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There are more than 10,000 enterprises across the globe that rely on a data stack that is made up of multiple distributed systems. While these enterprises, which span a wide range of verticals — finance, healthcare, technology, and more — build applications on a distributed big data stack, some are not fully aware of the performance management challenges that often arise. This piece will provide an overview of what a modern big data stack looks like, then address the requirements at both the individual application level of these stacks (as well as holistic clusters and workloads), and explore what type of architecture can provide automated solutions for these complex environments.