics that predict and reflect a team’s ability to successfully deliver working software into production, including deployment frequency, and the mean time to restore service after an incident. This articles discusses why some metrics are useless, and takes a closer look at the recommendations in the 2019 State of Devops report.

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Report Summary: Accelerate State of DevOps 2019

This is an abridged version of The Accelerate State of DevOps Report 2019; essentially a cut and paste of the most salient parts. The original is about 18,000 words; This is about 2,500 words.

I highly recommend reading the original in its entirety, if you have time, and I’m a big fan of the Accelerate book too. As with all the other summaries I create, this just as as way to help me digest and understand an excellent article.

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SRE vs DevOps

I’m really enjoying the Seeking SRE book. Chapter 12 covers SRE vs DevOps; a community sourced compare and contrast type discussion.

My favorite description is from Thomas Limoncelli, who suggested that:

DevOps engineers focus on the SDLC pipeline with occasional responsibilities for production operations. SREs focus on production operations with occasional responsibilities for the SDLC pipeline.

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“Ship It!” talk at the Boise Code Camp

Slides for my “Ship It!” talk at the Boise Code Camp in Boise State University today: https://www.slideshare.net/shaunabram/ship-it-boise

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Continuous integration / Continuous Delivery / Continuous Deployment

The terms Continuous Integration, Continuous Delivery and Continuous Deployment can still confuse. Even Jez Humble, author of the book Continuous Delivery commented that there is “confusion around the terms continuous delivery versus continuous deployment and my own thinking and definitions have changed”.(1)

This is my attempt to distinguish, based on the sources listed below.

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Dynamically set Jenkins node

This post explains how to dynamically/programmatically set the node a Jenkins/Hudson job will run on. This is relatively easy to do statically, using the NodeLabel Parameter Plugin, but trickier to do programmatically.

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Maven archetypes to create your project folder structure

Maven archetypes are useful for many things, including creating a folder structure to start with, even if you aren’t planning to use maven as your build tool. See a list of available archetypes here.
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Running Jenkins jobs sequentially

I am a huge fan of the Jenkins continuous integration tool, using it not just for continuous integration, but also continuous delivery, server monitoring and performance testing.

Although using Jenkins is normally a breeze, I recently had a need to run several Jenkins jobs sequentially and it proved a little trickier than expected, so I thought worth posting about.

Basically, I wanted to call a database backup job before calling the deploy build job, which obviously shouldn’t be done in parallel. After a bit of research, I found a number of ways to have Jenkins run jobs sequentially.
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