Azure Data Factory is a great orchestration tool in the cloud, is mature and for a while now with us. Authoring the pipelines and other objects as a developer via browser (v2), working appropriately with branches, debug mode and understanding an integration with Git repo might be a bit tricky. If you add to this, the need for deployment to different environments, adf_publish branch and why actually two methods of deployment exist - these things can be overwhelming. Learn the best ways of working with ADF, scripts and tools for deployment and differences between them. See, how to automatically (not via UI) generate/export arm template files and use them in further steps in Azure DevOps, if you prefer using this way.
Blogger, speaker, #sqlfamily member. Microsoft Data Platform MVP. Data passionate, Data Engineer and Architect. Over 20 years of programming and experience with SQL Server databases (since 2000 version) he confirmed by certificates MCITP, MCP, MCTS, MCSA, MCSE Data Platform & Data management & analytics. He worked both as a developer and administrator of big databases designing systems from the scratch. Recently focused on Data Platform in Azure as a certified (Azure Dev-Ops Engineer Expert, Azure Developer Associate) Data Engineer and Azure Architect. Passionate about optimization of database systems, an advocate of code transparency, open-source projects and automation, DevOps and PowerShell fan. Since 2015 he has been living and working in the UK. Currently professionally associated with Avanade, an international consulting company. For many years tied with Data Community Poland (former PLSSUG), between 2012-2018 acted as a Member of the Audit Committee. He worked a couple of years as a volunteer and now as a co-organizer and speaker of the biggest SQL Server conference in Poland (SQLDay). An originator of the "Ask SQL Family" podcast and founder of SQLPlayer blog. Privately happy husband and father of two wonderful girls.
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