Abstract: An efficient linear technique is used to determine allocation of tiered storage resources among data extents based on system performance and SLOs. Efficiency is achieved by first determining a system performance boundary condition via hardware performance modeling under desirable system performance zones. SLOs are then balanced and SLO achievement improved by exchanging workload activities among SG donors and SG receivers while system performance boundary conditions are maintained. Remaining unutilized capacity is the uniformly distributed to further improve SLO achievement.

Abstract: Described are techniques for configuring data storage. Criteria identifying limits is received for a plurality of storage tiers for one or more logical devices. The storage tiers include a first storage tier and one or more other storage tiers where the first storage tier is higher performing than the other storage tiers. First processing is performed to determine a first set of data portions of the logical devices to be stored on physical devices of the first storage tier subject to limits included in said criteria. First processing includes determining scores for data portions of the logical devices. Each score is calculated using one or more metrics including a first metric weighted based on an expected I/O size. The data portions are ranked in accordance with the scores. The first set of data portions stored in the first storage tier is selected based on the score ranking.

Abstract: A write operation writes first data to a target logical address range included in a first logical address range of a virtually provisioned device. It is determined that physical storage is not allocated for the target logical address range. First processing is performed to allocate a first portion of physical storage having a first corresponding logical address subrange that includes the target logical address range. The first portion is allocated from a physical device included in a first storage tier. The first processing includes selecting the first storage tier from multiple storage tiers in accordance with selection criteria including metrics characterizing an expected workload or level of activity for the first corresponding logical address subrange of the virtually provisioned device. Mapping information is updated to indicate that the first corresponding logical address subrange of the virtually provisioned device maps to the first portion of physical storage.

Abstract: Described are techniques for automated compression and/or decompression of data. Idle counters are received for data portions which indicate a level of inactivity with respect to idle criteria for the data portions. Compression criteria is received specifying conditions for determining whether a data portion is a candidate for data compression. The compression criteria includes a time compression threshold indicating a minimum amount of time that a data portion has been deemed idle with respect to said idle criteria. A data portion that qualifies as a candidate for data compression has an associated idle counter indicating an inactivity level that is greater than the time compression threshold. Processing determines whether a first data portion is a candidate for data compression in accordance with the compression criteria. If the first data portion is determined as a candidate for data compression, compression processing is performed for the first data portion.

Abstract: Described are techniques for performing storage optimizations in a system. The optimizations may include a data movement optimization. First processing may be performed by a first component to determine whether to automatically perform the data movement optimization for devices included in one or more data storage systems. The first component may be external with respect to the data storage systems and may not be included in any of the data storage systems. As a result of performing the data movement optimization, a first portion of data is automatically moved from a first of the devices to a second of the devices. The first and second devices may have different performance classifications. Additionally, automated discovery processing may be performed to determine performance classifications for devices of the data storage systems and/or determine physical device dependencies.