The question is simple: In a software team using git and feature branching, what's the best way to incorporate finished work back to your main line of development? It's one of those recurring debates where both sides have strong opinions, and mindful conversation can sometimes be hard (for other examples of heated debate see: The Internet). Should you adopt a rebase policy where the repository history is kept flat and clean? Or a merge policy, which gives you traceability at the expense of readability

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One question that every team faces when moving to Git is what development workflow to use. Since every team is different and has different requirements, there is no one-workflow-fits-all approach. However, there is one rule all teams should follow when looking for a new workflow to adopt: Keep it simple. Doing so will reduce the number of mistakes people can make, and will help with adoption. On the Stash team, we've adopted one of the simplest Git workflows possible. And since so many of you

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Last week, we hosted a webinar on git, focusing on workflows and practices you can adopt when you move to git. We discussed two of the more popular branching models used internally at Atlassian in depth, and gave practical examples on how git can allow you to reduce friction and increase the efficiency of your team. Watch the recording, share it with your team If you're evaluating the move to git and you want to get familiar with distributed version control concepts, then this webinar will

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We've all been there. Those times where we realise that we've been sitting around arguing for hours over the small stuff, because we've forgotten about the bigger, more important stuff. Or to bring it into the realm of digital products: whether that interface should still have an accordion menu or should we change it to a set of tabs. But we've already shipped, and customers are used to it being this way! We can't it change now... can we? Wouldn't it be nice if we had something that helped us steer

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Alerts, anomalies & automated canaries at DevOps Dojo hangout #4

For our 4th installment of the DevOps Dojo hangouts, we corralled monitoring mavens from Atlassian, LogicMonitor, Netflix, and Metafor for an hour-long geek-out that got quite animated! Did you know, for example, that the very notion of distinguishing application monitoring from infrastructure monitoring is controversial? I did not. Or ever thought about the effects of human bias when looking for anomalies in monitoring data? Personally, it never crossed my mind. There's lots for your brian

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The science that drives Uber

Since its launch in 2010, Uber's engineering team has grown from four to 70. You might be surprised to hear that today, only six of those engineers are focused on mobile; the rest are responsible for the science that is helping Uber solve transportation problems globally (18 countries, 45 cities, every time zone, and a dozen languages, to be exact). Using Python and JavaScript, Uber's science team has built a logistics framework that – in addition to facilitating delivery of ice cream, roses,

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