Many – if not most – organizations have treated the deployment of code to databases differently than they do other code stacks. This is in part because few organizations have dedicated “Database Developers”, as they do java, python, swift, or other ‘specialized’ software engineers.
It is also because databases have not traditionally been easily amenable to the standard software deployment processes or toolsets. These differences can lead to occasional deployment mishaps that can result in slow deployments or costly mistakes that are difficult to roll back. Ironically, making the case to justify an investment in database deployment automation is not necessarily an easy task because these mishaps, though costly, are viewed simply as process failures due to resource or team “discipline” challenges. The truth is much deeper than that.
This presentation describes MedImpact’s journey to improve database deployment throughput and quality – a journey that required people, processes, and tooling changes. It also describes the justification process that finally enabled the investment, and the improvements MedImpact has experienced since.
Learn more about MedImpact’s journey
Read our blog: Journey to Database Change Automation
View the case study: MedImpact’s Journey to Database Change Automation
