Modern DevOps pipelines, which consist of eight major stages, often encounter bottlenecks that can impede productivity and delay critical updates or bug fixes. To address these issues, it is essential for DevOps teams to utilize data analytics across the entire application delivery lifecycle to identify and alleviate bottlenecks, thereby enhancing team velocity and code quality. By aggregating and analyzing data from various tools, teams can gain a comprehensive view of their processes, enabling them to make informed decisions and implement continuous improvements. This approach not only streamlines the release process but also aligns technical and business goals, fostering innovation through the principle of "fail fast, fail small, fail cheap." Through these strategies, DevOps teams can effectively manage bottlenecks and ensure that application delivery contributes positively to business objectives.