Discovering application dependency on data and storage is a key prerequisite for many storage optimization tasks such as data assignment to storage tiers, storage consolidation, virtualization, and handling unused data. However, in the real world these dependencies are rarely known, and discovering them is a challenge because of virtualization at various levels and the need for discovery methods to be non-intrusive. As a result, many optimization tasks are performed, if at all, without the full knowledge of application-to-storage dependencies.   This paper presents a non-intrusive application-to-storage discovery method, and while it is built on our prior work, the storage discovery described here is entirely new. We used this discovery method in two production enterprise environments, consisting of about 323 servers, and we show how the discovered data enables three optimization tasks. First, we relate application criticality with storage tiers. Second, we find unused storage devices and we show how this information together with storage consolidation can be used to achieve power savings of up to two orders of magnitude. Third, we identify opportunities for database storage optimization.
['Nikolai Joukov', 'Birgit Pfitzmann', 'HariGovind V. Ramasamy', 'Murthy V. Devarakonda']
Application-storage discovery