Emc IP Holding Company LLC

Emc Corporation

Dell Products Inc.

Mark Adam Arakelian

Debra Robitaille

Venkat Reddy

Tamilarasan Janakiraman

Kannan Subbaraman

Hanna Yehuda

Robert Anthony Lincourt, Jr

Christopher Chaulk

Rony R Baenziger

Sindhura Chamala

Gary K Roberts

Michael J McCarthy

David Biernacki

Steven Teng

Ju-Lien Lim

JoAnne Hubbard

Parthasarathi Ilangovan

Matthew Eaton

David S Shaffer

Belagapu Kumar

Sivaram Selvam

Jeff Phillips

Suhas K B

Kiran Kumar G Ramegowda

Gayatri Singh Balaji

Katarzyna Leskow

Belagapu Pradeep Kumar

Santosh Govindrao Bhandiwad

A boot image is modified to require authentication based on stable system values that are uniquely associated with a storage array. The stable system values may be used as a key to decrypt a password. The modified boot image will not allow booting to proceed without the decrypted password. The password cannot be decrypted based on different stable system values such as the stable system values of other storage arrays.

Authenticated boot to protect storage system data by restricting image deployment

A workload manager uses on-band and off-band metrics to select a host server in a cluster to handle a connection request. The on-band metrics include CPU usage, memory usage, and vulnerability metrics. The off-band metrics include hardware component error logs. Utilization and vulnerability scores are calculated for each host server from the on-band metrics. A reliability score is calculated for each host server from the off-band metrics. A health score for each host server is calculated from the vulnerability and reliability scores. The health score is used to exclude unhealthy host servers from consideration. A priority score is calculated for each host server from the utilization, vulnerability, and reliability scores. The host server that has not been excluded and has the greatest priority score is selected to handle the connection request.

Intelligent system to prioritize servers for envisaged requests

An apparatus comprises at least one processing device coupled to memory. The at least one processing device is configured to obtain a secured disk image comprising an encrypted manifest file, an encrypted install binary and a plurality of other files. The at least one processing device is further configured to obtain a certificate corresponding to the secured disk image and to derive a public key based at least in part on the certificate. The at least one processing device is further configured to decrypt the manifest file and the install binary based at least in part on the public key and to validate checksums for respective ones of the plurality of other files against corresponding checksums contained in the decrypted manifest file. The at least one processing device is further configured to execute the decrypted install binary responsive to validation of the checksums for the respective ones of the plurality of other files.

Virtual host upgrade using a secured disk image

A method of providing an error occurrence estimate for a proposed software update, before the proposed software update is created, includes training a learning process to cause the learning process to learn a correlation between the complexity of the previous software updates and the error occurrences of the previous software updates. The complexity information may include the number of lines of code and the number of check-in operations that occurred in connection with creation of the previous software updates. The trained learning process is then provided with expected complexity information of a proposed software update, and used to generate an error estimate including the number of errors that are likely to occur, the severity of the errors that are likely to occur, and the amount of software developer time that should be expected to be incurred to correct the errors.

Method and apparatus for predicting errors in to-be-developed software updates

A data processing device includes persistent storage and a software development manager. The persistent storage stores a code repository. The software development manager generates commit impact information based on: pre-commit code for a code base stored in the code repository, and dependency data based on committed code of the code base; displays a pre-commit analysis graphic user interface (GUI) reflecting the commit impact information and testing information for the pre-commit code; obtains, using the displayed pre-commit analysis GUI, reviewer feedback regarding approval of the pre-commit code; makes a determination, based on the reviewer feedback, that the pre-commit code has been approved; in response to the determination: performs limited testing of the code base based upon the dependency data to obtain testing results; and commits the pre-commit code to the committed code when the testing results match a predetermined behavior.

System and method for managing a code repository

A method, computer program product, and computing system for monitoring the availability of multiple redundant data sources within a high-availability data environment. The inaccessibility of at least one of the multiple redundant data sources is detected, thus defining at least one inaccessible data source. Which software applications are impacted by the at least one inaccessible data source is determined, thus defining at least one impacted software application. A notification is provided to one or more parties associated with the at least one impacted software application concerning the inaccessibility of the at least one inaccessible data source.

Message generation system and method

A native data collection component may be implemented as a tool, appliance, application and/or utility, and including physical and/or logical implementations thereof. The native data collection component may be responsible for data orchestration, data collection, and aggregation and distribution of collected data from among multiple sources. Accordingly, the native data collection component may be independent of a particular data source and act as an independent performance characteristic collection mechanism. In an embodiment, the native data collection component may include three devices/sub-components: a data orchestration device, a data collection interface and a data aggregation and distribution device. Each sub-component may be service based and communication with each service may be done using state-less protocols. The data collection interface enables a software structure that includes data collection plug-ins that are independent of data sources and are not deployed into the SAN as agents of any of the data sources.

Native storage data collection using plug-ins that are independent from data sources

A system provides for display of results from performance data analysis that presents mini-chart overlays on a topology map based on intelligent analytics for components in a I/O data path of a host or other object. The mini-charts may be advantageously used to show criticality of impact to assist a user with incident avoidance and/or to provide fast incident resolution. When launching into the topology map, the user may enable mini-charts and visually see from the charts where a possible performance bottleneck is detected by the analytics. In an embodiment, the mini-charts for the most relevant metrics may be displayed and identified for criticality, such as by color. The colors may be determined by thresholds, that may be set by a user and/or determined by the system, and may be calculated automatically based on learned base line, maximum line and minimum line operations over set times.

Path performance mini-charts

A native data collection component may be implemented as a tool, appliance, application and/or utility, and including physical and/or logical implementations thereof. The native data collection component may be responsible for data orchestration, data collection, and aggregation and distribution of collected data from among multiple sources of a storage area network (SAN). The native data collection component is not required to be installed as an agent on any data source of the SAN, and the native data collection component may be independent of a particular data source and act as an independent performance characteristic collection mechanism. In an embodiment, the native data collection component may include three devices/sub-components: a data orchestration device, a data collection interface and a data aggregation and distribution device. Each sub-component may be service based and communication with each service may be done using state-less protocols.

Native storage data collection using multiple data collection plug-ins installed in a component separate from data sources of one or more storage area networks

A system for controlled-tuning path performance data collection through a single application control. In an embodiment, performance data collection may be turned on or off from an application host running a path performance data application via a user interface. The tool may automatically update performance data collection characteristics as the application host I/O data path changes according to user controlled settings but without requiring further user intervention during the updating. In various embodiments, the tool may update continuously and/or at specified intervals. Turning on path performance data collection on the application host via the user interface may automatically set up synchronized performance data collection for all managed objects within I/O data path(s) of the managed objects.

Path performance data collection

Growing community of inventors

Shirley, MA, United States of America

Mark Adam Arakelian