SYNTHETIC DATA GENERATION FOR ENHANCED MICROSERVICE DEBUGGING IN MICROSERVICES ARCHITECTURES

    公开(公告)号:US20230195601A1

    公开(公告)日:2023-06-22

    申请号:US17557953

    申请日:2021-12-21

    Abstract: An apparatus to facilitate synthetic data generation for enhanced microservice debugging is disclosed. The apparatus includes one or more processors to: load a filter for a synthetic data generator for a service deployed in a datacenter system, the filter configured for the service based on service policies; prioritize synthetic parameters of the filter based on service parameters used to model microservices deployed for the service; generate a synthetic dataset for ingestion using the prioritized synthetic parameters in the filter of the synthetic data generator, the synthetic dataset generated by applying the synthetic parameters of the filter to an original infield dataset of the service; demultiplex the synthetic dataset in response to a synthetic activation profile generated using the synthetic dataset matching one or more monitored previous activation profiles of the service; and reverse map the demultiplexed synthetic dataset to match to original data in the original infield dataset.

    Telemetry targeted query injection for enhanced debugging in microservices architectures

    公开(公告)号:US11558265B1

    公开(公告)日:2023-01-17

    申请号:US17557937

    申请日:2021-12-21

    Abstract: An apparatus to facilitate telemetry targeted query injection for enhanced debugging in microservices architectures is disclosed. The apparatus includes one or more processors to: identify contextual trace of a previous query recorded in collected data of a service, where microservices of the service responded to the previous query; access an interdependency flow graph representing an architecture and interaction of microservices deployed for a service; retrieve, based on the interdependency flow graph, telemetry data of the microservices corresponding to the contextual trace; identify, based on the telemetry data, an activation profile corresponding to the previous query, the activation profile detailing a response of the microservices to the previous query; compare the activation profile to a correlation profile for the previous query to detect whether an anomaly occurred in the service in response to the previous query; and recommend a modified query based on detection of the anomaly.

    METHODS AND APPARATUS TO FACILITATE SERVICE PROXYING

    公开(公告)号:US20210328886A1

    公开(公告)日:2021-10-21

    申请号:US17359349

    申请日:2021-06-25

    Abstract: Example methods, apparatus, and systems to facilitate service proxying are disclosed. An example apparatus includes interface circuitry to access a service request intercepted by from an infrastructure processing unit, the service request corresponding to a first node; instructions in the apparatus; and infrastructure sidecar circuitry to execute the instructions to: identify an active service instance corresponding to the service request; compare first telemetry data corresponding to the active service instance to a service quality metric; select a second node to service the service request based on the comparison and further telemetry data; and cause transmission of the service request to the second node.

    ARTIFICIAL INTELLIGENCE MODEL PROMPT ADAPTATION IN PROGRAMMABLE NETWORK INTERFACE DEVICES

    公开(公告)号:US20250103965A1

    公开(公告)日:2025-03-27

    申请号:US18971998

    申请日:2024-12-06

    Abstract: An apparatus includes a host interface, a network interface, and programmable circuitry communicably coupled to the host interface and the network interface, the programmable circuitry comprising one or more processors are to implement network interface functionality and are to receive a prompt directed to an artificial intelligence (AI) model hosted by a host device communicably coupled to the host interface, apply a prompt tuning model to the prompt to generate an initial augmented prompt, compare the initial augmented prompt for a match with stored data of a prompt augmentation tracking table comprising real-time datacenter trend data and cross-network historical augmentation data from programmable network interface devices in a datacenter hosting the apparatus, generate, in response to identification of the match with the stored data, a final augmented prompt based on the match, and transmit the final augmented prompt to the AI model.

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