Extracting DORA metrics from Azure DevOps is complex and resource-intensive due to the limitations of Analytics Views and the extensive data manipulation required. Azure DevOps, a leading platform that integrates various phases of the development process, faces challenges in implementing DevOps analytics effectively. The extraction of DORA metrics, which quantify DevOps effectiveness through four key metrics—Deployment Frequency, Lead Time for Changes, Mean Time to Recover, and Change Failure Rate—requires significant effort, often akin to building a new product. The reliance on Power BI for data collection and the necessity for complex queries, coupled with the limitations in the types of data easily imported, make the process challenging. Furthermore, the unique structure of Azure DevOps complicates data aggregation and sharing, necessitating custom solutions for extracting meaningful metrics. The platform's inability to easily slice data by teams and the need for custom queries in Power BI add further complexity, suggesting that enterprises may need to consider commercial solutions for extracting DORA metrics effectively.