Apparatuses and methods are provided to generate customizable databases and/or analyze performance. In an example embodiment, a method of generating customizable databases is provided. The method includes receiving a calculation expression relating to one or more defined characteristics. The calculation expression may be defined by a user. The method also includes loading data into a data warehouse. The data includes at least one of the one or more defined characteristics. The method further includes generating a data cube based on the received calculation expression and the data loaded into the data warehouse. The data cube includes an accessible table. A corresponding apparatus is provided. Additional method and apparatus to analyze performance are also provided.

Performance testing a data storage system includes recording operating parameters and performance data as the data storage system executes performance tests over a test period, the performance data including one or more measures of a performance characteristic (e.g., latency) across a range of I/O operation rates or I/O data rates for each of the performance tests. Subsets of recorded operating parameters and performance data are selected and applied to a machine learning model to train and use the model, and the model provides a model output indicative for each performance test of a level of validity of the corresponding performance data. Based on the model output indicating at least a predetermined level of validity for a given performance test, the performance data for the performance test are incorporated into a record of validated performance data for the data storage system, usable for benchmarking, regression analysis, hardware qualification, etc.

The present disclosure provides methods, systems, and non-transitory computer readable media for performing data transfers with improved error encoding. The methods include receiving a request for data transfer from a source medium in the data storage system to a destination medium in the data storage system, wherein the data storage system comprises a computer cluster and a storage cluster; determining whether the source medium and the destination medium are within the storage cluster; based on the determination of whether the source medium and the destination medium are within the storage cluster, transferring the data from the source medium to the destination medium, wherein: the data is transferred without performing error correcting code check when the data is transferred within the storage cluster, and the data is transferred with an error correcting code check when the data is transferred between the computer cluster and the storage cluster.

In an approach for generating differentiated workload telemetry data, a processor corresponds one or more services with a workload related telemetry generating an event emitter. A processor performs a correlation analysis of corresponding relationship and connection among connected resources and current traffic into and out of the one or more services. A processor labels domain context for each telemetry event. A processor communicates each telemetry event to a global event handler. A processor performs a cross-correlation in real-time of telemetry data with the global event handler. A processor updates a real-time differentiated workload report.

An interface receives reported information from a system on chip (SOC), where the reported information includes: (1) hardware-reported information that is reported by a hardware functional module included in the SOC and (2) firmware-reported information that is reported by a firmware functional module included in the SOC. A processor receives one or more display settings and generates visual information based at least in part on: (1) the one or more display settings, (2) the hardware-reported information, and (3) the firmware-reported information. The visual information is displayed via a display.

Event records from multiple computing devices are received at a managing unit. Individual event records include an event identifier field including an event identifier identifying a first event associated with a particular computing device, a parent event identifier field identifying a parent event that initialized the first event, and an entity identifier field including an entity identifier identifying the particular computing device. The managing unit generates log records associated with event identifiers included in the event records. The log records include state fields indicating a state of a particular event associated with a particular event identifier. Based on a correlation of the event and log records, the managing unit determines at least two computing devices associated with events resulting in an error state, and identifies parent events that initialized the events with errors. The managing unit generates a report linking the parent events to the events having an error state.

A method performed by a computing device, of configuring a new design of a new data storage system (DSS) having initial configuration parameters is provided. The new design includes an initial plurality of storage drives. The method includes (a) collecting operational information from a plurality of remote DSSs in operation, the operational information including numbers of writes of various write sizes received by respective remote DSSs of the plurality of remote DSSs over time; (b) modeling a number of drive writes per day (DWPD) of the initial plurality of storage drives of the new DSS based on the collected operational information from the plurality of remote DSSs and the initial configuration parameters; (c) comparing the modeled number of DWPD to a threshold value; and (d) in response to the modeled number of DWPD exceeding the threshold value, reconfiguring the new DSS with an updated design.

A method and system for auto live-mounting database golden copies. Specifically, the disclosed method and system entail reactively auto live-mounting golden copy databases on hosts or proxy hosts based on the operational state of one or more database hosts and/or one or more assets (or databases) residing on the database host(s). Should a database host prove to be unresponsive, through periodic monitoring, databases residing on the database host may be brought back online on a proxy database host using stored golden copies respective of the aforementioned databases. Alternatively, should a given database on any database host exhibit an operational abnormality (e.g., an error, failure, etc.), the given database may be brought back online on the database host or a proxy database host using a stored golden copy respective of the given database. Accordingly, through the disclosed method and system, database outages may be minimized.

The present disclosure provides a method for information storage and a system thereof, which adapts to a data storage system. A monitoring unit is configured to detecting and monitoring operations of a storage node in the data storage system to generate corresponding one and more monitoring data. A recording processor is configured to receiving the one or the plurality of monitoring data, and rendering one or a plurality of logs according to the difference of content of the one or the plurality of monitoring data. The adjustment mechanism is performed according to the stored logs, thereby the amount of large data generated during monitoring is effectively reduced.

An illustrative method includes detecting, by a cloud based storage system services provider based on a problem signature, that a storage system has experienced a problem that is associated with the problem signature; and deploying, without user intervention, one or more corrective measures that modify the storage system to resolve the problem.