Martin Hinshelwood: Migration Azure DevOps Server to the Cloud - Episode 302

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Martin is a passionate agile leader with a track record of inspiring, encouraging, and igniting momentum. Featured speaker, author, and industry thought leader, Martin has a strong track record of helping organizations build a vision and execute evolutionary and revolutionary change. His deep technical knowledge, business insight, and experience drive impactful change for organizations. Technologist turned agilist, Martin successfully helps organizations decentralize, democratize, and evolve their way of work to build extraordinary processes and drive organizational change through culture, technology, and teamwork. He’s been recognized by Microsoft as a Microsoft MVP, and he is the maintainer of the open-source Azure DevOps Migration Tools. Topics of Discussion: [2:59] Martin’s career journey. [4:51] What Martin has learned as an MVP for 15 years. [5:59] If you’re not good at something, do it more. [6:52] Azure DevOps Migration tools. [10:11] Martin adopted platform engineering to streamline processes and reduce costs. [14:31] What you should know before using Martin’s tools. [21:55] It’s not either/or between Microsoft migration tools and Azure DevOps migration tools. [27:00] What made TFS unique. [20:03] TFGit. [30:02] The process used in your source and target, and what challenges might people expect? [31:44] Limitations of migrating data from old TFS to new Azure DevOps using Microsoft tools. Mentioned in this Episode: Clear Measure Way Architect Forum Software Engineer Forum Programming with Palermo — New Video Podcast! Email us at programming@palermo.net. Clear Measure, Inc. (Sponsor) .NET DevOps for Azure: A Developer’s Guide to DevOps Architecture the Right Way, by Jeffrey Palermo — Available on Amazon! Jeffrey Palermo’s Twitter — Follow to stay informed about future events! GitHub Migration Tools for Azure DevOps Martin — Scrum Naked Agility Agile Actually Podcast Want to Learn More? Visit AzureDevOps.Show for show notes and additional episodes.


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