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Prioritizing Invisible Work There are work items that will give the team an operational boost and perhaps avoid a crisis, but that never make it to the top of the priority list—like build and deployment improvements, or paying down technical debt. For enabling work that is valuable but too invisible to be a priority, consider breaking it down. |
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Team Agility in a Post-Pandemic World COVID-19 has necessitated entirely remote environments, and people the world over have had to inspect their foundations of working, adapt to a new way of remote execution, and integrate their personal and professional lives more than before. Organizational leaders need to embrace a new outlook in four critical areas. |
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What’s the Problem with User Stories? Agile projects focus on very lightweight, simple requirements embodied in user stories. However, there are some problems with relying solely on user stories. They often don't contain enough accuracy for development, testing, or industry regulations. There's a better way to write detailed requirements that are still agile. |
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Ditch Your Logs for Better Monitoring Metrics Many teams use logs to track the behavior of applications, services, or platforms. But how actionable is that log data? There are better ways to parse that information and make it more visible, more useful, and easier to understand. Try converting your logs into metrics for a faster and more lightweight monitoring system. |
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Testing in the Dark Requirements only go so far in identifying areas to test. Sometimes testers are given no information at all, leaving it up to them to determine what to test. Don’t accept the need to indiscriminately test with no clear understanding. Your testing should be targeted, and these techniques will help focus your test effort. |
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Breaking Down Apache’s Hadoop Distributed File System Apache Hadoop is a framework for big data. One of its main components is HDFS, Hadoop Distributed File System, which stores that data. You might expect that a storage framework that holds large quantities of data requires state-of-the-art infrastructure for a file system that does not fail, but quite the contrary is true. |
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Leave No Tester Behind Creating comprehensive automated tests within a sprint can be a challenge. If the testers don't finish the automation and the rest of the team moves on, testers get left behind and can't catch up. You need some techniques to keep everyone together and ensure that all essential work is accomplished—including test automation. |
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Comparing Apache Hadoop Data Storage Formats Apache Hadoop can store data in several supported file formats. To decide which one you should use, analyze their properties and the type of data you want to store. Let's look at query time, data serialization, whether the file format is splittable, and whether it supports compression, then review some common use cases. |
