Emc IP Holding Company LLC

Emc Corporation

Gil Ratsaby

Dan Aharoni

Hagay Dagan

Julio A Colon

Amnon Naamad

Hui Wang

Sergey Rytenkov

Ilies Idrissi

Ophir Aharoni

Richard F Otte

Marvin F Miller

Iliès Idrissi

Philipp Smirnov

Almog Tabak

Taojun Wu

A method includes (a) receiving workload data for a data storage system, the data storage system having a plurality of processing cores, the data storage system being configured to operate according to any of a plurality of profiles, each of the plurality of profiles having a respective assignment of respective cores of the plurality of cores to particular storage roles of the data storage system, (b) for each profile of the plurality of profiles, simulating operation of the data storage system running a workload based on the received workload data using the assignment of respective cores of the plurality of cores to particular storage roles for that profile, thereby producing a set of utilization scores, (c) selecting a profile of the plurality of profiles based on the set of utilization scores, and (d) outputting an indication of the selected profile for use by the data storage system.

Intelligent core assignment

Determining cumulative workload skew is described. Measurements for one or more logical devices are determined. The set of measurements include, for each of N storage tiers, a workload measurement identifying workload directed to the single tier, and a capacity measurement identifying an amount of data stored in the single tier. N points may be determined using the measurements. Each point corresponds to a different storage tier and has a first coordinate identifying a cumulative percentage of data portions stored in the storage tier and all other tiers having a higher performance ranking than the one storage tier, and a second coordinate denoting an aggregated percentage of total workload directed to the foregoing cumulative percentage of data portions. A curve representing a cumulative workload skew may be determined using these N points and a point of origin.

Techniques for determining workload skew

Described are techniques for processing collected workload and performance data. Components of a component category are selected, filtering criteria is specified, the filtering criteria is applied to the collected workload and performance data for the components selected and thereby generating filtered data results, and the filtered results are viewed. The filtering criteria may include a first operation and a first set of one or more metrics included in the collected workload and performance data for the components selected. The first operation may be applied to the first set of one or more metrics and may be selected from a plurality of operations. The plurality of operations may include at least one arithmetic operation, at least one logical operation and at least one relational operation.

Techniques for filtering workload and performance data

A method, apparatus and computer program product for providing pre-calculated performance simulation is presented. Performance simulations for a storage system are provided by selecting a subset of system configuration options from a large set of system configuration options. Simulation results for the subset of system configuration options are pre-calculated. The simulation results for the subset of system configuration options are loaded on a portable device. System configuration requirements for a customer are received and at least one system configuration option is selected from the subset of system configuration options based on the simulation results and the system configuration requirements for a customer.

Pre-calculated performance simulation

A target data storage system is simulated. A source configuration is received. First activity data is received representing workload for the source configuration. A target data storage system configuration for one or more target data storage systems is created. The target data storage system configuration is modeled including determining a simulated workload for components of the target data storage system configuration based on the first activity data. A utilization map is displayed in a user interface indicating component level utilizations of components of the target data storage system configuration based on the simulated workload. A data movement optimization for the target data storage system configuration is simulated. A second utilization map is displayed indicating updated component level utilizations for the target data storage system configuration which have been revised to model the simulated data movement optimization for the target data storage system configuration.

Data storage system modeling

A tool and/or other system is provided that simulates write pacing in connection with a requested operation for a storage system to allow an analysis of the effect of the requested operation on the storage system. In an embodiment, the storage system may be an RDF system operating in an asynchronous transfer mode (e.g., an SRDF/A system) and the requested operation may correspond to a snapshot copy operation of the R2 device and/or a slowdown in one of the storage devices and/or the links therebetween while the SRDF/A system is operating. The system described herein enables simulation of a storage system to take into account an effect of write pacing and may be advantageously used to anticipate and/or otherwise minimize or avoid operations at a particular time that would create undesired initiation of write pacing.

Write pacing simulation tool

Described are techniques for identifying a data storage volume exhibiting a performance problem. First information indicating a sorted ordering of a plurality of maximum response times is displayed for a plurality of data storage volume. A first of the plurality of data storage volumes having a largest one of the plurality of maximum response times is selected. In response to such selecting, additional information is displayed in the user interface about the first data storage volume. The additional information includes at least one workload or performance characteristic of the first data storage volume.

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Boston, MA, United States of America

Gil Ratsaby