Abstract: Systems and methods for backing up and restoring serverless applications are provided. A serverless application is queried to identify the functions and services used. These functions and services are transformed into a manifest or graph that allows the relationships of the serverless application to be identified in an automated manner. The serverless application can be backed up and/or restored using the manifest.

Abstract: Systems and methods for performing data protection operations in a containerized application. A sidecar application is associated with or attached to a main application. The sidecar application has access to the resources of the main application. Backup requests are handled by the sidecar so that the application, which may be stateful, can be placed in a consistent state prior to performing the backup operation. The backup operation is then performed on the consistent application or on the data that is quiesced.

Abstract: Dynamic honeypots for computer program execution environments are described. A determination is made whether a time period has expired since a computer program execution environment, of multiple computer program execution environments, began executing a computer program that provides a user service. The computer program execution environment is changed into a computer security mechanism that counteracts an attempt of unauthorized use of a system that comprises the computer program execution environment, in response to a determination that the time period has expired since the computer program execution environment began executing the computer program that provides the user service.

Abstract: Systems and methods are provided for dynamically reallocating resources during run-time execution of workloads in a distributed accelerator-as-a-service computing system to increase workload execution performance and resource utilization. A workload is executed in the distributed accelerator-as-a-service computing system using an initial set of resources allocated to the executing workload, wherein the allocated resources include accelerator resources (e.g., physical and/or virtual accelerator resources). The performance of the executing workload is monitored to detect a bottleneck condition which causes a decrease in the performance of the executing workload. In response to detecting the bottleneck condition, another set of resources is reallocated to the executing workload, which is determined to reduce or eliminate the bottleneck condition.

Abstract: Disclosed is a method, apparatus, and system for collecting video data relating to a security event at a security operations center (SOC), the operations comprising: receiving video data captured through one or more cameras installed at one or more vehicles within a predetermined range of the security event at the SOC from the one or more vehicles; and compiling the video data into viewable format usable in an investigation of the security event.

Abstract: Virtual machines can be discretely tested for disaster recovery or other data protection operations. To perform these types of data protection operations, a single virtual machine or a set of virtual machines is migrated to a target site and the migrated virtual machines are replaced with dummy virtual machines at the source site. The dummy virtual machines replicate communications. This allows the migrated virtual machines to be tested in the context of disaster recovery to a target site such as the cloud.

Abstract: A node for use in a data archive includes a persistent storage and a data protection agent. The persistent storage stores a copy of data. The data protection agent obtains a request to archive the copy of the data; in response to the request: generates an archive of the copy of the data; stores the archive in an archive node; generates metadata based on the archive; deletes the copy of the data from the persistent storage; and, after deleting the copy of the data, advertises, to a second node, that the copy of the data is stored in the node.

Abstract: A containerized environment and application that are configured for component specific continuous replication and granular application level application. A key value store, which stores key values related to configuration data of the containerized application, is replicated continuously to a replicated key value store at a replica site. Persistent volumes may also be replicated to a replica site. The replication can be performed to multiple replica sites in an application specific manner.

Abstract: One example method includes receiving an IO request that specifies an operation to be performed concerning a data block, determining if a policy exists for a device that made the IO request, when a policy is determined to exist for the device, comparing the IO request to the policy, recording the IO request, and passing the IO request to a disk driver regardless of whether the IO request is determined to violate the policy or not.

Abstract: Example embodiments of the present invention relate to methods, systems, and a computer program product for managing a virtual datacenter. The method includes tracking configuration metadata for a virtual datacenter operating at a first site and simulating the virtual datacenter at a second site according to the tracked virtual datacenter configuration metadata. An analysis then may be performed on operation of the simulated virtual datacenter at the second site.

Abstract: Systems and methods for discovering applications. An application may be discovered by determining a topology of the application in a containerized platform. Discovering the topology may include determining the components of the application and then determining relationships between the components. The relationships may include whether a component (e.g., a microservice) is user facing and may be based on traffic patterns between the components. The components or microservices may be prioritized or ranked based on the topology. The topology can be used when performing a data protection operation such as a restore operation.

Abstract: One example method includes receiving input concerning a boot order sequence, where the input includes VM metadata, entering a training phase which includes generating a boot sequence rule based on the input, using the boot sequence rule to generate a proposed boot sequence, performing the proposed boot sequence, and gathering information concerning performance of the proposed boot sequence. The gathered information can be used as a basis to generate a modified boot sequence.

Abstract: One example method includes performing a machine learning process that involves performing an assessment of a state of a computing system, and the assessment includes analyzing information generated by an IoT edge sensor in response to a sensed physical condition in the computing system, and identifying an entity in the computing system potentially impacted by an event associated with the physical condition.

Abstract: One example method includes receiving input concerning a boot order sequence, where the input includes VM metadata, entering a training phase which includes generating a boot sequence rule based on the input, using the boot sequence rule to generate a proposed boot sequence, performing the proposed boot sequence, and gathering information concerning performance of the proposed boot sequence. The gathered information can be used as a basis to generate a modified boot sequence.

Abstract: In a multi-cloud computing environment comprising a plurality of cloud platforms across which an enterprise stores primary data and copies of the primary data, a method maintains a distributed ledger system with a plurality of nodes, wherein a given one of the plurality of cloud platforms is operatively coupled to a given one of the plurality of nodes of the distributed ledger system. Further, the method manages capacity planning and data placement for the primary data and the copies of the primary data in association with the distributed ledger system by storing transaction data in the distributed ledger system that represents at least one of one or more pricing models associated with each cloud platform and one or more regulatory policies associated with each cloud platform to enable an environment-wide view of at least one of the pricing models and the regulatory policies of the plurality of cloud platforms.

Abstract: A method for use in a computing system, the method comprising: identifying plurality of storage devices; generating a plurality of virtual drive sets, each virtual drive set corresponding to a different one of the plurality of storage devices, each virtual drive set including a plurality of virtual drives, such that each of the virtual drives in the virtual drive set is mapped to a different portion of the virtual drive set's corresponding storage device; instantiating a plurality of storage drive arrays, each of the storage drive arrays being formed of virtual drives from different virtual drive sets; instantiating a plurality of logical units, each of the logical units being instantiated on a different one of the plurality of storage drive arrays; and assigning at least some of the logical units to different software components that are executed on the computing system.

Abstract: A method and system for performance-driven load shifting. Specifically, the method and system disclosed herein entail transferring user program workloads, for processing, between local computing resources available on a client device and cloud computing resources available on an offload domain based on the assessed performance score of the client device at any given point in time. Seamless load shifting is further guaranteed due substantively to the employment of a mobile network facilitating communications between the client device and the offload domain.

Abstract: Techniques are provided for compression and decompression of log data using pattern recognition. An exemplary method comprises: obtaining at least one log message, wherein the at least one log message comprises a pattern-based message template and one or more message variables, wherein the pattern-based message template was learned from historical log data using a log pattern mining technique; obtaining a compression index that maps a plurality of pattern-based message templates to a corresponding message signature; and writing the one or more message variables and a message signature corresponding to the pattern-based message template of the at least one log message to a log file. The log pattern mining technique learns a given pattern-based message template from the historical log data to represent a plurality of historical log messages. The at least one log message may comprise a historical log message or may be from a real-time stream of log messages.

Abstract: Techniques are provided for compression of log data using field types. An exemplary method comprises: obtaining at least one log message, wherein the at least one log message comprises a message template and at least one message variable, wherein the message template comprises at least one field corresponding to the at least one message variable; obtaining a compression index that maps a plurality of message templates to a corresponding message signature; identifying a predefined field type of the at least one field; selecting a compression technique to apply to the at least one message variable based on the predefined field type to obtain a compressed message variable; and writing the compressed message variable and a message signature corresponding to the message template of the at least one log message to a log file. The at least one log message can be a historical log message or part of a real-time stream of log messages.

Abstract: An aspect includes reading a first page and a corresponding second page from a storage device. The first page specifies a metadata page stored in persistent storage and having logical addresses of metadata, and the second page associates logical block addresses (LBAs) with corresponding physical locations for the metadata. An aspect also includes reading data for a RAID stripe according to an associated physical offset in the second page, accessing a stripe counter from the second page, and comparing the stripe counter from the second page to a stripe counter held in memory. Upon determining the stripe counter from the second page is not the same, a third page is loaded, and a physical location of the data is read from the third page that provides a hash value of the data and corresponding physical location. The physical location of the data is accessed, and the second page is updated.