Abstract: Techniques for evaluating data sets for compression processing may include: receiving first information for a data set, the first information including I/O activity information for the data set, a service level objective for the data set, and a size of the data set; determining, in accordance with the first information, whether the data set meets criteria indicating a specified level of importance and a specified level of I/O activity; responsive to determining the data set meets the criteria, sending second information identifying one or more storage objects of the data set to a compression engine, wherein the one or more storage objects of the data set are identified as having the specified level of importance and at least the specified level of I/O activity; and performing processing, by the compression engine using the second information, to determine whether to compress first data stored in the data set.

Abstract: Techniques for evaluating data sets for compression processing may include: receiving first information for a data set, the first information including I/O activity information for the data set, a service level objective for the data set, and a size of the data set; determining, in accordance with the first information, whether the data set meets criteria indicating a specified level of importance and a specified level of I/O activity; responsive to determining the data set meets the criteria, sending second information identifying one or more storage objects of the data set to a compression engine, wherein the one or more storage objects of the data set are identified as having the specified level of importance and at least the specified level of I/O activity; and performing processing, by the compression engine using the second information, to determine whether to compress first data stored in the data set.

Abstract: Techniques for identifying I/O workload patterns may include monitoring key performance indicators (KPIs) for a monitoring period; and at the end of the monitoring period, performing processing including: determining whether there have been a specified number of occurrences of a predefined event with respect to a data portion of the application, wherein the predefined event is a violation of an application KPI for the application and also a violation of at least one of a plurality of data storage KPIs for the data portion of the application; and responsive to determining that there have been the specified number of the occurrences of the predefined event with respect to the first data portion of the application, recording a pattern of I/O workload for the data portion in accordance with the occurrences of the predefined event. Hints, such as affecting data movement and/or compression, may be generated based on detected patterns.