Abstract: Discussed herein are techniques for migrating an application from a source cloud environment (SCE) to a target cloud environment (TCE). Responsive to a request received by an application migration service (AMS) to migrate an application executed in a first compute instance in the SCE to a second compute instance in the TCE, the AMS authenticates credentials of a user with respect to the SCE. Upon the credentials being successfully authenticated, the AMS generates a public key and a private key. The public key is transmitted to a service manager that injects the public key in the application executed in the first compute instance and the private key is assigned to a source agent. The source agent obtains one or more artifacts and configuration information that enable execution of the application based on the private key, which are installed by a target agent in the second compute instance in the TCE.

Abstract: Embodiments of the present invention provide a computer system, a computer program product, and a method that comprises identifying a plurality of data logs; generating a data model using analyzed time series data from the identified data logs; detecting anomalies within the generated data model; constructing a causal graph using the detected anomalies and retrieved domain knowledge; computing a severity value for the detected anomalies with the constructed causal graph; assigning the detected anomaly to a classification based on a function vector, wherein the computed severity value is a function vector; and automatically modifying a function of a computing device based on the function vector of the assigned, detected anomaly, wherein a modification addresses the detected anomaly located at a center of the constructed casual graph.

Abstract: A new and innovative high-pressure priming valve is provided for use in high-pressure fluid systems that require a high level of fluid purity. The priming valve includes at least three ports, some of which are angled. The priming valve also includes a needle that variably blocks and unblocks a pathway to one of the ports between normal operation and a priming operation, respectively. The priming valve includes a sealing insert positioned below a stack of washers that maintain the needle's alignment in response to high fluid pressures exerted on the needle. The sealing insert helps prevent fluid from contacting the stack of washers, which helps prevent biological growth within the valve. The angled ports help facilitate priming valve drainage to further help prevent biological growth. By helping prevent biological growth, the sealing insert helps prevent fluid contamination and enables the priming valve to be utilized for high-purity fluid applications.

Abstract: A system may monitor transaction data pertaining to a plurality of transaction types received by a network order fulfillment system. The system may classify the transaction data into a plurality of alarm types based on pre-defined impact of an alarm type to a given transaction type. The system may analyze a plurality of performance parameters influencing a performance of the network order fulfillment system, and identify a performance parameter exhibiting an anomaly based on historical data, a current status of the plurality of the performance parameters and a predefined prediction model. The system may ascertain whether the identified performance parameter negatively impacts the performance of the network order fulfillment system, based on evaluation rules. The system may proactively implement a remediation action to remediate a potential fault caused by the identified performance parameter when the identified performance parameter negatively impacts the performance of the network order fulfillment system.

Abstract: A computerized-method for calculating an After-Call-Work (ACW) factor of an interaction in a contact center, by which a related recording may be filtered for evaluation is provided herein. The method includes an After-Call-Work (ACW) factor calculation module. The operating of the ACW factor calculation module includes: (i) receiving agent recording of the interaction. (ii) aggregating data fields associated with: (a) the interaction; and (b) the customer; (iii) retrieving ACW time of the interaction; (iv) forwarding the aggregated data fields to a machine learning model; (v) operating the machine learning model to calculate a predicted ACW time, based on the aggregated data fields; (vi) calculating an ACW factor based on the received time of ACW and the calculated predicted ACW time; and (vii) sending the calculated ACW factor to a platform by which the platform is preconfigured to distribute the interaction for evaluation, based on the ACW factor.

Abstract: One embodiment provides a method, including: obtaining a plurality of previously submitted application documents, wherein each of the previously submitted application documents comprises information provided by a user who initiated a given previously submitted application document; clustering the plurality of previously submitted application documents into clusters of application documents based upon topics of the previously submitted application documents; selecting a representative application document; identifying entities contained within a given representative application document, wherein each of the entities corresponds to information to be entered into a new application document created from the given representative application document; and engaging in a dialogue with a user to create the new application document utilizing a similar representative application document to request information from the user, wherein the similar representative application document comprises a representative application d

Abstract: Methods, computer program products, and/or systems are provided that perform the following operations: in an information technology (IT) management system, grouping one or more ongoing service failure events into a service failure record; identifying a representative event for the service failure record; identifying one or more conversations that relate to the one or more ongoing service events; computing, using a similarity algorithm, feature similarity scores for respective conversations of the one or more conversations based, at least in part, on the features associated with the representative event and features associated with the respective conversations; linking a subset of the one or more conversations to the one or more ongoing service events in the service failure record based, at least in part, on the computed feature similarity scores; and providing the service failure record to a collaboration platform utilized in addressing the one or more ongoing service events.

Abstract: A method, system, and non-transitory processor-readable medium for optimizing lifecycle rule computer processing including: selecting a set of lifecycle rules to apply to interactions, finding a set of interactions satisfying criteria associated with the lifecycle rule; calculating an associated rule occupancy score based on the number of executed interactions associated with the rule, and executing the rule based on the rule occupancy score associated with the rule.

Abstract: A computerized-method for determining a storage class of a media file is provided herein. The computerized-method includes: (i) aggregating data from the plurality of data sources; (ii) operating a pre-built machine learning File Access Frequency Score (FAFS) model to calculate an accessibility score for a media file; (iii) sending the media file to archive storage when the accessibility score is below a preconfigured threshold; (iv) calculating Predicted Active Lifetime Span (PALS) score of the media file, when the accessibility score is above the preconfigured threshold; (v) repeating the calculating of the PALS score of the media file every preconfigured period of time, when the media file is in active storage, until the calculated PALS score of the media file is lower than or equals zero; and (vi) sending the media file to the archive storage.

Abstract: Systems, computer-implemented methods, and computer program products to facilitate proactive operational risk assessment of a proposed change in a computing environment are provided. According to an embodiment, a system can comprise a processor that executes computer executable components stored in memory. The computer executable components can comprise an extraction component that identifies change events in historic operational data that induced one or more incidents in a computing environment. The computer executable components further comprise an assessment component that employs a model to assign a change risk assessment score to a defined change in the computing environment based on the change events.

Abstract: A computerized-method for calculating an After-Call-Work (ACW) factor of an interaction in a contact center, by which a related recording may be filtered for evaluation is provided herein. The method includes an After-Call-Work (ACW) factor calculation module. The operating of the ACW factor calculation module includes: (i) receiving agent recording of the interaction; (ii) aggregating data fields associated with: (a) the interaction; and (b) the customer; (iii) retrieving ACW time of the interaction; (iv) forwarding the aggregated data fields to a machine learning model; (v) operating the machine learning model to calculate a predicted ACW time, based on the aggregated data fields; (vi) calculating an ACW factor based on the received time of ACW and the calculated predicted ACW time; and (vii) sending the calculated ACW factor to a platform by which the platform is preconfigured to distribute the interaction for evaluation, based on the ACW factor.

Abstract: A computerized-method for gauging agent's self-assessment effectiveness, is provided herein. The computerized-method includes for each interaction (i) operating a Self-assessment Consolidation module to calculate a confidence-interval for each data-point of one or more preconfigured data-points, and (ii) operating a Self-assessment Divergence Determinant (SDD) module. The operating of the SDD includes: retrieving one or more data-points of the interaction; for each data-point retrieving the confidence interval; setting a divergence-indicator as zero, when the data point is within the confidence-interval; setting the divergence-indicator as a subtraction of the data point from the calculated lower-bound, when the data-point is lower than the lower-bound of the confidence-interval; and setting the divergence-indicator as a subtraction of the calculated upper-bound from the data-point, when the data-point is greater than the upper-bound of the confidence-interval.

Abstract: A computerized-method for calculating an After-Call-Work (ACW) factor of an interaction in a contact center, by which a related recording may be filtered for evaluation is provided herein. The method includes an After-Call-Work (ACW) factor calculation module. The operating of the ACW factor calculation module includes: (i) receiving agent recording of the interaction; (ii) aggregating data fields associated with: (a) the interaction; and (b) the customer; (iii) retrieving ACW time of the interaction; (iv) forwarding the aggregated data fields to a machine learning model; (v) operating the machine learning model to calculate a predicted ACW time, based on the aggregated data fields; (vi) calculating an ACW factor based on the received time of ACW and the calculated predicted ACW time; and (vii) sending the calculated ACW factor to a platform by which the platform is preconfigured to distribute the interaction for evaluation, based on the ACW factor.

Abstract: A computer-implemented method gathers a set of previously filed applications, performs intent identification on the set, clusters applications in the set based on identified common intents, receives input from user and identifying intent of the input, matches the input to a cluster based on a common intent, and generates a new application based on the input using filed applications in a cluster having a common intent between the cluster and the input.

Abstract: A system may monitor transaction data pertaining to a plurality of transaction types received by a network order fulfillment system. The system may classify the transaction data into a plurality of alarm types based on pre-defined impact of an alarm type to a given transaction type. The system may analyze a plurality of performance parameters influencing a performance of the network order fulfillment system, and identify a performance parameter exhibiting an anomaly based on historical data, a current status of the plurality of the performance parameters and a predefined prediction model. The system may ascertain whether the identified performance parameter negatively impacts the performance of the network order fulfillment system, based on evaluation rules. The system may proactively implement a remediation action to remediate a potential fault caused by the identified performance parameter when the identified performance parameter negatively impacts the performance of the network order fulfillment system.

Abstract: A computerized-method for determining a storage class of a media file is provided herein. The computerized-method includes: (i) aggregating data from the plurality of data sources; (ii) operating a pre-built machine learning File Access Frequency Score (FAFS) model to calculate an accessibility score for a media file; (iii) sending the media file to archive storage when the accessibility score is below a preconfigured threshold; (iv) calculating Predicted Active Lifetime Span (PALS) score of the media file, when the accessibility score is above the preconfigured threshold; (v) repeating the calculating of the PALS score of the media file every preconfigured period of time, when the media file is in active storage, until the calculated PALS score of the media file is lower than or equals zero; and (vi) sending the media file to the archive storage.

Abstract: Methods, systems, and computer program products for mining multi-party collaboration platforms to create triaging trees and playbooks are provided herein. A computer-implemented method includes obtaining, from a multi-user platform, conversations related to at least one technical issue; generating a plurality of triaging trees by analyzing the conversations, wherein each of the triaging trees stores information corresponding to temporal sequences of steps related to diagnosing and resolving said at least one technical issue; and deriving a playbook for resolving said at least one technical issue at least in part by combining two or more of the plurality of triaging trees.

Abstract: Methods, systems, and computer program products for generating dialog system workspaces are provided herein. A computer-implemented method includes obtaining (i) a set of policy documents and (ii) a set of initial questions; identifying at least one of the policy documents in the set of policy documents that is relevant to answering a given one of the initial questions in the set of initial questions; generating, based at least in part on an analysis of said identified policy document, (i) at least one follow-up question to said given initial question and (ii) two or more candidate answers to said at least one follow-up question; generating a dialog tree comprising at least (i) a parent node corresponding to the at least one follow-up question and (ii) child nodes corresponding to the two or more candidate answers; translating the dialog tree into a dialog workspace; and deploying the dialog workspace in an intelligent dialog system.

Abstract: A computer server controls access to a hosted service using digital certificates that are requested from each client attempting to access the service. When a particular client accesses the hosted service, the host service requests a digital certificate from the particular client and issues a challenge message. The particular client signs the challenge message and provides a client digital certificate to the hosted service. The hosted service confirms that the signature on the challenge message matches the client digital certificate, and that the client digital certificate is signed by a trusted entity. Trusted entities are defined by an administrator by uploading, to the hosted service, one or more trusted digital certificates associated with a trusted entities. Using the trusted digital certificates, the hosted service confirms that the digital certificate provided by the particular client is signed by at least one of the trusted entities.

Abstract: A new and innovative high-pressure priming valve is provided for use in high-pressure fluid systems that require a high level of fluid purity. The priming valve includes at least three ports, some of which are angled. The priming valve also includes a needle that variably blocks and unblocks a pathway to one of the ports between normal operation and a priming operation, respectively. The priming valve includes a sealing insert positioned below a stack of washers that maintain the needle's alignment in response to high fluid pressures exerted on the needle. The sealing insert helps prevent fluid from contacting the stack of washers, which helps prevent biological growth within the valve. The angled ports help facilitate priming valve drainage to further help prevent biological growth. By helping prevent biological growth, the sealing insert helps prevent fluid contamination and enables the priming valve to be utilized for high-purity fluid applications.