Your organization is doing DevOps, but it still takes several weeks to make simple changes to your production databases? Yikes. There are a myriad of excuses – you’re dealing with legacy data, there’s significant technical debt, you have inadequate automated tests (if any), database changes are handled by “the data team”, you don’t have the tooling, and many more – but they’re all starting to ring hollow. Data should be an important corporate asset, yet in practice it is rarely treated that way. Now it’s time to “go the last mile” and bring databases into your DevOps strategy.
Database DevOps requires a significantly different mindset than traditional data management or just agile software development. Data professionals need to embrace changing requirements, light-weight modelling strategies, automated regression testing, continuous database integration and continuous deployment strategies. Agile developers need to embrace fundamental database skills, realizing that just because you’ve encapsulated database access doesn’t mean you can ignore the design and implementation of what’s been encapsulated. Then of course for operational databases we need real-time monitoring, resilient architectures, and security.
The techniques and support tools exist, and in this workshop we will explore the challenges around Database DevOps and what you need to do to overcome them.