Emc IP Holding Company LLC

Dell Products Inc.

Erez Sharvit

Valerie Lotosh

Jehuda Shemer

Saar Cohen

Adam E Brenner

Steven Sadhwani

Assaf Natanzon

Lev Ayzenberg

Leehod Baruch

Alex Solan

Slavik Neymer

Yoval Nir

Tomer Twig

Providing content-based sensitivity classification to content data in a data processing system, by defining sensitivity designations for data objects stored in the system, and creating datasets by grouping metadata for data objects that are intended to classified with a same sensitivity designation, wherein each dataset spans multiple storage devices of different storage types, and wherein each dataset defines a single data sensitivity unit for the data objects referenced by a respective dataset. A sensitivity classifier component tags each dataset with a sensitivity tag to specify a protection or control operation on the data objects referenced by the respective dataset, and a processing component then processes data objects for each tagged dataset in accordance with the specified protection or control operation.

Data sensitivity classification using content-based datasets

Providing content-based encryption to content data in a data processing system by creating datasets by grouping metadata for data objects that are intended to be encrypted with a common encryption key, where each dataset spans multiple storage devices of different storage types, and defines a single data encryption unit for the data objects referenced by a respective dataset. Each dataset is tagged with an encryption tag to enable or disable use of a self-selected encryption key. Encryption keys stored in or made available to the system are accessed for encrypting the data objects using an encryption process. A key management component maps each dataset to a corresponding encryption key of the encryption keys, and an encryption component encrypts, for each dataset, referenced data objects using a corresponding mapped encryption key.

Encryption key management using content-based datasets

A system can maintain a first data center that comprises a virtualized overlay network and virtualized volume identifiers, and store data comprising virtualized workloads. The system can determine a service level agreement associated with providing a second data center as a backup to the first data center. The system can, based on the service level agreement, divide, into a first portion of tasks and a second portion of tasks deploying the data to a secondary storage of the second data center, deploying the data to a primary storage of the second data center, and configuring the second data center with the virtualized overlay network and the virtualized volume identifiers. The system can perform the first portion of tasks before determining to restore the first data center to the second data center. The system can perform the second portion of tasks in response to determining to restore the first data center.

Standby data center as a service

Managing a lifecycle of data by identifying data objects that are subject to same control rules in each stage of the lifecycle as grouped data, where the control rules allow only authorized access to or authorized operations on the grouped data based on a current stage of the lifecycle. A dataset is generated for the grouped data by identifying metadata of the grouped data to be processed similarly within the lifecycle, and storing the metadata in the dataset. The control rules associated with the grouped data as stage tags for the dataset. Actions performed on the data referenced by the dataset are monitored to ensure that the monitored actions comply with control rules using the stage tags of the dataset.

Dataset lifecycle management using monitoring and ACL control for content-based datasets

Embodiments of monitoring data assets in a system to apply rules to optimize storage and access of the data assets based on data content rather than data location, by defining rules based on the monitoring attributes, wherein a rule dictates a storage location of selected data or access permissions to the data by one or more persons or groups in the system. The selected data is tagged with a defined metadata tag, and a dataset is created by running a query against a data catalog to derive the dataset. A component monitors data usage and access of data elements referenced by the dataset to detect any violations of the defined rules, and provides a notification of any violation to facilitate remedial action by a user or process. The dataset can span multiple storage devices of different types to define a single processing unit for the monitoring attributes.

Monitoring data usage to optimize storage placement and access using content-based datasets

A system can determine timeseries telemetry data of a first resource utilization of a data center maintained by the system. The system can predict, from the timeseries telemetry data, a second resource utilization of the data center will occur at a future time, the second resource utilization exceeding a threshold amount of resource utilization of the data center. The system can determine, based on an amount of time available until the future time, a selected location indicative of whether to install additional hardware at a first physical location of the data center, or a second physical location of the data center, wherein an amount of time associated with installing the additional hardware at the first physical location is less than an amount of time associated with installing the additional hardware at the second physical location. The system can install the additional hardware at the selected location.

Automated data center expansion

A system can determine to restore a datacenter that comprises a group of virtualized workloads. The system can determine respective associations between respective virtualized workloads and respective datastores. The system can determine to restore a first virtualized workload of the group of virtualized workloads first. The system can restore a first portion of infrastructure that corresponds to the first virtualized workload first among a group of infrastructure. The system can, after restoring the first portion of infrastructure, restore a first portion of data that corresponds to the first virtualized workload first among a group of data. The system can, after restoring the first portion of data, restore a first portion of a virtualization layer that corresponds to the first virtualized workload first among a group of virtualization layers. The system can, after restoring the first portion of the virtualization layer, restore the first virtualized workload.

Data center restoration

Optimizing data movement from a source data center to a target data center by grouping metadata of data objects into a dataset that encompasses data processed identically by a data processing operation, where the dataset defines a single data access unit for these data objects, and the data processing operation processes them as a single unit based on data content rather than physical or logical data location of the data objects. A mobility process correlates an increase in a number of metadata elements in the dataset with a growth rate of the dataset, and compares the dataset growth rate with historical or similar dataset growth rate data. The comparison is used to determine when and where to move data from the source to the target data center based on a forecast of accelerated growth indicated by the comparing step, and a consideration of target data center resources, data move costs, and streaming data effects.

Optimizing cross-data center mobility using content-based datasets

A system can determine timeseries telemetry data of resource utilization of respective data centers of a group of data centers maintained by the system. The system can predict respective hardware requests based on future resource utilization based on the timeseries telemetry data, the hardware requests comprising respective hardware requests at respective data centers of the group of data centers. The system can predict respective future times at which the respective hardware requests will occur. The system can determine respective physical location sources of hardware, respective physical location destinations of hardware, and respective amounts of hardware based on the respective hardware requests and the respective future times. The system can store an indication of the respective physical location sources of hardware, respective physical location destinations of hardware, and respective amounts of hardware.

Global automated data center expansion

One example method includes measuring a journal distribution lag of a journal, evaluating a first operational measure at a production site, and evaluating a second operational measure at a replication site operable to communicate with a production site, based on the journal distribution lag, and the evaluation of the first operational measure and the second operational measure, determining a scale out for a consistency group of the replication site, and implementing the scale out of the consistency group.

Automatic consistency group scale-out for any point in time replication systems

A system can maintain a first data center that comprises a virtualized overlay network and virtualized volume identifiers. The system can determine to perform a restore of data of the first data center to a second data center, the data comprising first instances of virtualized workloads. The system can transfer the data to the second data center. The system can configure the second data center with the virtualized overlay network and the virtualized volume identifiers. The system can operate the virtualized workloads on the second data center, the second instances of the virtualized workloads invoking the second instance of the virtualized overlay network and the second instance of the virtualized volume identifiers.

Data center restoration and migration

A system can receive an order to install a first data center on customer premises, wherein the first data center comprises a first instance of a virtualized overlay network and a first instance of virtualized volume identifiers. The system can, in response to determining that installing the first data center is threshold likely to take at least a defined amount of time to install, instantiate a second data center for the customer account at a colocation site, wherein the second data center comprises a second instance of the virtualized overlay network a second instance of the virtualized volume identifiers. The system can operate customer workloads using the second data center. The system can, after instantiating the second data center, and in response to determining that the first data center is operational, switch the operating of the customer workloads from the second data center to the first data center.

Data center time to value

Any point in time backups for distributed consistency is disclosed. IOs from a consistency group are received by multiple aggregators and stored in corresponding journals. In response to a bookmark, the multiple journals are synthesized to create a do stream or to add the multiple journals to the do stream. A full synchronization operation can be performed simultaneously with replication operations.

Any point in time backup on secondary storage for distributed consistency groups

A system is provided that includes one or more hardware processors, and a non-transitory storage medium having stored therein instructions that are executable by one or more hardware processors to perform operations including: gathering information concerning thin journal space usage, in a thin journal, by each of a plurality of consistency groups, and the thin journal space comprises a plurality of journal blocks; computing an ideal journal block state for each consistency group; computing an achievable journal block state for each consistency group; and computing a transition step from the achievable journal block state to the ideal journal block state.

Dynamic shared journal

Generating any point in time backups without native snapshot generation. Production data is split such that a journal stream is sent to a data protection system, which may be local or remote. The journal stream includes a data stream and a metadata stream. Backups are synthesized at the data protection system by rolling at least a portion of the journal. A backup for any point in time represented in the journal can be synthesized.

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Ramat Gan, Israel

Erez Sharvit