Abstract: A system including one or more memory devices having instructions thereon, that, when executed by one or more processors, cause the one or more processors to receive a request from a service provider to be added to a trusted network of service providers, receive health safety data of a health data stream associated with the service provider and risk data of a risk data stream indicating risk levels associated with the service provider, determine that the service provider meets a level of heath safety by correlating the health safety data of the health data stream with the risk data of the risk data stream, receive a request from a device for a service provider recommendation of the trusted network of service providers, and provide an indication of the service provider to the device in response to a reception of the request for the service provider recommendation.

Abstract: In some examples, a plurality of alerts relating to issues in a computing arrangement are received, where the plurality of alerts generated based on events in the computing arrangement. A subset of the plurality of alerts is grouped into a bundle of alerts, the grouping being based on a criterion. The bundle of alerts is communicated to cause processing of the alerts in the bundle of alerts together.

Abstract: Gaps in proficiencies may be identified within an enterprise. Understanding gaps in the existing workforce may help inform training, hiring, and firing decisions to ensure successful completion of the upcoming projects and deadlines. Using a multi-level model for each proficiency that accounts for enterprise needs as well as hiring, retraining, and the like, a relationship between proficiencies, projects, and employees over time may be generated as a multi-dimensional temporal model. The temporal model may be simulated to forecast gaps in proficiencies of the employed workforce. Recommendations regarding retraining, hiring, and termination can be made to help users remedy the deficiencies. Additionally, the proficiencies most valuable to the enterprise may be determined using a catalog of proficiencies to cluster the proficiencies into proficiency clusters for each job or job category and the proficiencies scored.

Abstract: Systems and techniques for semantic graph database capture of industrial organization and market structure are described herein. Electronic market data may be obtained from an electronic data source. A set of entities and corresponding relationships may be extracted from the electronic market data. A property may be determined for each of the relationships. A market graph data structure may be generated using the set of entities. A search query may be received including an identifier of a member of the set of entities. A market graphic may be generated based on a node corresponding to the identifier and a set of edges corresponding to the node. The market graphic may be output in a computer-readable format.

Abstract: Illustrative embodiments provide automated methods and systems for generating customer communications through analysis of known data of the customer, and data derived from third-party systems such as social media platforms and government data sources. Some embodiments provide automated methods and systems that produce, based on past interactions with a customer, a set of future interactions for execution by a sender. The set of future interactions is preferably configured, relative to a previous set of interactions, to increase the likelihood of a favorable response from the customer.

Abstract: The subject matter of this specification generally relates to measuring the performance of facilities and generating user interfaces that present the performance. In one aspect, a method includes detecting, at a user interface of an application and based on data received from a device on which the application is executing, a first selection of a particular facility. In response to detecting the first selection, data that causes presentation of a dashboard user interface that includes a summary of information for the particular facility is provided. The summary includes a composite score for the particular facility that is computed based on multiple metrics for the particular facility and a value for each metric. In response to detecting a second selection of one or the metrics at the dashboard user interface, data that causes presentation of a second user interface that includes a detailed view of the one metric is provided.

Abstract: A valid combination of products is constructed from a set of products identified by a retailing backend system. The valid combination satisfies a condition of an offer. A product in the combination of product is a physical product located in a physical store. A social sentiment towards the product in social media data of a shopper is evaluated, and a rating of the product is computed using the evaluation. A location of the product in the store is obtained from the retailing backend system. The location of the product is overlaid on a view of the store, where the view is from a perspective of a location of the shopper, the shopper being physically situated in the store.

Abstract: Techniques for an optimization service of a service provider network to help optimize the selection, configuration, and utilization, of virtual machine (VM) instance types to support workloads on behalf of users. The optimization service may implement the techniques described herein at various stages in a life cycle of a workload to help optimize the performance of the workload, and reduce underutilization of computing resources. For example, the optimization service may perform techniques to help new users select an optimized VM instance type on which to initially launch their workload. Further, the optimization service may monitor a workload for the life of the workload, and determine new VM instance types, and/or configuration modifications, that optimize the performance of the workload. The optimization service may provide recommendations to users that help improve performance of their workloads, and that also increase the aggregate utilization of computing resources of the service provider network.

Abstract: A team health monitor system having a voice interface system for monitoring and improving team dynamics is described herein. The systems and techniques are directed to a voice interface system that is configured to conduct a health monitor or health diagnostic meeting in which a graduated score is received for a set of key team attributes from each of the meeting participants. The voice interface system also collects score narratives and pairs narratives with associated team attributes by determining a relevance percentage or similar criteria. The voice interface system is also configured to facilitate a consensus vote for each of the team attributes and construct an anonymized report that includes consensus scoring and composite narratives without attributing content to a particular team member or participant.

Abstract: Systems and methods for enhanced data analytics and presentation therefore are provided herein. In particular, systems and methods for graphically constructing a query for processing event-based data and identifying connections between two or more events, systems and methods for processing event-based data and identifying drivers in real-time across event-based data, and systems and methods for optimizing drivers for implementing actor encounters for achieving an objective.

Abstract: System and method for integrating systems to implement data quality processing. A business rule creation module is configured to create a business rule associated with a business term. A data quality specification module is configured to create a data quality specification based on the business rule. The data quality specification comprises (1) an identity of a column of a table stored in a database comprising data to be tested; (2) a test to perform on the data to be tested; and (3) reference data required to perform the test on the data. A validation module is configured to receive the data quality specification; retrieve data associated with the column from the database; and test the retrieved data in accordance with the test using the reference data. A result publication module is configured to return a result of the test to the data quality specification module.

Abstract: A system can receive selection of endpoints for a spool on a graphical user interface (“GUI”) and attempt to assemble a spool based on the endpoints. To do so, a plugin can execute a route-finding process that traverses routes from the endpoints. The routes can be determined by retrieving connectors from the endpoints and, for each connector, determining what parts are connected. For each connected part, the process can repeat so long as the connected part is not one of the endpoints or already in another route or spool. When the routes are complete, the connected parts can be treated as an assembly of the spool. The GUI can generate a spool sheet that uses the assembly as the spool.

Abstract: A method for correlating energy usage data and water usage data to a waste scoring system is described. In one embodiment, the method includes receiving energy usage data and water usage data from a plurality of users, identifying at least one user group from the plurality of users based on predetermined parameters, and calculating average energy usage and average water usage for each of the user groups. The energy usage data and water usage data received for an individual user may then be compared to the calculated average energy usage and calculated average water usage for at least one of the user groups, and a general waste score may be calculated for the individual user. In some cases, a plurality of sub-waste scores may be calculated indicating factors of energy usage and factors of water usage for the individual user.

Abstract: Methods, apparatus, and processor-readable storage media for machine learning techniques for automated processing of workflow approval requests are provided herein. An example computer-implemented method includes generating a machine learning model for workflow approval requests, wherein generating the machine learning model comprises automatically learning temporal-based patterns from historical data related to previous workflow approval requests; generating, in response to an additional workflow approval request, an output value by applying the machine learning model to input data related to the additional workflow approval request; comparing the output value to at least one predefined threshold value; and automatically rejecting the additional workflow approval request responsive to a result of the comparing of the output value to the at least one predefined threshold value.

Abstract: Provided are a system and method for controlling a workflow across domains on the basis of a hierarchical engine framework. Inventive workflow control makes it possible to configure a flexible hierarchical engine framework and provide a workflow service with low latency. Also, the system and method make it possible to control a workflow by building an engine and a data pipeline across domains.

Abstract: A platform is described for analyzing assessment data, including correlating assessment data with learning outcome data, and presenting analysis results through one or more interactive dashboards. A course syllabus and/or other course described information is analyzed to identify expected target outcomes to be achieved by students of the course, and to identify a relative weight of each of the various target outcomes based on their coverage in the syllabus. Assessment data describing a digitally administered assessment is analyzed to identify the categories that are assessed in the various questions of the test, and determine student performance with respect to particular categories. The platform provides interactive dashboards to present analysis results and provide integration with a continuous quality improvement (CQI) system for task tracking related to the analysis results.

Abstract: A platform is described for analyzing assessment data, including correlating assessment data with learning outcome data, and presenting analysis results through one or more interactive dashboards. A course syllabus and/or other course described information is analyzed to identify expected target outcomes to be achieved by students of the course, and to identify a relative weight of each of the various target outcomes based on their coverage in the syllabus. Assessment data describing a digitally administered assessment is analyzed to identify the categories that are assessed in the various questions of the test. The target outcomes are compared to the assessed categories to determine the extent to which the assessment is assessing each of the target outcomes, the degree of correspondence between the distribution of assessed categories and the distribution of target outcomes, and whether any gaps are present indicating that certain target outcomes are going unassessed or are insufficiently assessed.

Abstract: A platform is described for analyzing assessment data, including correlating assessment data with learning outcome data, and presenting analysis results through one or more interactive dashboards. A course syllabus and/or other course described information is analyzed to identify expected target outcomes to be achieved by students of the course, and to identify a relative weight of each of the various target outcomes based on their coverage in the syllabus. Assessment data describing a digitally administered assessment is analyzed to identify the categories that are assessed in the various questions of the assessment. The assessment data, including scores on the assessment, can be presented in an interactive dashboard to indicate how well students are performing on assessments with respect to particular learning outcomes, determine question quality, and present other information regarding assessments and/or curriculum effectiveness.

Abstract: Methods, systems, and non-transitory computer readable storage media are disclosed for determining parameters for digital campaign content in connection with executing digital campaigns using a rank-one assumption and a best-arm identification algorithm. For example, the disclosed system alternately explores response data in the first dimension and response data in the second dimension using the rank-one assumption and the best-arm identification algorithm to estimate highest sampling values from each dimension. In one or more embodiments, the disclosed system uses the estimated highest sampling values from the first and second dimension to determine a combination with a highest sampling value in a parameter matrix constructed based on the first dimension and the second dimension, and then executes the digital campaign using the determined combination.

Abstract: A technique allows a credential manager application on a client computer system to identify fields and forms on a web page. An analysis server may automatically crawl web pages and identify the fields and form, then push the information to the client computer system for use by the credential manager. If the credential manager discovers the information is not available, the credential manager may analyze the web form to discover the fields and form information, then provide the discovered information to the analysis server for providing to other client computers. The analysis server may use crowd-sourcing for asynchronous verification of field and form information discovered by the analysis server or provided by the client computer.

Abstract: Methods, systems and apparatus are disclosed to model consumer choices. An example apparatus includes a multinomial logit (MNL) engine to add a set of products having respondent choice data to a base MNL model, an aggregate building engine to improve a computational efficiency of model generation by generating a number of copies of the base MNL model, each one of the number of copies of the base MNL model exhibiting an effect of an independence or irrelevant alternatives (HA) property, a sourcing modifier to proportionally affect interrelationships between dissimilar ones of the number of products in the set by inserting sourcing effect values in the aggregate model, an estimator to estimate the item utility parameters of the aggregate model based on the number of copies of the base MNL model and the respondent choice data, and a simulation engine to calculate the choice probability.

Abstract: A system and method simulate a chat-based conversation with a human user. The system and method receive a text message through the chat system that enables a receiver to transmit an automatically generated response in real time during a chat session. The system and method recognize characters in a text message and generates an automatic prediction or classification using a conversational assistant pod that resides in a container. The system and method generate an automatic response and modify computing resources by replacing the conversational assistant pod and the container with a second conversational assistant pod and a second container without interrupting the chat session.

Abstract: Techniques for scenario planning are provided. In one example, a computer-implemented method can comprise analyzing, by a device operatively coupled to a processor, content using a topic model. The content can be associated with a defined source and is related to one or more current events. The computer-implemented method can also comprise determining, by the device, one or more portions of the analyzed content that are relevant to one or more key risk drivers using a risk driver model. The computer-implemented method can also comprise aggregating, by the device, the determined one or more portions into one or more emerging storylines based on values of one or more attributes of the topic model.

Abstract: Techniques for scenario planning are provided. In one example, a computer-implemented method can comprise analyzing, by a device operatively coupled to a processor, content using a topic model. The content can be associated with a defined source and is related to one or more current events. The computer-implemented method can also comprise determining, by the device, one or more portions of the analyzed content that are relevant to one or more key risk drivers using a risk driver model. The computer-implemented method can also comprise aggregating, by the device, the determined one or more portions into one or more emerging storylines based on values of one or more attributes of the topic model.

Abstract: Method and apparatus uses statistical principles to evaluate historical labor performance of an organization and to predict future labor needs. A system may identify patterns based on seasonality and recent performance, as well as identify parametric drivers. Illustrative parametric drivers may include a skill type, a location, and an experience level of a worker. The system may use the parametric drivers to determine and output labor needs. The communicated labor needs may enable leaders to take action to ensure that the right skill is available at the right time and in the right place for their company. The system may couple the prediction of labor needs with a prediction of labor availability to predict shortages and surpluses so that the workforce may be re-skilled or redeployed as needed.

Abstract: A Quality of Service (QoS) improvement system and method for transport network fault detection and QoS improvement so that a telecommunication network service provider can analyze the root cause on chronic performance issues and recommend potential solutions is disclosed. The system runs performance analysis on each AAV (mobile backhaul) or other transport networks and collects performance related metrics data. The system then selects a subset of the data related to certain key performance indicators (KPIs), such as latency, jitter, packet loss ratio, and availability. On this subset of KPI-related data, the system applies clustering techniques to identify clusters with similar performance issues. For each cluster, the system binds the AAV performance KPI data with one or more of the following site features—health, location, vendor, market, service type, etc.—to create a cluster map. The system can then generate inferences on root causes of the performance issues.

Abstract: A system, which is configured to generate an action for controlling a business to be carried out by a business operation system, the system is configured to: obtain business data including a plurality of attributes relating to the business from the business operation system; identify target data to be analyzed based on a distribution of a relevant indicator; analyze the target data, to thereby calculate an awareness feature, which is likely to contribute to improvement of the business evaluation indicator; generate an action for improving the business evaluation indicator based on the awareness feature.

Abstract: Examples described herein include systems and methods for management of contextual notifications on user devices. Entities can be categorized as VIP status based on scoring profiles sent from a management server to the user device. Applications on the user device can implement an SDK that reads the profiles and sets certain actions to boost scores and others to reduce scores. These local VIP scores can be sent periodically from the user device to the management server. The management server can use them in conjunction with global VIP scores for the same entities to create aggregated VIP information. This can be sent back to the user device, allowing the user device to then visualize different notifications or workflows based on whether an entity's aggregated VIP information exceeds one or more thresholds.

Abstract: A system and method for determining a level of empathy of an employment candidate is provided. One aspect includes receiving video input, audio input, and behavioral data input of an interview for each of a plurality of candidates. Behavioral data is extracted from the behavioral data input. An audiovisual interview file is saved in a candidate database. In response to receiving a request to view a candidate profile, the system selects one candidate from among a plurality of candidates, the selecting based at least in part on the empathy score of the selected candidate. In another aspect, a candidate can answer multiple questions during a video interview. The behavioral data extracted from a first portion of the video interview can be compared to behavioral data from a second portion of the video interview.

Abstract: This disclosure relates to method and system for generating strategy and roadmap for end-to-end information technology (IT) infrastructure cloud implementation.

Abstract: Techniques are disclosed for passively characterizing a type of host or computing device which may be engaged in a transaction between the host and another computing device. Observation data corresponding to one or more sessions of network traffic between an unclassified host and a second system may be passively generated by a device characterization server. The observation data can be processed by the device characterization server using a machine-learning classifier. The machine-learning classifier can be trained with a set of training data that includes multiple sessions of network traffic from multiple training data hosts. Each session of network traffic includes an exchange of multiple packets in various embodiments, including packets sent from, and packets received by, the training data hosts. Based on the processing, the unclassified host may be characterized by the device characterization server as one of a physical computing device, a virtual machine, or a container.

Abstract: A service monitoring system executing on one or more processors may have operations that are determined by control information. Control over the operation of the service monitoring system can be exerted through the use of a graphical interface. The graphical interface may present the control information of a new or existing correlation search definition for user interaction. The service monitoring system may maintain a data store of key performance indicator (KPI) data, where a KPI value in the data store is produced by a KPI-defining search query that derives the value from machine data associated with one or more entities that perform a monitored service. A correlation search definition of the service monitoring system determines how a search of the KPI data is conducted, how its data is evaluated to determine whether a triggering condition has been met, and, if so, determines what triggered action is to be initiated.

Abstract: A system and method is disclosed for configuring a performance analytics (PA) software application operational for analysis of performance data of a managed network. The system may include a PA database containing data for generating a unified graphical user interface (GUI) for consolidating configuration of key performance indicators (KPIs) of the managed network, and one or more server devices configured to receive, from a client device, a request to view information representative of a particular KPI. Based on the request, the server devices may obtain information regarding the particular KPI from the PA database and then transmit, to the client device, a representation of the unified GUI. The unified GUI may include a tabbed interface containing views corresponding to groups of related attributes of the particular KPI, the views including: (i) a data source view, (ii) a breakdown view, (iii) a data collection view, and (iv) an impact analysis view.

Abstract: A method, computer program product, and a system where a processor(s) obtains notifications of issues experienced in computing resources allocated to an entity from a shared distributed computing environment and notifications of events with discernable impacts on business performance measures of the entity. The processor(s) quantifies a technical performance impact of each issue and a business performance impact of each event. The processor(s) cognitively analyzes the business performance impact of each event and the technical performance impact of each issue to correlate a portion of the quantified events with a portion of the quantified issues. The processor(s) prioritizes, the portion of the issues by severity of business performance impact. The processor(s) mitigates the portion of the issues experienced in the computing resources allocated to the entity, in order of priority.

Abstract: Methods, systems, and computer program products for identifying relationships among a group of indicators are provided. Aspects include obtaining the group of indicators, including a number of indicators relating to an operation of a computing system. Aspects also include creating pairs of indicators, wherein the pairs of indicators includes all possible combination of the group of indicators. Aspects further include, for each pair of indicators, calculating a linear correlation score, calculating a fitting function score, determining a final correlation score based at least in part on one of the linear correlation score and the fitting function score and storing the final correlation score in a relationship database. Aspects also include creating a graphical display based on the relationship database, wherein the graphical display is configured to convey a strength relationships among the group of indicators.

Abstract: A computer-implemented method and system for streamlining interactions between a customer and a company representative. Information related to a customer is received by a company representative. A predicted future action by the customer is then calculated by a computer process wherein the calculation is based on the received information. The predicted future action is then caused to be displayed on a computer operated by a representative of the company. A conversation plan may be generated according to the information and a business rule which may be displayed on the representative's computer.

Abstract: Methods and systems for making effective use of system resources. A plurality of requests for access to a resource are received. Each request has an associated group of features. The group of features for each request is analyzed to collect observations about the plurality of requests. A function to predict an outcome of a subsequent request is generated based on the observations. Resources are allocated to service the subsequent request based on the function.

Abstract: A method performed by a control system for a work machine includes receiving machine data indicative of operating parameters on the work machine, receiving a set of performance scores indicative of relative machine performance in a set of different performance categories, each performance score being generated by a different performance score generator based on sensor data associated with the work machine, accessing a set of rules that each map one or more triggering conditions to a corresponding adjustment action on the work machine, identifying a set of potential adjustment actions by evaluating fulfillment of the set of rules based on the operating parameters and performance scores, and correlating each potential adjustment action to one or more of the performance categories, selecting a particular adjustment action, from the set of potential adjustment actions, based on an indication of a selected target performance category, and outputting a control instruction based on the particular adjustment action.

Abstract: Systems and methods are described for providing logging functionalities to code executing in an on-demand code execution system while minimizing the need to define such functionalities within the code. A logging endpoint is provided that can be called by an execution of code and passed information for logging. The logging endpoint can enrich the information with additional information, such as information regarding a state of an execution environment for the code (which additional information may not be accessible to the execution of code itself). The logging endpoint can then facilitate storage of the enriched logging information, such as by handling authentication to a storage endpoint. Thus, users of the system may author code that provides robust logging functionalities while minimizing the implementation of such functionalities within the authored code.

Abstract: A user configurable tile allows the user to configure a set of threshold values for a corresponding metric. When the metric is calculated by the system, it is compared against the threshold values to determine what range the calculated metric resides in. A corresponding tile is displayed, with a visual indicator that is indicative of the range that the corresponding metric resides in, relative to the one or more threshold values.

Abstract: A method of determining a set of prescribed actions includes receiving a configuration script identifying a set of influencers, a set of performance indicators, a model type, a target time, and a prescription method. The method further includes deriving a model of the model type based on data associated with the set of influencers or with the set of performance indicators. The method also includes projecting a set of future influencer values associated with the set of influencers and projecting a set of future indicator values of the set of performance indicators at the target time using the model. The method can further include prescribing using the prescription method and based on projecting using the model a set of prescribed actions associated with the subset of actionable influencers. The method also includes displaying the set of prescribed actions.

Abstract: A method includes obtaining a sequence of words of a query and identifying, for each word of the sequence of words, an identigen subset to produce a plurality of identigen subsets. The method further includes determining, in accordance with grouping rules, a query entigen grouping that includes a sequence of unique entigens, where an entigen of the sequence of unique entigens corresponds to an identigen of a corresponding identigen subset of the plurality of identigen subsets, and where the query entigen grouping corresponds to a meaning of associated with the query. The method further includes identifying a section of a knowledge base that substantially matches the query entigen grouping, where the knowledge base facilitates storage of knowledge as a multitude of entigen groupings. The method further includes determining an answer to the query based on the section of the knowledge base.

Abstract: A device may receive one or more data models that have been trained on a set of historical network performance indicators. The set of historical network performance indicators may include metrics associated with measuring network performance for one or more data centers. The device may receive network data for a group of user devices that are actively using the one or more data centers for network services. The device may determine a set of network performance indicators for the one or more data centers. The device may generate, by providing the set of network performance indicators as input to the one or more data models, one or more recommendations associated with improving network performance. The device may perform, after generating the one or more recommendations, one or more actions associated with improving network performance.

Abstract: A data analysis system may automatically suggest data visualizations to a user. A primary data visualization may be displayed to graphically illustrate a primary data set of a database. Criteria may be automatically applied to the database to identify a secondary data set that meets the criteria. A secondary data visualization that graphically illustrates the secondary data visualization and/or a corresponding indicator may be displayed. Multiple visualizations and/or indicators may be displayed, and the user may select one for viewing. The criteria may again be applied to the database to identify a tertiary data set. An analysis path may be recorded to enable the user to easily view the decisions made and/or the data visualizations viewed. The criteria may include determination that the secondary data set has the desired amount of data, has unique data types or descriptors, includes data previously selected by the user, or the like.

Abstract: An approach to optimizing predictive model analysis, comprising creating one or more model templates, decomposing a predictive model, wherein model information is extracted from the predictive model, storing the model information in the one or more model templates, creating a plurality of sub-models, associated with the predictive model, using the stored model information, sending the plurality of sub-models to a scoring engine, receiving results based on the plurality of sub-models from the scoring engine and generating predictions based on combining the results received from the scoring engine. The generated predictions can be sent to one or more analytic applications for further processing.

Abstract: An intelligent processing modulation system comprises: a detector detecting the condition of the processing equipment before the process for processing a raw material into a product begins; a data storage recording the information of the product; a basic database storing the information of the detector and the data storage corresponding to the product and the condition of the product for each time the process is completed; a mode database receiving the information of the detector, the data storage and the basic database and setting up the processing model; a processing equipment operating according to the parameters of the processing model received by the processing information manager; a processing information manager modifying the processing model promptly according to the result of the product in order to improve the yield rate of the product.

Abstract: Methods, systems, and computer-readable storage media for receiving, within a customer-side staging environment, a computer-executable ADR application from a vendor, testing the computer-executable ADR application within the staging environment, the staging environment executing the computer-executable ADR application using sample data, receiving feedback from a customer, the feedback including an election to deploy the computer-executable ADR application to a production environment from the staging environment, and providing the computer-executable ADR application to the production environment in response to the election to deploy the computer-executable ADR application, the production environment being sealed from data transfer to the staging environment.

Abstract: Systems, methods, and computer-readable media are disclosed for systems and methods for intelligent content rating determination. Example methods include determining presence of a first feature in a first frame of a video using an object recognition algorithm, determining presence of a second feature in an audio file associated with the video using an audio processing algorithm, and determining presence of a third feature in a text file associated with the video using a natural language processing algorithm. Certain embodiments may include generating a predicted content rating for the video using a machine learning model, where the predicted content rating is based at least in part on the first feature, the second feature, and the third feature, and using feedback data for the predicted content rating to retrain the machine learning model.

Abstract: Method, system and program product, comprising obtaining agent performance data; ranking, agents based the agent performance data; dividing agents into agent performance ranges; partitioning callers based on criteria into a set of partitions; determining for each partition an outcome value for a first agent performance range and a second agent performance range; calculating for the partitions a respective outcome value difference indicator based on the outcome value for the first agent performance range and the outcome value for the second agent performance range for the partition; matching a respective agent to a respective caller in one of the partitions, based on the outcome value difference indicators for the partitions.

Abstract: Techniques for dynamically adapting cloud applications are described. A current value of a Key Performance Indicator (KPI) of an executing cloud service instance of a cloud application is detected. A determination is made as to whether the current value of the KPI is unacceptable (e.g., either it is outside of an acceptable range or is within an adaptation region). If the current value of the KPI is unacceptable, a first application programming interface (API) is invoked to request a cloud service instance monitor to adapt the cloud service instance to operate within an acceptable KPI range. If the cloud service instance monitor was unsuccessful, the unacceptable KPI is escalated to the cloud service monitor for the type of the cloud service instance. If the cloud service monitor is unsuccessful, the unacceptable KPI is escalated to the application monitor.