Abstract: An apparatus comprises at least one processing device configured to register two or more source services, wherein registering a given source service comprises executing the given source service to identify inputs and outputs of the given source service, and to select a set of outputs from the registered source services for generating at least a portion of a user interface of an application in an application client, the selected set of outputs comprising at least first and second output from first and second ones of the registered source services. The processing device is also configured to determine an orchestration of the registered source services for obtaining the selected set of outputs, to generate a custom microservice configured to execute the registered source services in accordance with the determined orchestration, and to deploy the custom microservice in an auto-scalable computing framework accessible to the application client of the application.

Abstract: A decision management technique comprises obtaining, for a set of items, data indicative of a previous percentage division between a first item type and a second item type for each item in the set of items. The technique further comprises classifying each item in the set of items into one of a plurality of clusters, based on the obtained data, wherein each cluster represents a different percentage division range between the first item type and the second item type. The technique further comprises identifying any items in each cluster that deviate from the percentage division range for the cluster, and then applying weights to any identified items based on the deviation from the percentage division range. The technique further comprises re-classifying any identified items to another cluster in the plurality of clusters based on the applied weights.

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 are provided for managing an end-to-end software development life cycle. A software development lifecycle management system performs a plurality of stages of work for developing a software application, and records transactions which result from performing the plurality of stages of work, in an immutable digital ledger. The immutable digital ledger can be a blockchain ledger.

Abstract: An initial transaction is generated representing a forecasted demand for material needed to manufacture equipment via a supply chain. The initial transaction is added to a blockchain for access by entities in the supply chain comprising at least a subset of one or more supply entities, one or more material distribution entities, and one or more manufacturing entities. In one or more examples, the steps may be performed by an OEM blockchain node that accesses any transactions added by the various entities on the blockchain node and limits access to transactions on the blockchain by the various entities. Further, the initial transaction may be a main transaction and a transaction representing a commitment by one of the supply entities may be a sub-transaction of the main transaction, and the sub-transaction is closed in the blockchain upon the request for payment for the committed material or payment of the request.

Abstract: An example methodology includes receiving a forecast for a product and a forecast for a component item needed to make the product. The method also includes, responsive to a determination that the forecast for the component item is an outlier anomaly, computing an outlier corrected forecast quantity for the component item and correcting the forecast for the component item to be the computed outlier corrected forecast quantity for the component item. The method can further include computing a percentage deviation between a total corrected forecast quantity and a quantity forecasted for the component item and, responsive to a determination that the forecast for the component item is an inlier anomaly, computing an inlier corrected forecast quantity for the component item and correcting the forecast for the component item to be the computed inlier corrected forecast quantity for the component item.

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: Techniques for managing critical workloads in container-based computing environments are disclosed. In one example, a method determines a resource trigger threshold associated with executing at least one containerized workload associated with a first service having a first criticality level, the resource trigger threshold corresponding to a resource capacity allocated to execute the first service. The method determines when the resource capacity allocated to execute the first service reaches the resource trigger threshold, and then re-allocates resource capacity allocated to execute at least one containerized workload associated with a second service having a second criticality level to the first service when the resource trigger threshold is reached. For example, the first criticality level may be higher than the second criticality level.

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: Automated item management techniques are disclosed. For example, for a given item type obtainable from one or more sources and storable as inventory at one of a first site or a second site and based on a given demand forecast, a method classifies the item type based on historical data associated with obtaining the item type from the one or more sources. The method computes a risk factor value for the item type based on one or more risk factors. The method then computes, for the given demand forecast and based on the classifying and the risk factor value, a first amount of the item type to store as inventory at the first site and a second amount of the item type to store as inventory at the second site.

Abstract: An example methodology implementing the disclosed techniques includes, by a computing device, receiving data about a probable overstock product at a retail partner in a sales region from another computing device, the data including a finished goods assembly (FGA) stock keeping unit (SKU) that identifies the probable overstock product and a corresponding quantity of the probable overstock product. The method also includes, by the computing device, determining a total quantity of the probable overstock product in the sales region, wherein the total quantity includes the quantity of the probable overstock product at the retail partner, and computing a corrected FGA demand of the probable overstock product in the sales region based on the total quantity of the probable overstock product in the sales region. The method further includes, by the computing device, the corrected FGA demand of the probable overstock product in the sales region.

Abstract: An apparatus comprises at least one processing device configured to register two or more source services, wherein registering a given source service comprises executing the given source service to identify inputs and outputs of the given source service, and to select a set of outputs from the registered source services for generating at least a portion of a user interface of an application in an application client, the selected set of outputs comprising at least first and second output from first and second ones of the registered source services. The processing device is also configured to determine an orchestration of the registered source services for obtaining the selected set of outputs, to generate a custom microservice configured to execute the registered source services in accordance with the determined orchestration, and to deploy the custom microservice in an auto-scalable computing framework accessible to the application client of the application.

Abstract: Automated item management techniques are disclosed. For example, for a given item type obtainable from one or more sources and storable as inventory at one of a first site or a second site and based on a given demand forecast, a method classifies the item type based on historical data associated with obtaining the item type from the one or more sources. The method computes a risk factor value for the item type based on one or more risk factors. The method then computes, for the given demand forecast and based on the classifying and the risk factor value, a first amount of the item type to store as inventory at the first site and a second amount of the item type to store as inventory at the second site.

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.

Abstract: Techniques are disclosed for managing workloads in data processing systems. For example, a method determines a set of containers for processing a given workload of data records, wherein each container of the set of containers is configured to process a given subset of the data records. The method causes deployment of the set of containers in a ring configuration to process the given workload of data records such that at least one of the containers in the ring configuration automatically processes one or more data records of a subset of data records assigned to another container in the ring configuration that becomes inactive.

Abstract: A computer-implemented method is provided. Raw data records associated with one or more user interactions of a user with one or more entities, each respective raw data record comprising one or more of a textual interaction, an audio interaction, and a video interaction, are received. A first analysis is performed on the set of raw data records to analyze them for at least one of sentiments, emotions, and intent. A second analysis is performed on the set of raw data records to segment the set of raw user data. A third analysis of the raw set of data records performs at least one of interpreting, summarizing and classifying, of the information associated with the first and second analyses to determine, at least one recommended action to assist the user. An output signal, comprising the at least one recommended action is generated to the user based on the third analysis.

Abstract: A method comprises transmitting order data to at least one package configured for electronically receiving the order data and accommodating one or more items therein, wherein the at least one package is electronically locked. In the method, an access code for electronically unlocking the at least one package is generated and transmitted to a user device. The method also includes receiving a notification that the at least one package was unlocked, wherein the notification is received in response to electronically unlocking the at least one package with the access code.

Abstract: Automated item management techniques comprising balancing of items across a plurality of sites are disclosed. For example, for a given item type stored as inventory at a plurality of sites, a method predicts a stock factor for each of the plurality of sites based on historical stock factor data. The method also predicts an aging items count for each of the plurality of sites based on historical aging item data. The method computes a plan, based on the predicted stock factor and the predicted aging items count for each of the plurality of sites, to move an amount of the given item type between two or more of the plurality of sites to satisfy a demand forecast at each site.

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: 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.