Abstract: An aspect includes storage stack analysis. A processor determines a client configuration of a client storage stack that includes a plurality of layers with configurable parameters to control storage and retrieval of data between an uppermost layer and a lowest layer. The processor initiates creation of a replica of the client storage stack based on the client configuration. Input/output characteristics are collected of a workload executed on the client storage stack using the client configuration. A synthesized workload is applied to the replica of the client storage stack, where the synthesized workload is based on the input/output characteristics of the workload. The processor analyzes input/output performance through the layers of the replica of the client storage stack in response to applying the synthesized workload. One or more configuration issues are identified with the client configuration of the client storage stack based on a result of the analysis.

Abstract: Embodiments of the invention relate to recovering from a disaster associated with an information technology environment. An information technology environment is replicated to a service provider. A recovery plan is generated for the environment. The recovery plan includes two processes. In response to the service provider receiving a disaster recovery request associated with the environment, the service provider executes a disaster recovery protocol. The protocol includes simultaneously executes the first and second processes. The first process operates a workload in the form of one or more containers, and the second process is a background process that creates a replica of the environment. After completion of the replica creation, the workload is migrated to the replica.

Abstract: An approach for managing replicated data is presented. A current usage of resources in a system and a threshold usage of the resources are determined. Based on inter-replica correlation(s) and inter-data correlation(s) specified by a unified replication metadata model, a proper subset of replicas included in a plurality of replicas is indexed by (i) if the current usage is less than the threshold usage, determining an expected additional resource usage due to performing an indexing task online and based on the expected additional resource usage, determining a resource affinity score for performing the indexing task online, or (ii) if the current usage is greater than or equal to the threshold usage, determining an expected resource usage due to performing the indexing task offline and based on the expected resource usage, determining a resource affinity score for performing the indexing task offline.

Abstract: Software that performs the following steps is provided: (i) running an application on a first virtual machine on a first physical server, with the application including a first plurality of independently migratable elements, including a first independently migratable element that utilizes a first resource on the first virtual machine and a second independently migratable element that utilizes a second resource on the first virtual machine; and (ii) on condition that a first migration condition exists, migrating the first independently migratable element to a second virtual machine on a second physical server, such that the first independently migratable element is able to utilize a resource that is similar to the first resource on the second virtual machine on the second physical server while the second independently migratable element remains able to utilize the second resource on the first virtual machine on the first physical server.

Abstract: One embodiment provides a quality of service (QoS) monitoring framework for dynamically binding one or more customer applications to one or more microservices in a dynamic service environment, collecting compliance data and contextual data from the dynamic service environment and one or more hosting environments, and modifying a monitoring infrastructure for the one or more customer applications based on the compliance data and the contextual data.

Abstract: A blockchain of transactions may be referenced for various purposes and may be later accessed by interested parties for ledger verification and information retrieval. One example method of operation may include one or more of monitoring a computing service via various nodes operating on a blockchain, identifying a proposed change to the computing service, storing details of the proposed change in a smart contract, storing the smart contract as a transaction in the blockchain, and validating the proposed change of the smart contract.

Abstract: A blockchain of transactions may be referenced for various purposes and may be later accessed by interested parties for ledger verification and information retrieval. One example method of operation may include one or more of storing original data in a blockchain, storing transformed data based on the original data in the blockchain, storing chaincode on the blockchain used to transform the original data to the transformed data, and retrieving a transaction from the blockchain with the transformed data and the chaincode.

Abstract: Systems and methods for resource provisioning are disclosed. A method includes: generating, by a computer device, a resource provisioning policy for a resource; receiving, by the computer device, a request for an allocation of the resource from an account; applying, by the computer device, the resource provisioning policy to the request based on receiving the request; automatically approving or denying, by the computer device, the request based on the applying the resource provisioning policy to the request; updating, by the computer device, the resource provisioning policy for the account based on the automatic approving or denying the request.

Abstract: An autonomous system for x-by-wire control includes processing nodes distributed and connected to one another. Sensors are connected to the processing nodes. Actuators are configured to directly control the autonomous system driven by and connected to the processing nodes for x-by-wire control. The processing nodes are configured to: partition and map processing tasks between the processing nodes, and merge and reduce results of individual processing tasks into an actionable table that specifies objectives for the autonomous system.

Abstract: A method for distributing data among storage devices. The method comprising one or more processors receiving a first graph workload that executes within a networked computing environment. The method further includes identifying data from the first graph workload that is utilized during the execution of the first graph workload that includes a plurality of data packets. The method further includes creating a first graph workload model representative of the graph structure of the first graph workload and determining two or more partitions that are representative of a distribution of the identified data utilized by the first graph workload based, at least in part, on the first graph workload model. The method further includes allocating a plurality of network accessible storage devices among the two or more partitions and copying a first set of data packets of the plurality of data packets to a network accessible storage device.

Abstract: A method and associated systems for identifying and correcting suboptimal storage-reclamation processes. A storage-management system uses information received in system-generated storage-reclamation reports to assign each user a set of reclamation scores. Each score identifies how effectively the user has been able to reclaim lost storage at particular times. These scores are organized into user-specific profiles that each consists of a chronological sequence of one user's scores. If a user's profile is “good” (that is, if the user's scores are consistently high) or “improving” (if scores are increasing over time), the system then determines whether that user's reclamation efforts have successfully reduced the amount of reclaimable storage controlled by the user. If not, the system infers that a suboptimal storage-reclamation process interfered with the user's reclamation efforts. The system then undertakes corrective action to identify and resolve the cause of the suboptimal process.

Abstract: In one embodiment, a method includes determining a first set of similarity metrics for a first storage environment, the first set of similarity metrics being based on predetermined parameters related to the first storage environment, at least one of the predetermined parameters being relating to a redundancy of connections and devices in the first storage environment. In addition, the method includes obtaining a second set of similarity metrics for a second storage environment. Also, the method includes determining that the second storage environment is similar to the first storage environment by calculating a similarity measurement score between the sets of similarity metrics for the first and second storage environments. Moreover, the method includes re-aligning the first storage environment according to one or more identified aspects of the second storage environment that improve performance of the first storage environment.

Abstract: A computer-implemented method according to one embodiment includes identifying a storage volume comprising a plurality of files, calculating a file level input/output operations per second (IOPS) value for each of a subset of the plurality of files within the storage volume, creating a predictive model for the storage volume, using metadata determined for the subset of the plurality of files and the IOPS values calculated for each of the subset of the plurality of files within the storage volume, estimating file level IOPS values for each of the plurality of files in the storage volume, utilizing the predictive model, combining the estimated and calculated file level IOPS values and comparing the combined values to a calculated volume level IOPS value for the storage volume, conditionally adjusting one or more of the estimated file level IOPS values, based on the comparing, and returning the estimated file level IOPS values.

Abstract: One embodiment provides a method comprising receiving metadata comprising univariate time series data for each variable of a multivariate time series. The method comprises, for each variable of the multivariate time series, applying a hybrid and hierarchical model selection process to select an anomaly detection model suitable for the variable based on corresponding univariate time series data for the variable and covariations and interactions between the variable and at least one other variable of the multivariate time series, and detecting an anomaly on the variable utilizing the anomaly detection model selected for the variable. Based on each anomaly detection model selected for each variable of the multivariate time series, the method further comprises performing ensemble learning to determine whether the multivariate time series is anomalous at a particular time point.

Abstract: A method for distributing data among storage devices. The method comprising one or more processors receiving a first graph workload that executes within a networked computing environment. The method further includes identifying data from the first graph workload that is utilized during the execution of the first graph workload that includes a plurality of data packets. The method further includes creating a first graph workload model representative of the graph structure of the first graph workload and determining two or more partitions that are representative of a distribution of the identified data utilized by the first graph workload based, at least in part, on the first graph workload model. The method further includes allocating a plurality of network accessible storage devices among the two or more partitions and copying a first set of data packets of the plurality of data packets to a network accessible storage device.

Abstract: In one embodiment, a method includes determining a first set of similarity metrics for a first storage environment, obtaining one or more second sets of similarity metrics from second storage environments that correspond with the first storage environment, calculating a similarity measurement score between the first storage environment and each of the second storage environments, and determining a set of similar storage environments from amongst the second storage environments based on the similarity measurement scores. Other methods, systems, and computer program products are presented according to more embodiments.

Abstract: A blockchain of transactions may be referenced for various purposes and may be later accessed by interested parties for ledger verification. One example operation may comprise one or more of identifying an updated software build, creating a hash based on the updated software build, storing the hash of the updated software build in a blockchain, and storing a binary representation of the updated software build in a distributed hash table (DHT).

Abstract: A method for inferring an application type, based on an operational characteristic I/O pattern of a storage volume. One or more processors determine at least one operational characteristic of each storage volume of a storage volume group associated with an application. One or more labels are assigned for each storage volume, based on the operational characteristics of each storage volume. At least one template is received that includes labels of storage volume characteristics of known application types. One or more processors infer a type of application associated with the storage volume group, based on a best-fit match of the aggregate labels of the storage volumes of the storage volume group to the labels included in the templates of storage volume characteristics of known application types.

Abstract: Embodiments relate to container migration and provisioning. An aspect includes receiving a request to migrate a composite application to a container-based environment. Another aspect includes determining a plurality of software components that make up the composite application. Another aspect includes determining communications patterns between the plurality of software components. Another aspect includes determining a containerization plan for the composite application based on the determined communications patterns. Another aspect includes creating a plurality of containers, and communications channels between the plurality of containers, for the software components of the composite application based on the containerization plan.

Abstract: A virtual blockchain configuration may provide a distributed structure that uses a distributed hash configuration to reduce the complexity of blockchain transactions. One example method of operation may comprise one or more of storing a subset of blockchain data in a network device, accessing via the network device a virtual copy of a blockchain, accessing a blockchain block via the virtual copy of the blockchain, and writing blockchain transactions to the blockchain block via the network device.