1164 results about "Microservices" patented technology

The invention discloses a computer big data information processing system, which comprises a data acquisition layer, a data processing layer and a data processing layer, wherein the data acquisition layer is used for accessing structured, unstructured and streaming data by using a multi-source adapter and Apache NiFi, executing format standardization, and extracting basic metadata and semantic tags through a rule engine and an NLP model; the metadata intelligent management layer integrates four modules, namely a federal learning framework for realizing cross-domain dynamic classification labels, an intelligent contract for real-time uplink storage evidence blood relationship change, a Neo4j combined graph neural network for constructing a knowledge graph for mining implicit association, and a reinforcement learning engine for optimizing a storage strategy based on frequency and risk indexes; the distributed storage calculation layer is used for processing batch and real-time metadata by adopting a Cassander + MinIO mixed framework and Spark / Flink, and dynamic partition balance performance is realized; and the application service layer is used for outputting functions of blood relationship query, classified browsing, compliance report and the like through a Vue.js portal and a Spring Cloud micro-service API (Application Program Interface) to form a full-link closed loop.

The invention discloses an internet of things multi-protocol fusion limo intelligent control system, which relates to the field of limo intelligent control and comprises a hardware irrelevant layer, a multi-protocol adaptation layer, a data abstraction layer, a programmable logic layer, a security and redundancy mechanism and an edge AI module. According to the invention, a physical bus is packaged into an independent module, an MCU / SoC and a protocol transceiver are built in, hot plugging is realized through a standardized PC I e / EdgeConn backboard, a core processing board only exposes a unified backboard interface, module drive localization execution is realized, master control firmware does not need to sense protocol details, only the module needs to be replaced when a protocol is newly added, and the master control firmware or upper software does not need to be modified. The defect that the whole vehicle firmware needs to be refreshed when a bus is replaced in a traditional system is overcome, each protocol corresponds to an independent drive micro-service deployed in a containerization mode, the drive micro-service analyzes a message into a unified data model and uploads the unified data model to a data abstraction layer, a downlink control instruction is packaged and issued according to a target protocol, and it is guaranteed that the protocols are diversified and interfaces are consistent.

The invention discloses an optical cable intelligent label full life cycle management method and system, and the method comprises the steps: extracting structured data through an XML analysis engine based on a configuration file, carrying out the semantic analysis of an unstructured text, carrying out the regression quantification of text features through combining symbol quantiles, and constructing a knowledge graph; according to the knowledge graph, dynamically adjusting the character size, the two-dimensional code position and the error-tolerant rate by adopting a generative adversarial network technology according to the optical cable type and the pasting scene, and generating optical cable intelligent labels adaptive to different scenes; collecting a label image, and converting the label image into structured label identification data including an optical cable type, a connection relation and a transmission signal type by adopting a computer vision technology; the identification data and the knowledge graph are compared, consistency is checked, potential abnormity is analyzed, influences are evaluated, and graded early warning is generated; a micro-service architecture system is constructed, data analysis, AI generation, an intelligent recognition engine and knowledge graph service are integrated, and full-life-cycle management is achieved. The intelligent level of full-life-cycle management of the optical cable label is improved.

The invention relates to the field of wireless communication and intelligent networks, in particular to a software defined radio-based ad hoc network dynamic slicing architecture and a management and control method, comprising a basic communication layer, an intelligent control layer and a service execution layer. The basic communication layer adopts a multi-distribution multi-center clustering architecture; the intelligent control layer is responsible for intelligent management and resource scheduling of the self-organizing network, and the intelligent control layer comprises a plurality of command and control nodes; and the service execution layer adopts a micro-service-based architecture, and encapsulates different network functions and service logics into independent micro-service modules. According to the method, the technical problems of high plane coupling, resource scheduling rigidness, insufficient survivability and high hardware dependency in the prior art are solved.

In order to extract more contextualized metrics associated with a particular service in a microservices-based application, a method of aggregating metrics comprises analyzing tags of spans for each trace and, based on a first predetermined set of rules, extracting one or more tags pre-selected by a user of the monitoring service. A pre-selected tag may appear in one or more spans associated with a particular service in a trace and may be extracted as a numeric metric. The method comprises computing a set of metrics for the particular service using the numeric metric extracted from the one or more spans of the trace. The method also comprises determining a set of aggregated metrics over the selected time duration for the particular service by aggregating the set of metrics over multiple traces.

The invention discloses a fault determination method and device for a micro-service system, a product and electronic equipment. Relates to the technical field of artificial intelligence. The method comprises the following steps: determining an abnormal event flow according to abnormal monitoring information; an abnormal event causal graph is determined based on an abnormal event flow, and then a fault point, a fault chain and a fault classification are determined by utilizing an intelligent agent driven by a pre-training model and combining the event causal graph and a fault mode standard. According to the method, anomaly detection, fault classification and root cause positioning of the micro-service system are realized, and closed-loop diagnosis from anomaly discovery to root cause positioning is realized; secondly, performing depth feature engineering and semantic abstraction on the refined data from the perspective of events and causal relationships, fusing system behaviors and dependency relationships dispersed in different modal data into a unified event causal graph through a graph modeling technology, and providing comprehensive and high-dimensional input for fault reasoning of an intelligent agent; and the accuracy of micro-service fault determination is improved.

The invention provides an application environment and version management method and system suitable for a low-code platform, and relates to the technical field of platform management.The application environment and version management method comprises the steps that a directed dependency graph is constructed by obtaining change records, and a dependency loop is detected and intelligently decomposed through a depth-first traversal algorithm; and packaging the node clusters into micro-services based on a function relevancy model to form an acyclic directed dependency graph, constructing a version backtracking index and a difference analysis matrix to determine a change influence range, executing incremental deployment according to a topological sequence, and recording deployment information. According to the method, the problem of version management and environment dependence in a low-code platform is solved, and the application deployment efficiency and the system stability are improved.

The invention discloses a traffic scheduling method and an electronic device, and relates to the technical field of traffic scheduling, and the method comprises the steps: determining the priority weight of a micro-service, and predicting a target traffic according to the historical traffic information of a network device; constructing a graph model according to the topological information of the network equipment and the dependency relationship of the micro-service, and performing embedded learning on nodes in the graph model to generate a state vector representing a network state; the priority weight, the state vector and the target traffic of the micro-service serve as input of a reinforcement learning model, and a traffic scheduling strategy of the network equipment is obtained; performing iterative search according to iterative particles formed by encoding the strategy network parameters of the reinforcement learning model and the feature learning network parameters of the graph model to determine reinforcement learning model parameters; and issuing the traffic scheduling strategy to the network equipment and executing the traffic scheduling strategy so as to solve the technical problem that a traffic scheduling method in related technologies is difficult to adapt to a dynamic and complex network environment and service requirements under a micro-service architecture, and the reliability of traffic scheduling is improved.

The invention discloses a unified identity authentication and access control method for a power multi-service system based on a national secret algorithm. According to the invention, through systematic deployment of SM2, SM3 and SM4 cryptographic algorithms, a full-link security protection system from identity authentication to authority management is constructed. The unified identity authentication platform adopts a mode of combining a distributed micro-service architecture and a hardware encryption machine, so that the physical security of key storage and operation is guaranteed, and the stability and response speed of the system are improved through a master-slave synchronization mechanism and interface delay control. A multi-source identity information federation acquisition mechanism realizes real-time integration of static attributes and dynamic behavior data, abnormal characteristics of user operation can be accurately captured by combining a risk assessment matrix of an improved LSTM-attention mechanism, and an SM2 bidirectional dynamic authentication protocol is automatically triggered when a risk score exceeds a dynamic threshold. Closed-loop protection of collection-evaluation-authentication-auditing is formed, and security threats such as identity counterfeiting and authority crossing are effectively resisted.

The invention discloses a distributed service deployment method and a distributed service deployment device based on Kubernetes. According to the method, resource object definition and service metadata are extracted by automatically analyzing a configuration file, and accurate acquisition and standardized processing of deployment information are realized; optimal deployment nodes are dynamically matched based on service characteristics and cluster real-time states, and resource scheduling rationality and service operation efficiency are improved; then automatically creating and starting a service instance at a target node according to an analysis result, and ensuring configuration consistency and standardization of a deployment process; and the service flow is controllably migrated to the new instance through the predefined version switching rule, so that smooth transition and risk controllability of version upgrading are realized. According to the method, the efficiency, the reliability and the version management capability of micro-service deployment are remarkably improved through full-process automatic closed loop from configuration analysis, intelligent scheduling to instance creation and flow switching.

A modular open system architecture for common intelligence picture generation is disclosed. The system receives intelligence requirements through a multimodal artificial intelligence system and calculates collection feasibility across multiple intelligence sources based on physical and temporal conditions. The system develops integrated collection plans through the containerized analytics workbench using containerized analytics modules and processes intelligence through GPU-accelerated deep learning models for automated target recognition. Satellite collection is orchestrated through satellite data acquisition optimization platform by evaluating weather conditions, orbital parameters, and sensor capabilities, while space domain awareness is maintained through space domain awareness system for real-time collection asset management. Multi-source intelligence data is fused through multi-source intelligence fusion system to populate a common intelligence picture. The system implements automated workflows for intelligence analysis and dissemination while maintaining security controls, with the containerized analytics workbench providing pattern of life analysis and dynamic exploitation through containerized microservices.

The invention provides a multi-modal neural causal inference micro-service fault positioning method and system, and the method comprises the steps: accessing observability data in a service operation process, and representing the tracking information of each request as a directed acyclic graph of a multi-modal feature; performing multi-modal feature coding and graph self-coding anomaly detection on the calling graph, and identifying an abnormal node through a reconstruction error; based on service topology prior, learning a sparse causal relationship graph between services by adopting a multi-scale neural causal inference method; calculating a node root cause score according to the causal relationship graph and the abnormal score, and executing causal path search to generate a fault propagation path; and marking the potential root cause according to the path weight of the propagation graph and the node popularity, and outputting a visual diagnosis result. According to the method, the system operation state is comprehensively described by fusing three kinds of micro-service system multi-modal data of logs, indexes and Trace in the micro-service system, and the structure-perceived causal diagram is constructed, so that accurate and explainable root cause positioning is realized.

The invention discloses an electromagnetic transient simulation and mapping method and system oriented to multi-physics field coupling, and belongs to the technical field of substation digital operation and maintenance and electromagnetic simulation. Deploying multiple types of sensors in a transformer substation, preprocessing the acquired multi-physical field data, and fusing with the three-dimensional twinborn model; a coupling algorithm is adopted to carry out multi-physical field coupling analysis, multi-physical quantity display and thermodynamic diagram superposition are realized, and scene evolution change simulation under various typical working conditions is supported; a micro-service architecture is adopted to construct a digital twin system, double closed-loop verification of simulation and actual measurement is performed through actual measurement data and simulation data of a real-model test field, model optimization is completed, and real-time mapping of electromagnetic transient dynamic simulation and a transformer substation physical entity is realized. The method improves the precision of model and entity mapping, meets the requirements of real-time tracking and response of the electromagnetic transient change of the transformer substation, adapts to the digital transformation of different transformer substations, and provides a basis for the operation and maintenance of the transformer substations.

A method for microservice authentication includes intercepting, at a first policy engine sidecar of a first microservice, a service request from the first microservice to a second microservice. The service request includes services requested from the second microservice. The method includes generating a transaction challenge, transmitting the service request, a first token identifying the first microservice, and the transaction challenge to the second microservice, and intercepting a service request response from the second microservice to the first microservice. The method includes determining whether the service request response includes a second token identifying the second microservice and a transaction challenge response generated by a second policy engine sidecar of the second microservice, and transmitting the service request response to the first microservice in response to determining the second token identifies the second microservice and determining that the transaction challenge response includes an acceptable transaction challenge response.

The invention discloses a service-oriented distributed resource automatic extraction and packaging method and a server, and relates to the technical field of micro-services, and the method comprises the following steps: querying to obtain a service packaging task state according to a service identifier; determining whether a packing task being executed exists or not; if not, performing dynamic dependency analysis on the target service corresponding to the service identifier during operation, and constructing a service dependency graph; detecting cyclic dependency based on the service dependency graph, and if the cyclic dependency exists, determining a resource acquisition range; obtaining multi-dimensional service resources from the plurality of distributed data sources; carrying out resource aggregation processing on the multi-dimensional service resources to generate a service basic information file, and packaging the multi-dimensional service resources and the service basic information file to generate a service resource package; and uploading the service resource packet to a distributed service management platform for deployment, and creating an asynchronous task. According to the method, the dependency relationship dynamically generated during operation can be effectively captured, the error rate is reduced, and the efficiency is improved.

In various examples, systems and techniques are provided that are directed to processing, using a language model, a user query associated with an artificial intelligence (AI) task. The system and techniques are used to obtain a recommendation to use, in performance of the AI task, one or more AI services—such as inference microservices—provided by, for example, a cloud AI server.

The invention relates to a group type enterprise business opportunity conflict detection and cooperative processing system based on a dynamic rule engine and semantic analysis. The rear end of the system adopts a Python Flask framework to construct micro-service, and the front end adopts a response type design; the rear end further comprises a business opportunity admission management module and a cooperative processing module which are arranged on an application layer; the business opportunity admission management module comprises a standardized business opportunity establishment application form, a business opportunity conflict identification model and a business opportunity closing application form; the business opportunity conflict identification model adopts a dynamic rule engine and a weighted matching strategy to carry out weighted processing on structured fields, unstructured texts and industry-specific word libraries; performing accurate matching on the hard indexes, and calculating the similarity of business opportunity names by adopting cosine similarity on the flexible indexes; the semantic feature extraction layer for storing the industry-specific lexicon uses TF-IDF weighted word vectors to enhance the industry-specific lexicon; the cooperative processing mechanism integrates a WebSocket technology, pushes weighted messages in real time, carries out business opportunity tracking, and pushes the weighted messages to a business opportunity closing application form to carry out business opportunity closing.

The invention relates to a micro-service architecture system based on business function and data double isolation, and the system comprises a business function splitting module which splits a single application into independent micro-services; the data physical isolation module is used for distributing an independent database instance for each micro-service; the dynamic routing control module is used for dynamically distributing flow through a load sensing strategy and integrating a fusing mechanism; and the gray release module supports flow hierarchical diversion and abnormal automatic rollback, and ensures safe switching of service versions. According to the invention, by realizing double isolation of service functions and data, the independence and the expandability of the system are improved, and the data coupling degree and the maintenance cost are reduced; the stability and reliability of the system are ensured, and the risk in the migration process is reduced; according to the method, rapid iteration and continuous delivery can be realized, the development and deployment period of new functions is accelerated, and the user experience is improved through efficient service governance and data consistency guarantee, so that the system can better cope with challenges of high concurrent access and distributed transaction processing.

An apparatus may comprise a memory communicatively coupled to a processor. The processor may be configured to receive a request to perform multiple data processing operations and determine multiple sub-dialogues corresponding to the request. The sub-dialogues are part of a plurality of IVR operations. The processor may be further configured to route the request to a microservice of the microservices based at least in part upon the sub-dialogues. The microservice may be configured to fulfill the request. The processor may generate a response to the request associated with the microservice, update publishing commands in accordance with one or more rules and policies in response to generating the response, and publish the first microservice. The publishing commands associated with the microservice may be updated in isolation from the rest of the microservices.

The invention provides an inter-micro-service dynamic secure communication method and device based on chaos cryptography. The method comprises the steps that a service provider instance registers a public key and chaos initial parameters to a service registration center; before calling, the service consumer instance acquires a public key and a chaos initial parameter of a target service provider instance from a service registration center; the service consumer instance performs key negotiation with the acquired public key by using a private key of the service consumer instance to determine a shared key; performing key derivation on the shared key and the chaotic initial parameter to generate an initial key; respectively using the initial keys to initialize the chaotic system so as to generate synchronous encryption key streams; and the two communication parties perform real-time stream encryption and decryption on the communication data between the micro-services by using the encryption key stream. The unpredictability of a chaotic system and modern cryptography can be combined, and a micro-service design mode is deeply integrated, so that a lightweight and high-security communication security mechanism which does not need to share a key in advance and can be adaptive to dynamic change of service is realized.

The invention relates to a remote sensing image data processing method and system based on a Spark architecture, and belongs to the technical field of remote sensing image data processing. The method comprises the following steps: converting a collected original file into a COG format, constructing a hybrid index through a spatial dimension reduction technology, extracting metadata and establishing a metadatabase; based on the hybrid index, quickly positioning a target tile through spatial query, reading a data block, and constructing a TileLayerRDD of a spatial partition in a Spark cluster; and dynamically assembling and calculating the directed acyclic graph according to the algorithm warehouse template, and submitting the directed acyclic graph to a Spark cluster for distributed memory calculation. According to the method, rapid retrieval is achieved through the COG format and the mixed index, pre-slicing is replaced with Spark distributed computing, the storage pressure is greatly reduced, and on-demand real-time analysis and high-concurrency online service of mass remote sensing data are finally achieved through micro-service and elastic resource scheduling.

The invention provides a low-altitude multi-source equipment data base fusion method and system based on deep learning, and belongs to the technical field of low-altitude data processing. A multi-modal dynamic strategy generation engine is adopted to analyze multi-dimensional context information such as equipment modality, space environment and task intention and generate an optimal fusion strategy instruction; according to the present invention, adaptive adjustment fusion is carried out according to the current situation, when the GPS signal is interfered, the dependence on the GPS signal is automatically reduced, the weight of other reliable signal sources is enhanced, and when the optical sensor fails in the heavy fog weather, the data processing assembly line is dynamically reconstructed, the image processing micro service is bypassed, and the radar data is preferentially processed. The dynamic self-adaption and toughness anti-interference capability of the low-altitude multi-source data fusion process is improved, various interferences can be effectively resisted, high-precision fusion output is always kept in a complex and changeable low-altitude environment, data source selection and weight are flexibly adjusted according to a real-time dynamic environment and task requirements, and the real-time dynamic environment and task requirements are met. And the accuracy and the response speed of low-altitude multi-source data fusion are improved.

The invention provides a micro-service performance problem diagnosis and repair method and system, and the method comprises the steps: obtaining various data of the operation of a micro-service system, carrying out the preprocessing of the obtained data, extracting features, and carrying out the preliminary anomaly detection; using the trained large model to identify the root cause of the micro-service performance problem, and converting each item of data into a state representation which can be understood by an intelligent agent in reinforcement learning; triggering a reinforcement learning process according to a preliminary anomaly detection result, representing a repair action adopted by a decision according to a current state, and in a decision process, guiding an intelligent agent to learn a strategy capable of effectively repairing a problem and minimizing negative effects by a target bit of a reward function; and converting the repair action obtained by the decision into actual operation, obtaining various data of operation of the micro-service system after the actual operation, calculating a reward value of the action according to the reward function, and performing large model optimization. According to the invention, the availability of the micro-service system and the stable operation of services can be guaranteed.

The invention relates to the technical field of micro-services, and discloses an Istio-based inference service global activation connection number limiting method, which comprises the following steps: step 1, when a client request is received, extracting label information in a request header, and carrying out label analysis; 2, after label analysis is completed, threshold value query is conducted, and interface response content is obtained; 3, acquiring real-time load data of the target service, and calculating a real-time dynamic threshold value; 4, performing three-level quota verification from the tenant level, the service level and the instance level; and 5, after three-level quota verification, connection processing is carried out, a connection processing result is reported, and closed-loop feedback is carried out. According to the scheme, a global and intelligent connection number limiting mechanism is constructed in a micro-service architecture, the problems of service overload, resource competition and system stability caused by sudden increase of the connection number in distributed reasoning service are solved, and dynamic sensing, intelligent decision making and accurate control of the reasoning service connection number are achieved.

Apparatus and methods are disclosed for retrieving data, responsive to received input, at a microservice supporting an application programming interface (API). A score is generated, indicating likeness of semantic content, between each of multiple candidate API-conforming queries and the received input. Queries are selected based on their scores, and executed on a live repository. Based on retrieved data, a response to the input is formulated and transmitted. Disclosed techniques are suitable for a data producer front end in a copilot having a microservice network architecture. Compared to much larger competing LLMs, comparable or superior performance is achieved for certain tasks, while computation time and hardware requirements are significantly reduced, even to a single compute node with a single GPU. One or more data producers can provide a retrieval microservice with access to various databases having respective APIs, to extend the copilot's reach. Variations and additional techniques are disclosed.

The invention provides an SDN (Software Defined Network) dynamic control system based on a cloud native architecture, and belongs to the technical field of SDN and cloud native. The system adopts a three-layer decoupling architecture of a service layer, a control layer and a data layer, wherein the service layer consists of a core network, a cloud platform and edge nodes and is used for issuing service requirements and executing a joint resource scheduling strategy; the control layer comprises four core modules, namely a micro-servitization SDN control module, a cross-domain collaborative engine module, an end-to-end service quality guarantee module and an edge collaborative optimization module, and is responsible for unified analysis, decision and scheduling to realize dynamic updating of a network strategy and multi-cluster collaborative optimization; the data layer is composed of an SDN switch and a router, and is used for executing a flow table rule and collecting network situation data. Through deep fusion of the SDN and the cloud native technology, the problems of upgrade interruption, low cross-domain collaboration efficiency and edge resource limitation of a traditional network architecture are solved, and the method can be widely applied to hybrid cloud management, industrial Internet of Things and intelligent city network scenes.

The invention provides an open platform management method and system based on dynamic reflection calling in the technical field of distributed micro-services and gateways. The method comprises the following steps: S1, forwarding an access request to an authentication center; s2, the authentication center executes identity authentication and issues an access token, and the client sends a request message to the open platform based on the access token; s3, the open platform carries out authentication, decryption and signature verification on the request message to obtain message content containing request parameters and a target service subsystem; s4, searching interface metadata and a network address of the target service subsystem; and S5, through a dynamic reflection calling engine, generating a proxy instance based on the interface metadata, mapping the request parameter into a target parameter, and through the proxy instance and the network address, calling the target service subsystem to execute the target parameter. The method has the advantages that the safe, uniform and non-intrusive open service capability is realized, and the maintainability, the safety and the evolution capability of the platform are greatly improved.

The application provides a large model-based microservice fault diagnosis and self-recovery system, and belongs to the technical field of software engineering and artificial intelligence.The application collects multi-dimensional running data of each service instance under a microservice architecture through a data collection layer, and pre-processes the collected data to adapt to the input requirements of a large model.Subsequently, a large model analysis layer analyzes the pre-processed data based on a pre-trained fault diagnosis large model, accurately locates fault causes, and generates fault diagnosis results and corresponding self-recovery strategies.Finally, a self-recovery execution layer automatically executes repair operations to realize automatic fault recovery of microservices.

A system can execute a containerized application that comprises a microservice in a decentralized service mesh architecture, and a sidecar. The system can intercept, by the containerized application, a call from the microservice that is directed to a remote endpoint, and direct the call to the sidecar. The system can communicate, by the sidecar to an identity manager, service account credentials associated with the microservice, resulting in receiving an identity token associated with the microservice. The system can determine, by the sidecar, connectivity information of the remote endpoint based on a virtual address of the remote endpoint identified in the call. The system can communicate, by the sidecar to a token exchanger, the identity token and the connectivity information, resulting in receiving an access token and a network route to the remote endpoint. The system can relay, by the sidecar, network traffic between the microservice and the remote endpoint.

The invention provides a service interface dependency relationship mining and analysis method based on AI and graph calculation, and relates to the technical field, and the method comprises the steps: constructing a dependency relationship graph, guiding random walk sampling through a meta path, adaptively calculating the radius of a dynamic sub-graph, and hierarchically detecting a framework. The detection accuracy of the abnormal dependency relationship is improved, the operation and maintenance cost of the micro-service system is reduced, and the stability and reliability of the system are enhanced.