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Key Factors for an Efficient System Architecture Design Software architecture is all about trying to bring structure to areas that can’t be structured easily. When an architect designs a system, service, or feature, they are formulating a comprehensive solution to a unique problem. The concepts here help create a scalable, accessible, secure, and cost-friendly architecture. |
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What’s New in Apache Cassandra 4.0 Apache Cassandra is an open source, distributed NoSQL database based on the wide column model. The highly scalable, highly available database is great for handling large amounts of data. There is no set release date yet for the next version, Cassandra 4.0, but we do already know about several new features. |
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Figuring Out Your Regression Testing Strategy When your application is scheduled to go to production, the development team may be asked what their regression testing strategy is. This is a perfectly reasonable question, but a lot of people have a hard time answering it. Don't overcomplicate it. Analyze your process, look at the other testing, and put it together. |
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DevOps in the Trenches: Get Started with Metrics DevOps initiatives often start with one silo seeking to be more collaborative with others. This "DevOps in the trenches" isn't ideal, but it is a way to get DevOps bootstrapped and begin seeing benefits. Here are some tips for how to get started doing DevOps based on what role you're in, with key metrics to help. |
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Fueling Innovation through Design Thinking Organizations must embrace new technologies in their product engineering efforts to stay ahead of the curve. But there is another quality that will be key this decade to giving product teams a proactive advantage: design. Design thinking should be embraced not just by designers, but by everyone involved with a product. |
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Machine Learning and Deep Learning: What's the Difference? Many people think that machine learning and deep learning are each just a fancy way to say artificial intelligence, but that is a misconception. Both terms represent subsets of AI technology, but they are different, and their differences dictate the functionality and application of these two software solutions. |
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Pros and Cons of Codeless Test Automation To create automated tests for software applications, testers have historically needed to be able to code in programming languages. Codeless testing eliminates the need for scripting from scratch every time, but in addition to its advantages, there are also some drawbacks. Is codeless automation right for your team? |
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2 Ways to Get Better at Test Automation Many people in testing roles want to grow their skills and learn to build some tests with code. But no matter how well you test, automation is programming work. If you want to get better at automation, your best bet is to get into a role where you are dealing with code. Here are two ways you can break in and learn. |
