Abstract: An observability system is disclosed that provides novel techniques for configuring indexable custom tags. The observability system enables customers and users to specify and create indexable custom tags in a flexible and user-friendly manner. The observability system includes a novel custom tag configuration system that enables users of the observability system to configure indexed custom tags. Using a set of user interfaces (e.g., graphical user interfaces (GUIs)), a user is guided through a workflow for configuring indexed custom tags.

Abstract: A method for manufacturing system data analysis, preferably including receiving a query, determining a set of digests, and/or determining a query result. The method can optionally include merging the set of digests and/or providing the query result. A system for manufacturing system data analysis, preferably including a set of machines, a plurality of digests, and/or a set of computing systems.

Abstract: A method for machine program analysis, preferably including determining data for a set of programs and determining relationships between the set of programs, and optionally including determining an analysis based on the program relationships, acting based on analyses, and/or operating manufacturing system machines. A system for machine program analysis, preferably including one or more computing systems, and optionally including one or more manufacturing systems.

Abstract: A method for machine program analysis, preferably including determining data for a set of programs and determining relationships between the set of programs, and optionally including determining an analysis based on the program relationships, acting based on analyses, and/or operating manufacturing system machines. A system for machine program analysis, preferably including one or more computing systems, and optionally including one or more manufacturing systems.

Abstract: A computer implemented method for determining entity attributes. The method comprises determining one or more entity identifiers, determining an entity server address of the entity based on the one or more entity identifiers, wherein the entity server address points to an entity server; verifying the entity server address transmitting a message for request for information to the entity server address, receiving entity information from the entity server; and providing, to a machine learning model, the received entity information. The machine learning model is trained to generate a numerical representations of entities based on the entity information.

Abstract: A system for predictive analysis and/or process control, preferably including one or more communication and/or computing systems, and optionally including one or more entities and/or sensors. A method for predictive analysis and/or machine operation, preferably including receiving entity data and determining one or more latent features, and optionally including determining one or more response reconstructions, determining a processed representation of the entity data, determining entity information, and/or acting based on entity information.

Abstract: A computer implemented method for determining entity attributes. The method comprises determining one or more entity identifiers, determining an entity server address of the entity based on the one or more entity identifiers, wherein the entity server address points to an entity server; verifying the entity server address transmitting a message for request for information to the entity server address, receiving entity information from the entity server; and providing, to a machine learning model, the received entity information. The machine learning model is trained to generate a numerical representations of entities based on the entity information.

Abstract: A method of computing real-time metrics for automated workflows includes aggregating a set of ingested spans into a set of traces. The method further includes executing a set of rules to determine a set of workflows associated with the set of traces, wherein each workflow of the set of workflows is associated with a respective trace of the set of traces, and wherein each workflow is operable to group together activity associated with a client process within a respective trace. The method also includes assigning a name to each workflow based on the rules and computing real-time metrics for each of the workflows.

Abstract: A system for predictive analysis and/or process control, preferably including one or more communication and/or computing systems, and optionally including one or more entities and/or sensors. A method for predictive analysis and/or machine operation, preferably including receiving entity data and determining one or more latent features, and optionally including determining one or more response reconstructions, determining a processed representation of the entity data, determining entity information, and/or acting based on entity information.

Abstract: Provided are computer systems and methods that enable the remote control of a hardware security module (HSM) device. In particular, aspects of the present disclosure enable HSM device management to be split into two components: physical management, which can be handled by a cloud provider or other IT service provider; and logical management, which can be performed by the HSM end user. Thus, a user computing system can be enabled to remotely control a HSM device that is installed in a server computing system that is remotely located from the user computing system.

Abstract: A computer implemented method for determining entity attributes. The method comprises determining one or more entity identifiers, determining an entity server address of the entity based on the one or more entity identifiers, wherein the entity server address points to an entity server; verifying the entity server address transmitting a message for request for information to the entity server address, receiving entity information from the entity server; and providing, to a machine learning model, the received entity information. The machine learning model is trained to generate a numerical representations of entities based on the entity information.

Abstract: A method for implementing software-defined community clouds includes receiving, from a first requestor, a first access request requesting access to a first project of a plurality of projects. Each project includes project data governed by a compliance regime that enforces compliance requirements. The method includes, for each compliance requirement, determining that the first access request satisfies the compliance requirement. The method includes, based on determining that the first access request satisfies compliance requirements, granting the first requestor access to the first project. The method includes receiving, from a second requestor, a second access request requesting access to a second project and determining that the second access request fails to satisfy one of the one of the compliance requirements. The method also includes, based on determining that the second access request fails to satisfy one of the compliance requirements, denying the second requestor access to the second project.

Abstract: A method for machine program analysis, preferably including determining data for a set of programs and determining relationships between the set of programs, and optionally including determining an analysis based on the program relationships, acting based on analyses, and/or operating manufacturing system machines. A system for machine program analysis, preferably including one or more computing systems, and optionally including one or more manufacturing systems.

Abstract: A method for manufacturing system data analysis, preferably including receiving a query, determining a set of digests, and/or determining a query result. The method can optionally include merging the set of digests and/or providing the query result. A system for manufacturing system data analysis, preferably including a set of machines, a plurality of digests, and/or a set of computing systems.

Abstract: Techniques may include receiving a plurality of spans of trace data at a computing system during a first time period. The techniques may include storing the plurality of spans in a span partition of a data store. The data store can contain a plurality of span partitions with spans that are grouped in the partition by trace identifier. The device may include generating a timestamp partition, with an index of timestamps by trace identifiers, for the first time period. The techniques may include storing the timestamp partition in the data store. Also, the techniques may include identifying at least two timestamp partitions that correspond to a second time period that preceded the first time period. The techniques may include generating and storing a primary compacted timestamp partition by combining the at least two timestamp partitions.

Abstract: A method for manufacturing system data analysis, preferably including receiving a query, determining a set of digests, and/or determining a query result. The method can optionally include merging the set of digests and/or providing the query result. A system for manufacturing system data analysis, preferably including a set of machines, a plurality of digests, and/or a set of computing systems.

Abstract: A method for factory analysis and/or maintenance, preferably including receiving factory information and/or associating metrics with factory components, and optionally including acting based on defect associations and/or operating factory machines. The method is preferably associated with one or more manufacturing systems and/or elements thereof.

Abstract: A method for factory analysis and/or maintenance, preferably including receiving factory information and/or associating metrics with factory components, and optionally including acting based on defect associations and/or operating factory machines. The method is preferably associated with one or more manufacturing systems and/or elements thereof.

Abstract: A computer-implemented method for determining entity characteristics. The method comprising: determining a numerical representation of each of a plurality of second entities, each numerical representation comprising a multi-dimensional vector characteristic of the respective second entity, wherein each second entity is associated with one or more first entities; reducing the dimensionality of the numerical representations to produce a plurality of reduced dimensionality numerical representations; and determining a specialisation of each of the plurality of first entities based on the respective reduced dimensionality numerical representations.

Abstract: A method of identifying a root cause of a failure for a trace within a microservices-based application includes determining if a root span of the trace is an error span resulting in an error experienced by a user at a front end of the microservices-based application. If the root span of the trace is an error span, the method analyzes a plurality of spans comprising the trace to determine if the trace comprises at least one leaf error span. If the trace comprises a single leaf error span, the method attributes the root cause of the failure in the trace to a service associated with the single leaf error span. If the trace comprises multiple leaf error spans the method attributes the root cause of the failure in the trace to a service associated with a leaf error span of the multiple leaf error spans comprising a latest starting timestamp.