Abstract: Monitoring and troubleshooting tools provide the capability to visualize different levels of a client's application that is deployed as a suite of independent but cooperating services (e.g., as microservices of a microservices-based architecture), collect values of monitored or tracked metrics at those different levels, and visualize values of the metrics at those levels. For example, metrics values can be generated for teams of the microservices.

Abstract: A method of rendering a service graph responsive to a query comprises generating a plurality of frontend traces and a plurality of backend traces associated with an application or website. The method also comprises determining connection information between one or more frontend traces of the plurality of frontend traces and corresponding backend traces of the plurality of backend traces. Further, the method comprises consolidating the one or more frontend traces with the corresponding backend traces to form one or more end-to-end traces using the connection information. Responsive to the query, the method comprises retrieving a set of exemplary end-to-end traces from the one or more end-to-end traces and rendering a service graph in accordance with constraints applied in the query using the set of exemplary end-to-end traces and the connection information.

Abstract: Methods and systems to sample event messages are described. As event messages are generated by one or more sources, the event messages are stored in a storage queue. An event message policy that represents conditions for storing event messages in a sample log file are input. For each event message output from the storage queue, the event message may be stored in a sample log file when one or more of the conditions of the event message policy are satisfied. The event messages of the sample log file may be displayed in a graphical user interface that enables a user to change the event message policy.

Abstract: A method of performing error analysis in a system comprising microservices comprises identifying a root cause error span from among a plurality of error spans for a trace, wherein an error span is a span that returns an error to a microservice that generates the span, and wherein a root cause error span is an error span associated with an error originating microservice. The method further comprises determining a call path associated with the root cause error span, where the call path comprises a chain of spans starting at the root cause error span, and where each subsequent span in the chain is a parent span of a prior span. Subsequently the method comprises mapping each span in the chain to a span error frame to create an error stack and rendering an image of the error stack.

Abstract: Monitoring and troubleshooting tools provide the capability to visualize different levels of a client's application that is deployed as a suite of independent but cooperating services (e.g., an application that includes a monolithic application and a microservices-based application), collect values of monitored or tracked metrics at those different levels, and visualize values of the metrics at those levels. For example, metrics values can be generated for components of the monolithic application and/or for components of a microservice of the microservice-based application.

Abstract: A method of tracking errors in a system comprising microservices comprises ingesting a plurality of spans generated by the microservices during a given duration of time. The method further comprises consolidating the plurality of spans associated with the given duration of time into a plurality of traces, wherein each trace comprises a subset of the plurality of spans that comprise a common trace identifier. For each trace, the method comprises: a) mapping a respective trace to one or more error stacks computed for the respective trace and to one or more attributes determined for the respective trace; and b) emitting each error stack computed from the respective trace with an associated pair of attributes. The method then comprises reducing duplicate pairs of error stack and associated attributes and maintaining a count for each pair of error stack and associated attributes.

Abstract: A method of analyzing a performance of a microservices-based application comprises generating a plurality of traces from a plurality of spans associated with the microservices-based application. The method also comprises generating a plurality of data sets each associated with a respective analysis mode of a plurality of analysis modes using the plurality of traces, wherein each analysis mode extracts a different level of detail for analyzing the performance of the services in the application from the plurality of spans. Further, the method comprises selecting, based on a first user query, a first analysis mode from the plurality of analysis modes for generating a response to the first user query. The method also comprises accessing a data set of the plurality of data sets that is associated with the first analysis mode and generating the response to the first user query using the data set associated with the first analysis mode.

Abstract: A mobile support system for providing wagering game play to a plurality of mobile devices includes a first game source server component configured to generate and store ball call information and a first game source adapter component configured to register a first mobile device with the first game source server. The system also includes a resolution platform configured to: receive a play request from the first mobile device, identify a bingo card, receive current ball call data from the first game source adapter component; determine an outcome of the instance of game play, and transmit an outcome message to a game host server, the outcome message causes the award amount to be awarded during display of the instance of game play on the first mobile device.

Abstract: A mobile support system for providing wagering game play to a plurality of mobile devices is provided. The system is configured to receive a play request for the wagering game from a mobile device, where the play request includes a wager amount and represents placement of a wager for an instance of game play of the wagering game. The system generates an instance of game source data for the wagering game and identifies a game play data set used for the play request. Prior to performing a withdrawal transaction of the wager amount for the play request, the system generate a wager outcome for the play request by comparing the game source data with the game play data set. After determining the wager outcome for the play request, the system causes the withdrawal transaction of the wager amount to be performed, thereby completing a placement of the wager amount.

Abstract: Techniques for generating a stream processing pipeline are provided. In one embodiment, a method includes receiving a configuration file from a data service. The configuration file represents a pipeline configuration of the stream processing pipeline, and the pipeline configuration includes representations of a plurality of different types of pipeline stages configured based on a respective customization of an entity. The method further includes generating a plurality of pipeline stages in accordance with the pipeline configuration of the stream processing pipeline; collecting, at one or more pipeline stages of a first-type in the stream processing pipeline, data items from one or more data sources; processing the collected data items at one or more pipeline stages of a second-type in the stream processing pipeline; and transmitting, at one or more pipeline stages of a third-type in the stream processing pipeline, the processed data items to the data service.

Abstract: A method of analyzing a performance of a microservices-based application comprises generating a plurality of traces from a plurality of spans associated with the microservices-based application. The method also comprises generating a plurality of data sets each associated with a respective analysis mode of a plurality of analysis modes using the plurality of traces, wherein each analysis mode extracts a different level of detail for analyzing the performance of the services in the application from the plurality of spans. Further, the method comprises selecting, based on a first user query, a first analysis mode from the plurality of analysis modes for generating a response to the first user query. The method also comprises accessing a data set of the plurality of data sets that is associated with the first analysis mode and generating the response to the first user query using the data set associated with the first analysis mode.

Abstract: A method of performing error analysis in a system comprising microservices comprises identifying a root cause error span from among a plurality of error spans for a trace, wherein an error span is a span that returns an error to a microservice that generates the span, and wherein a root cause error span is an error span associated with an error originating microservice. The method further comprises determining a call path associated with the root cause error span, where the call path comprises a chain of spans starting at the root cause error span, and where each subsequent span in the chain is a parent span of a prior span. Subsequently the method comprises mapping each span in the chain to a span error frame to create an error stack and rendering an image of the error stack.

Abstract: A computer system adapts processing of expressions by a command-line interface. An expression provided to the command-line interface is analyzed, wherein the command line interface includes pre-defined expression processing. One or more artificial intelligence agents are selected from a plurality of artificial intelligence agents based on the analysis of the expression. The expression is evaluated by the selected one or more artificial intelligence agents to determine processing modifications for the pre-defined expression processing. The expression is processed in accordance with the determined processing modifications and results are provided to the command-line interface. Embodiments of the present invention further include a method and program product for adapting processing of expressions by a shell in substantially the same manner described above.

Abstract: A method of rendering a graphical user interface (GUI) comprising an application topology graph for a microservice architecture comprises generating a plurality of traces from a first plurality of spans generated by instrumented services in the architecture and generating generate a second plurality of spans for uninstrumented services using information extracted from the first plurality of spans. The method further comprises grouping the second plurality of spans with the plurality of traces. Subsequently, the method comprises traversing the traces and collecting a plurality of span pairs from the plurality of traces, wherein each pair of the span pairs is associated with a call between two services. The method also comprises aggregating information across the plurality of span pairs to reduce duplicative information associated with multiple occurrences of a same span pair from the plurality of span pairs.

Abstract: A method of performing error analysis in a system comprising microservices comprises identifying a root cause error span from among a plurality of error spans for a trace associated with a user-request, wherein an error span is a span that returns an error to a microservice initiating a call resulting in the span, and wherein a root cause error span is an error span associated with an error originating microservice. The method further comprises determining a call path associated with the root cause error span, where the call path comprises a chain of spans starting at the root cause error span, and where each subsequent span in the chain is a parent span of a prior span. Subsequently the method comprises mapping each span in the chain to a span error frame to create an error stack and rendering an image of the error stack.

Abstract: A method of tracking errors in a system comprising microservices comprises ingesting a plurality of spans generated by the microservices during a given duration of time. The method further comprises consolidating the plurality of spans associated with the given duration of time into a plurality of traces, wherein each trace comprises a subset of the plurality of spans that comprise a common trace identifier. For each trace, the method comprises: a) mapping a respective trace to one or more error stacks computed for the respective trace and to one or more attributes determined for the respective trace; and b) emitting each error stack computed from the respective trace with an associated pair of attributes. The method then comprises reducing duplicate pairs of error stack and associated attributes and maintaining a count for each pair of error stack and associated attributes.

Abstract: A method of performing error analysis in a system comprising microservices comprises identifying a root cause error span from among a plurality of error spans for a trace associated with a user-request, wherein an error span is a span that returns an error to a microservice initiating a call resulting in the span, and wherein a root cause error span is an error span associated with an error originating microservice. The method further comprises determining a call path associated with the root cause error span, where the call path comprises a chain of spans starting at the root cause error span, and where each subsequent span in the chain is a parent span of a prior span. Subsequently the method comprises mapping each span in the chain to a span error frame to create an error stack and rendering an image of the error stack.

Abstract: The current document is directed to an integrated application-aware load-balancing component of a distributed computer system. The integrated application-aware load-balancing component is, in a described embodiment, incorporated within a distributed application that serves as a control component of multiple physical computers within a distributed computer system. The integrated application-aware load-balancing component includes a layer-4 load-balancing subcomponent that distributes communications connections initiated by remote client computers among computational nodes within the distributed computer system in order to balance the computational load applied to the distributed application and distributed computer system by the remote client computers.

Abstract: In federated learning problems, data is scattered across different servers and exchanging or pooling it is often impractical or prohibited. A Bayesian nonparametric framework is presented for federated learning with neural networks. Each data server is assumed to provide local neural network weights, which are modeled through our framework. An inference approach is presented that allows us to synthesize a more expressive global network without additional supervision, data pooling and with as few as a single communication round. The efficacy of the present invention on federated learning problems simulated from two popular image classification datasets is shown.

Abstract: A feature vector characterizing a system to be analyzed via online partially rewarded machine learning is obtained. Based on the feature vector, a decision is made, via the machine learning, using an online policy. The system is observed for environmental feedback. In at least a first instance, wherein the observing indicates that the environmental feedback is available, the environmental feedback is obtained. In at least a second instance, wherein the observing indicates that the environmental feedback is missing, the environmental feedback is imputed via an online imputation method. the online policy is updated based on results of the obtained environmental feedback and the online imputation method. A decision is output based on the updated online policy.