September 18, 2014
Ignition’s Rachel Chalmers: Use Grassroots in the Enterprise
Written by activist Saul Alinsky, "Rules for Radicals" is a series of lessons aimed at the Seventies generation of activists. The book has s...
Heavybit member company LaunchDarkly held their Test in Production Meetup in the Heavybit Clubhouse on January 10th. In this session the focus was on ‘how’ teams test in production. If you’d like to attend future Test in Production Meetups in person, sign up here.
Josh Wills, Engineer at Slack
Josh started our Meetup with a short talk on deploying machine learning models into production. He’s worked as the Director of Data Science at Cloudera, he wrote the java version of Google’s AB testing framework, and he recently held the position of Director of Data Engineering at Slack. In his opinion the most important question is: “How often do you want to deploy this?” You should never deploy a machine learning model once. If the problem is not important enough to keep working on it and deploy new models, then its not important enough to pay the cost of putting it into production in the first place.
Watch his talk to get his thoughts on testing machine learning models in production.
Maria Verba, QA Automation Engineer at Handshake
Maria discusses how and why teams at Handshake test in production. In her role as QA Automation Engineer, she is focused on making sure her organization ships a product that customers love to use, as well as supporting the engineers with anything test related.
Watch her talk to learn how her team tests in production. She covers what requirements her team has put in place to test safely, and some specific examples of when testing in production is better than in pre-production.
Cindy Sridharan aka @copyconstruct
In December 2017, Cindy wrote an article about testing microservices. She wrote it in response to an article that showcased a team’s incredibly complex testing infrastructure. The piece described how a team built something that helped their developers run a lot of tests very quickly. And while it helped tremendously, Cindy wondered why it had to be so complex.
“The whole point of microservices is to enable teams to develop, deploy and scale independently. Yet when it comes to testing, we insist on testing *everything* together by spinning up *identical* environments, contradicting the mainspring of why we do microservices.”
Check out her talk to see how she recommends testing microservices—how to think about testing, what to consider when setting up tests, and other best practices.
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