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New whitepaper: Database DevOps — 6 Tips for Achieving Continuous Delivery. Discover 6 tips for continuous delivery with Database DevOps in this new whitepaper from Redgate. In 9 pages, it covers version control for databases and configurations, branching and testing, automation, using NuGet packages, and advice for how to start a pioneering Database DevOps project. Also includes further research on the industry-wide state of Database DevOps, how application and database development compare, plus practical steps for bringing DevOps to your database. For one of our customers, a leading publisher of financial information, tradeoffs meant it was impossible to move beyond 10 refreshes a year i. This stuck them with problematic test data quality, recurring surges of undetected bugs later and later in the software development life cycle SDLC. All of these factors resulted in lethargic time-to-market and, inevitably, lost productivity. They turned to Delphix for a solution. Collecting, analyzing, integrating and delivering data causes most of the bottlenecks software developers face today. It can take days just to provision developers with one data environment they need before they can get down to work. Delphix makes data manageable and eliminates all of these delays. The Software Development Life Cycle SDLC comprises four main stages: Development, Testing, User Acceptance Testing UAT and Production Release. The later the stage in which a bug is caught, the more difficult, time-consuming and, as a result, the more expensive it becomes to root-cause it and fix it. Delphix enables two strategies. The first, we call shift-left: shifting the process of bug-catching from later to earlier stages i. The second, uprooting: catching more bugs at every given stage of the SDLC. The combined aim is to catch as many bugs, as early as possible, and in this way to reduce the resources that rework takes up. This translates into higher quality and speed at a lower cost. How does it happen? Delphix is a software that stores importantly, on hardware of any kind a highly compressed copy of production data. It then uses this golden copy to provide developers, testers anyone who needs one, really with virtual copies of any and every relevant dataset. This allows for 3 critical advantages. First, these are virtual and not physical copies of the data: they can be provisioned and rearranged refreshed with new production data, reset and synced with previous versions, etc. Secondly, the copies can be provisioned on a self-service basis, which eliminates the delays sometimes weeks caused by the bucket brigades of ticket requests and handoffs. Third: these are all full copies, neither subsets nor outdated versions of the data, which leads to exponential improvements in the quality and reliability of every phase of development and testing. With Delphix, developers started to set up full, virtual copies of the necessary data environments in minutes, and then reset them, refresh them, sync them up - all on a self-service basis, and still in a matter of minutes. This way, they were able to test their software projects more often, non-destructively, against exact copies of production data. Here is the result: The black columns show how many bugs were caught at each stage of the SDLC per release prior to Delphix, the red columns after Delphix was introduced. More bugs were caught uprooting and fixed at an earlier stage shift-left in the SDLC. Delphix enables the testing costs to shift-left into less expensive territory. In this case study more than 100 percent more bugs were discovered in Development. Delphix reduced bugs reaching the costly 50X UAT stage to less than one quarter. These real use case numbers show significant savings in bug testing and app delivery. Conclusion That is how the software development paradigm changes. Speedier, higher-quality data management allows for fewer resources to be allocated much more effectively. Discover 6 tips for continuous delivery with Database DevOps in this new whitepaper from Redgate. In 9 pages, it covers version control for databases and configurations, branching and testing, automation, using NuGet packages, and advice for how to start a pioneering Database DevOps project. Also includes further research on the industry-wide state of Database DevOps, how application and database development compare, plus practical steps for bringing DevOps to your database.
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