Abstract: A method comprising: identifying an order for a product; dividing the order into order portions and assigning each of the order portions to a different respective supplier; adjusting each of the order portions based on a capacity of the respective supplier to which the order portion is assigned; and returning the order portions after the order portions have been adjusted, wherein adjusting any given one of the order portions includes identifying a term that is associated with the given order portion, dividing the given order portion into a plurality of daily quantities that correspond to different respective days in the term, and reducing any given one of the daily quantities that fails to meet a corresponding daily capacity of the respective supplier to which the given order portion is assigned.

Abstract: Intelligent prediction techniques for equipment manufacturing management are disclosed. For example, a method comprises obtaining: (i) a structured description of at least one of components and processes associated with manufacturing of equipment in accordance with a given design; (ii) first manufacturing-related data from one or more potential manufacturing entities for the equipment; and (iii) second manufacturing-related data representing at least one of current attributes and historical attributes associated with manufacturing equipment at least similar to the equipment of the given design. The method then applies one or more prediction models based on at least portions of the obtained structured description, the first manufacturing-related data, and the second manufacturing-related data to compute a predicted attribute associated with manufacturing the equipment.

Abstract: An apparatus comprises a processing device configured to generate and utilize an automated document parser for parsing documents exchanged as part of fulfillment of historical component orders by a given supplier in a supply chain for first and second organizations to identify first and second organization-specific component identifiers utilized by the first and second organizations and a given supplier-specific component identifier utilized by the given supplier for a given component.

Abstract: Techniques for managing activation of functionalities in an information processing system are provided. For example, a method generates, at a first node in a distributed ledger network, at least one data object comprising data associated with a system and one or more unactivated functionalities of the system, and the data object further comprises one or more parameter fields configured for one or more other nodes in the distributed ledger network to subsequently insert data therein. The method obtains the at least one data object after data is inserted in the one or more parameter fields by the one or more other nodes. The method sends the at least one object to an additional node in the distributed ledger network for use in activating the one or more unactivated functionalities of the system.

Abstract: An apparatus comprises a processing device configured to determine an asset identifier for an information technology asset, to encrypt the asset identifier utilizing a public key of a first homomorphic encryption key pair, and to evaluate a first homomorphic encryption function for a first homomorphically encrypted access authorization object that takes as input the encrypted asset identifier and provides as output an encrypted access authorization identifier. The processing device is also configured to decrypt the access authorization identifier utilizing a secret key of the first homomorphic encryption key pair and, responsive to validating the access authorization identifier, to evaluate additional homomorphic encryption functions for additional homomorphically encrypted access authorization objects that return encrypted access authorization information.

Abstract: Techniques for management of a multi-cloud computing environment are disclosed. For example, a method comprises the following steps. A node is configured to participate in a distributed ledger protocol with one or more other nodes. The node is further configured to maintain, in conjunction with the one or more other nodes, a data structure of blocks, wherein the blocks represent one or more of elements and operations associated with a multi-cloud computing environment and collectively function as a digital representation of the multi-cloud computing environment.

Abstract: Computing devices with dual computing architectures for use in a subscription model are disclosed. For example, a computing device comprises a first computing architecture comprising a first set of computing resources dedicated to executing one or more first computing tasks, wherein the one or more first computing tasks are associated with a subscription-based user of the computing device. The computing device further comprises a second computing architecture comprising a second set of computing resources dedicated to executing one or more second computing tasks, wherein the one or more second computing tasks are associated with a subscription-based provider of the computing device.

Abstract: An apparatus comprises at least one processing device configured to, in a monitoring system in which at any given time at least one monitoring node has a primary monitoring role responsible for monitoring operation of system nodes of a distributed system and other monitoring nodes have a secondary monitoring role responsible for monitoring operation of the at least one monitoring node having the primary monitoring role, identify a first monitoring node having the primary monitoring role at a current time. The processing device is also configured to determine, based at least in part on a time-based ranking of the monitoring nodes, a second monitoring node having the secondary monitoring role at the current time to transition to the primary monitoring role, and to transition the second monitoring node to the primary monitoring role at a subsequent time.

Abstract: Automated risk management techniques in an information processing system are disclosed. For example, for a given item type obtainable from two or more sources, wherein each of the two or more sources has an aging policy associated with the item type that is different with respect to one another, the method predicts a quantity of the item type obtainable from each of the two or more sources that is at risk during a given future time period based on the aging policy of each of the two or more sources. The method then determines one or more actions to be initiated to mitigate the quantity of the item type obtainable from each of the two or more sources that is at risk during the given future time period.

Abstract: Methods, apparatus, and processor-readable storage media for operating system for collecting and transferring usage data are provided herein. An example computer-implemented method includes: configuring two or more of a plurality of hardware components to perform a respective data collection process, wherein: the hardware components are associated with at least a first location, the configuring is performed by a system layer of an operating system installed on at least one of the plurality of hardware components, and a given one of the data collection processes collects usage data of the corresponding hardware component based on one or more characteristics of the corresponding hardware component; obtaining, by the operating system from the configured hardware components, the usage data collected by each of the data collection processes over a given time period; and uploading the obtained usage data to a datastore that is associated with at least a second location.

Abstract: Techniques for managing containerized workloads in a container computing environment are disclosed. For example, a method comprises the following steps. In a first mode, the method learns resources and execution times needed to process incoming workloads of a first workload type and a second workload type in a set of one or more clusters in a container-based computing environment. In a second mode, based on the learning of resources and execution times in the first mode, the method determines whether a subsequent incoming workload of the second workload type can be executed by one of the set of one or more clusters or whether an additional cluster should be created to process the subsequent incoming workload and then removed after processing the subsequent incoming workload is completed.

Abstract: Automated supply chain management techniques are disclosed. For example, a method comprises the following steps. The method obtains a demand for a given number of an item associated with a manufacturing order. The method obtains a set of classifications for a set of suppliers based on historical data corresponding to each of the suppliers, and obtains a criticality indicator for the demand. The method generates an allocation for the demand across at least a subset of the set of suppliers based on the set of classifications and the criticality indicator, wherein each of the suppliers in the subset is allocated a given proportion of the demand in accordance with the generated allocation.

Abstract: Techniques for managing containerized workloads in a container computing environment are disclosed. For example, a method comprises the following steps. The method predicts a composite time delay value for initializing an instance of a containerized workload for executing a microservice within a container computing environment. The method then computes at least one target resource utilization parameter, based on the predicted composite time delay value, for use by the container computing environment.

Abstract: Automated management of software code change and deployment in an information processing system is disclosed. In one example, a method comprises the following steps. The method obtains one or more parameters specifying a software deployment following at least one code change to a set of one or more software programs. The method distinguishes first portions of the set of one or more software programs that are affected by the at least one code change from second portions of the set of one or more software programs that are unaffected by the at least one code change. The method generates at least one deployment script for causing deployment of the first portions of the set of one or more software programs without causing deployment of the second portions of the set of one or more software programs.

Abstract: An apparatus comprises at least one processing device configured to, in a monitoring system in which at any given time at least one monitoring node has a primary monitoring role responsible for monitoring operation of system nodes of a distributed system and other monitoring nodes have a secondary monitoring role responsible for monitoring operation of the at least one monitoring node having the primary monitoring role, identify a first monitoring node having the primary monitoring role at a current time. The processing device is also configured to determine, based at least in part on a time-based ranking of the monitoring nodes, a second monitoring node having the secondary monitoring role at the current time to transition to the primary monitoring role, and to transition the second monitoring node to the primary monitoring role at a subsequent time.

Abstract: An apparatus in an illustrative embodiment comprises at least one processing device that includes a processor coupled to a memory, with the at least one processing device being configured to obtain at least a portion of a uniform resource locator (URL) presented in a browser, to determine at least one of a domain and one or more cookies associated with the URL, to generate a file comprising information characterizing the at least one of the domain and the one or more cookies associated with the URL, to generate a multi-dimensional code based at least in part on the generated file, and to present the multi-dimensional code via the browser for scanning. The multi-dimensional code in some embodiments is presented for scanning by a mobile application of a mobile device of a user.

Abstract: Conversational artificial intelligence techniques with live agent engagement based on automated frustration level monitoring are disclosed. For example, a method comprises obtaining, via a conversational artificial intelligence system, a frustration level metric associated with a user participating in a conversation with the conversational artificial intelligence system, The method further comprises managing, via the conversational artificial intelligence system, human agent engagement in the conversation based on the frustration level metric.

Abstract: Techniques for managing activation of software, e.g., an operating system, in an information processing system are provided. For example, a method comprises the following steps. A data object is obtained for a system having an un-activated computer program stored thereon. The data object comprises information about the system encrypted by a private value. The method then causes the data object to be securely stored on a distributed ledger for subsequent access during a process to activate the computer program.

Abstract: An apparatus comprises at least one processing device configured to detect one or more issues associated with execution of a first version of a microservice in one or more computing environments, to determine whether any of the detected issues correspond to one or more triggers of one or more predefined patterns in a knowledge base, and, responsive to determining that at least one of the detected issues corresponds to at least one of the triggers of at least one of the predefined patterns in the knowledge base, to utilize code modification data structures specified in the at least one predefined pattern to modify source code of the microservice. The processing device is further configured to generate at least one additional version of the microservice utilizing the modified source code, and to deploy the at least one additional version of the microservice in at least one of the computing environments.

Abstract: An example methodology implementing the disclosed techniques includes receiving an online meeting Uniform Resource Locator (URL) for an online meeting that is being scheduled. The method also includes determining whether the online meeting is a secure online meeting. The method also includes, responsive to a determination that the online meeting is a secure online meeting, generating a personalized online meeting URL for each meeting participant that is invited to the secure online meeting, the personalized online meeting URL being based on the online meeting URL. The method further includes encrypting the generated personalized online meeting URLs and sending to each meeting participant that is invited an invitation to the secure online meeting. The invitation sent to each invited meeting participant includes an encrypted personalized online meeting URL that is generated for that invited meeting participant.