Abstract: Systems and methods are provided for receiving, from a computing device, a selection of a template for a custom microservice and configuration parameters for the custom microservice, generating the template for the custom microservice using the configuration parameters, the template for the custom microservice comprising defined interfaces for accessing core microservices, defined integration points for integration with a system providing the core microservices, and stubs for custom components for the custom microservice, and providing the template for the custom microservice to the computing device, wherein custom components for the custom microservice are added to the template via the computing device using the stubs for the custom components. The systems and methods further provide for registering the custom microservice to be exposed to and accessed by a tenant with authorization to access the custom microservice along with the core microservices.

Abstract: Systems and methods are provided for receiving, from a computing device, a selection of a template for a custom microservice and configuration parameters for the custom microservice, generating the template for the custom microservice using the configuration parameters, the template for the custom microservice comprising defined interfaces for accessing core microservices, defined integration points for integration with a system providing the core microservices, and stubs for custom components for the custom microservice, and providing the template for the custom microservice to the computing device, wherein custom components for the custom microservice are added to the template via the computing device using the stubs for the custom components. The systems and methods further provide for registering the custom microservice to be exposed to and accessed by a tenant with authorization to access the custom microservice along with the core microservices.

Abstract: Techniques for implementing and using failure curve analytics in an equipment maintenance system are disclosed. A method comprises: accessing a failure curve model for an equipment model, the failure curve model being configured to estimate lifetime failure data for the equipment model for different failure modes corresponding to different specific manners in which the equipment model is capable of failing, the lifetime failure data indicating a probability of the equipment model failing in the specific manner of the failure mode; generating first analytical data for a first failure mode of the plurality of failure modes using the failure curve model based on the first failure mode, the first analytical data indicating at least a portion of the lifetime failure data for the equipment model corresponding to the first failure mode; and causing a visualization of the first analytical data to be displayed on a computing device.

Abstract: Systems and methods are provided for receiving a request to access a service catalog from a computing device associated with a tenant with authorization to access a custom microservice and the core microservices of the service catalog, and determining that the service catalog associated with the tenant comprises the custom microservice. The systems and methods further provide for determining routing information from the service catalog to make a request to the custom microservice, routing the request to the custom microservice based on the determined routing information, wherein the request is routed to a tenant computing system associated with the custom microservice, receiving a payload from the tenant computing system associated with the custom microservice, and generating a user interface comprising representations corresponding to the custom microservice and each of the core microservices, the representations corresponding to the custom microservice based on the received payload.

Abstract: Systems and methods are provided for receiving, from a computing device, a selection of a template for a custom microservice and configuration parameters for the custom microservice, generating the template for the custom microservice using the configuration parameters, the template for the custom microservice comprising defined interfaces for accessing core microservices, defined integration points for integration with a system providing the core microservices, and stubs for custom components for the custom microservice, and providing the template for the custom microservice to the computing device, wherein custom components for the custom microservice are added to the template via the computing device using the stubs for the custom components. The systems and methods further provide for registering the custom microservice to be exposed to and accessed by a tenant with authorization to access the custom microservice along with the core microservices.

Abstract: An adapter framework is provided for consuming resources provided by a database service by client applications. A location of an interface of the database service is received. Static metadata of a client application is received from the client application. Mapping of field names defined at the database service to field names defined in the client application is received at the framework. Metadata for a service interface is created at the adapter framework based on the received static metadata and dynamic metadata for dynamic fields from the database service. The mapping of field names is appended with mappings for the dynamic fields. At a runtime processor, a type of a data request from the client to the database service is determined. The request is processed and a response from the database service is generated by the adapter framework and provided to the client application in an expected format.

Abstract: Methods, systems, and computer-readable storage media for providing an insight provider including a logic component and a configuration component, the logic component including a domain-specific model, the configuration component including one or more parameter values for processing data using the domain-specific model, receiving a set of assets including data indicative of one or more assets, retrieving asset data associated with at least one asset of the first set of assets, the asset data including OT data and IT data, the OT data being provided from one or more networked devices, the IT data being provided from one or more enterprise systems, and processing the OT data and the IT data using the domain-specific model of the logic component to provide a result set, the result set including one or more of a second set of assets and enriched data.

Abstract: Methods, systems, and computer-readable storage media for providing an insight provider including a logic component and a configuration component, the logic component including a domain-specific model, the configuration component including one or more parameter values for processing data using the domain-specific model, receiving a set of assets including data indicative of one or more assets, retrieving asset data associated with at least one asset of the first set of assets, the asset data including OT data and IT data, the OT data being provided from one or more networked devices, the IT data being provided from one or more enterprise systems, and processing the OT data and the IT data using the domain-specific model of the logic component to provide a result set, the result set including one or more of a second set of assets and enriched data.

Abstract: Provided is a system and method for training and validating models in a machine learning pipeline for failure mode analytics. The machine learning pipeline may include an unsupervised training phase, a validation phase and a supervised training and scoring phase. In one example, the method may include receiving an identification of a machine learning model, executing a machine learning pipeline comprising a plurality of services which train the machine learning model via at least one of an unsupervised learning process and a supervised learning process, the machine learning pipeline being controlled by an orchestration module that triggers ordered execution of the services, and storing the trained machine learning model output from the machine learning pipeline in a database associated with the machine learning pipeline.

Abstract: Provided is a system and method for training and validating models in a machine learning pipeline for failure mode analytics. The machine learning pipeline may include an unsupervised training phase, a validation phase and a supervised training and scoring phase. In one example, the method may include receiving a request to create a machine learning model for failure mode detection associated with an asset, retrieving historical notification data of the asset, generating an unsupervised machine learning model via unsupervised learning on the historical notification data, wherein the unsupervised learning comprises identifying failure topics from text included in the historical notification data and mapping the identified failure topics to a plurality of predefined failure modes for the asset, and storing the generated unsupervised machine learning model via a storage device.

Abstract: A data container for a content package comprising one or more semantics for populating the content package with selected types of information associated with a product or service is received by a computing device of a digital services framework. An organizational structure between and within networked tenants of the digital services framework is analyzed to identify one or more recipients for the content package. A data topology associated with the product or service is analyzed to generate announcements indicative of individualized content packages for the identified recipients for the content package. The announcements are sent to the identified recipients. Requests are received for subscriptions to the content package. Based on the analysis of the organizational structure and data topology and user-defined rules and semantics, instances of the container are selectively populating for tenants who have subscribed to the content package.

Abstract: A selection indicative of one or more types of information associated with a product or service is received by a computing device of a digital services framework. A data container is generated for a content package comprising one or more semantics for populating the content package with the selected types of information. Based on the product or service, one or more recipients for the content package are identified. An announcement indicative of the content package is sent to the identified recipients. Requests for subscriptions to the content package identified recipients are received. Instances of the container are populated for identified recipients who have subscribed to the content package. The populating comprises populating the content package with the selected types of information based on the one or more semantics. The populated instances of the content package are sent to the subscribed recipients.

Abstract: Provided is a system and method for predicting leading indicators for predicting occurrence of an event at a target asset. Rather than rely on traditional manufacturer-defined leading indicators for an asset, the examples herein predict leading indicators for a target asset based on actual operating conditions at the target asset. Accordingly, unanticipated operating conditions can be considered. In one example, the method may include receiving operating data of a target resource, the operating data being associated with previous occurrences of an event at the target resource, predicting one or more leading indicators of the event at the target resource based on the received operating data, each leading indicator comprising a variable and a threshold value for the variable, and outputting information about the one or more predicted leading indicators of the target resource for display via a user interface.

Abstract: An adapter framework is provided for consuming resources provided by a database service by client applications. A location of an interface of the database service is received. Static metadata of a client application is received from the client application. Mapping of field names defined at the database service to field names defined in the client application is received at the framework. Metadata for a service interface is created at the adapter framework based on the received static metadata and dynamic metadata for dynamic fields from the database service. The mapping of field names is appended with mappings for the dynamic fields. At a runtime processor, a type of a data request from the client to the database service is determined. The request is processed and a response from the database service is generated by the adapter framework and provided to the client application in an expected format.

Abstract: Methods, systems, and computer-readable storage media for providing an insight provider including a logic component and a configuration component, the logic component including a domain-specific model, the configuration component including one or more parameter values for processing data using the domain-specific model, receiving a set of assets including data indicative of one or more assets, retrieving asset data associated with at least one asset of the first set of assets, the asset data including OT data and IT data, the OT data being provided from one or more networked devices, the IT data being provided from one or more enterprise systems, and processing the OT data and the IT data using the domain-specific model of the logic component to provide a result set, the result set including one or more of a second set of assets and enriched data.