104 results about "Service grid" patented technology

The invention discloses an intelligent gray scale and multi-version adaptive deployment system and method based on Kubernetes, and the method comprises the steps: through an Operator which operates in Kubernetes and integrates a plurality of intelligent modules, the Operator can collect and fuse a business performance index and a technical performance index, and generates a comprehensive "version health score"; according to the real-time state of the health score, the rhythm and the step length of flow release are adaptively adjusted; meanwhile, through integration with a service grid, staged and context-based accurate flow routing is realized; when serious problems occur, safe rollback can be automatically executed, and cooling locking can be applied. According to the method, the service target and the release process are deeply bound, so that the intelligence of release decision, the self-adaptive adjustment of the release process and the fine control of the risk are realized, and the security, efficiency and success rate of software release are remarkably improved.

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 game resource scheduling management method and system based on cloud computing, and relates to the technical field of game resources, the method comprises the following steps: decomposing a server of a cloud game application, and establishing a multi-attribute micro-service; constructing a heterogeneous resource pool containing computing nodes of different architecture types; performing request type demand analysis according to the received game session request, and determining a demand micro-service combination; based on the hardware preference features and the performance portraits, configuring computing nodes of the micro-services, and deploying corresponding micro-service instances on the computing nodes; and based on the demand micro-service combination, establishing communication connection between corresponding attribute micro-service instances through a service grid, and generating a collaborative scheduling execution instruction. By means of the method and device, the technical problem that in the prior art, due to the fact that resource scheduling is coarse in granularity and hardware resources are not fully utilized, computing resources are wasted, hardware loads are unbalanced, and the performance of the game server is affected is solved, and the resource utilization rate is increased through fine-granularity task-level scheduling.

In one embodiment, service mesh monitoring with infrastructure awareness is provided herein. An example method herein may comprise: parsing, by a service mesh manager process, a package manager chart to learn a plurality of cloud resources associated with a given application; monitoring performance metrics for each individual resource for the plurality of cloud resources; aggregating the performance metrics for each individual resource into an overall performance level of the given application; and generating a holistic health report of the overall performance level of the given application that is further indicative of the performance metrics for each individual resource.

The invention relates to the cross technical field of artificial intelligence operation and maintenance and cloud native computing, in particular to an AI model full life cycle management method and system based on cloud native, and the method comprises the steps: constructing a containerized interactive development environment, and generating an invariable OCI mirror image containing a model code and a dependency library; a versioning model registration center of a three-layer storage architecture is adopted, and strong consistency management of model files and metadata is achieved; an automatic CI / CD assembly line is driven through a declarative workflow engine, and event triggering and timing scheduling are supported; the reasoning service deployment module based on the service grid realizes gray release and elastic capacity expansion and contraction; a multi-dimensional monitoring index system is established, and model performance attenuation and data drift are detected in real time; and designing an adaptive resource scheduling algorithm, and dynamically optimizing heterogeneous computing resource allocation. The resources can be dynamically adjusted according to the actual load, and high performance and high availability of the model service are ensured.

The invention discloses a traffic request scheduling method, electronic equipment and a storage medium. The method comprises the following steps: acquiring a user request corresponding to at least one workload; the service grid agent corresponding to the at least one workload is used for intercepting and analyzing the user request to obtain request metadata, and the request metadata is used for describing request attributes of the user request; scheduling decision making is carried out according to the request metadata, a scheduling decision result corresponding to the user request is obtained, and the scheduling decision result is used for determining a request processing mode corresponding to the user request; and in response to determining to accept the user request according to the scheduling decision result, forwarding the user request to the target server. According to the method and the device, the technical problems of low scheduling efficiency and poor flexibility when high-concurrency traffic requests are processed in a service grid in the prior art are solved.

The present application relates to the technical field of distributed system testing and operation and maintenance monitoring, and particularly relates to a server test environment automatic monitoring method and system, comprising: collecting a micro-service cluster directed call topology structure, constructing a distributed cell layer with node and edge vector spaces; parsing data serialization rules to extract constraint restriction mapping matrices, assembling a Hodge-Dirac operator; obtaining real-time business state vector groups to splice into zero-order co-chains, using the operator to solve an algebraic Laplace matrix to calculate a quadratic form energy functional; when determining that the quadratic form energy functional is greater than zero, generating an early warning signal, constructing and solving a discrete layer diffusion dynamics equation based on the algebraic Laplace matrix, obtaining a state compensation update matrix; finally, analyzing the state compensation update matrix into reverse rollback and cache erasure instructions, and submitting the instructions to a service mesh data plane proxy component for execution. The present application realizes code-free cross-node semantic conflict quantification and distributed consistency state self-healing closed loop.

This invention discloses a service mesh user status verification method, apparatus, device, and medium. The method includes: acquiring an access request sent by a client; wherein the access request carries a predefined level token; parsing the predefined level token to obtain predefined level token information; determining whether the predefined level token information meets the access requirements; and if the predefined level token information meets the access requirements, allowing access to the service mesh. This technical solution, by classifying tokens into different levels, can reduce the parsing time on the service mesh side and improve throughput.

The invention provides a data processing method and device for a service grid platform and electronic equipment, and the service grid platform is connected with a registration center through a first controller, and obtains specified service data; based on a target service selected by a user and included in the service grid platform, generating service configuration data corresponding to the target service, issuing the service configuration data to k8s, and storing the service configuration data; the first controller monitors change of service configuration data in k8s through the k8s API-Server, obtains a registration center service model of a target service based on the service configuration data stored in the k8s, and converts the service grid platform service model into an agent service model to be issued to all agents; according to the method, the registration center is automatically docked, so that the service information and the instance information of the registration center can be synchronously displayed on the service grid platform, real-time synchronization of the grid platform and the service grid platform is realized, and manual participation is not needed.

According to one embodiment, a method, computer system, and computer program product for gamification of a cloud application is provided. The present invention may include intercepting communications between an end device and the application using a service mesh; analyzing frontend code of the application and external and internal network traffic of the application to produce a plurality of analyzed data; identifying an application-agnostic gamification strategy based on one or more user interface (UI) elements in the application; identifying an application-aware gamification strategy based on the plurality of analyzed data; and dynamically injecting gamification elements from the identified gamification strategies into the frontend code of the application.

This invention provides a technique for microservice scheduling and improving data read / write efficiency based on runtime state analysis. Microservice systems have become one of the fundamental technology platforms for building large-scale, complex applications. By encapsulating modular information processing units in a lightweight virtual machine manner, high fault tolerance is achieved. Various application functions are orchestrated through service mesh to realize stable large-scale, complex application systems. Microservices often need to access multiple data sources or data lake systems, and the location of data has a critical impact on data read / write efficiency. For example, in a distributed storage system, having the execution node of a microservice coincide with or be close to the data storage node will greatly improve data processing efficiency. Addressing the efficiency problem of microservices in data-intensive scenarios in large-scale applications, this invention proposes a technique based on analyzing the runtime state of data read / write operations to determine the optimal location for microservice scheduling and execution. By shortening the data path, data I / O efficiency is effectively improved, enhancing the performance of building large-scale, data-intensive application systems based on microservices.

A system can intercept, by a kernel-space application of a node of nodes, a call from a microservice that is directed to a remote endpoint that is external to a decentralized service mesh architecture, wherein the kernel-space application operates in a kernel space of the node, and wherein the microservice executes in a user space of the node. The system can perform, by the kernel-space application, an authorization check on the call based on the microservice and a virtual address of the remote endpoint identified in the call, to produce an authorization result determine, by the kernel-space application, connectivity information of the remote endpoint based on the virtual address of the remote endpoint identified in the call. The system can relay, by the kernel-space application, network traffic between the microservice and the remote endpoint, based on the authorization result indicating that the call is authorized and using the connectivity information.

The present disclosure provides a serialization and deserialization method of an FPGA-based IPU acceleration service grid. The serialization and deserialization method of the FPGA-based IPU acceleration service grid comprises: determining all message objects of remote procedure calls to be sent and received; allocating a sending descriptor ring and a receiving descriptor ring and configuring a control register through a memory-mapped I / O operation; defining a message format of a remote procedure call through a domain-specific language for serialization and deserialization; when in a transmission mode, creating a sending descriptor and filling it into the sending descriptor ring; the FPGA obtains the sending descriptor from the sending descriptor ring and sends encoded data to a system-on-chip; and the system-on-chip sends the encoded data through a network transmission protocol. The embodiments of the present disclosure solve the problems of performance bottleneck, high delay and high CPU resource occupation in the prior art.

In one embodiment, an illustrative method herein comprises: obtaining, by a process, a file having a given size; assigning, by the process, the file to a particular size-range bucket of a plurality of size-range buckets of a data ingestion pipeline, the plurality of size-range buckets having a corresponding size-based configuration; and forwarding, by the process, the file into a particular size-based service mesh ingress gateway of the data ingestion pipeline according to the particular size-range bucket to cause processing of the file within the data ingestion pipeline according to the corresponding size-based configuration of the particular size-range bucket.

The embodiment of the application discloses a service communication method and a service grid system. The method is applied to a service grid system, the service grid system comprises a first Pod, a network management Pod and a second Pod, the first Pod comprises a first service container, and the second Pod comprises a second service container; the method comprises the following steps: using the first service container to send target data to the network management Pod based on a first redirection rule, the target data being data required by the first service container to send to the second service container; and using the network management Pod to send the target data to the second service container based on a second redirection rule after the network management Pod acquires the target data sent by the first service container. The service communication method and the service grid system can optimize the data transmission path and improve the management efficiency of network traffic.

Network traffic external to a service mesh can be analyzed and displayed. For example, a system can receive first telemetry data associated with a service mesh and can receive second telemetry data associated with an external virtual application network. The system may then determine at least one connection point between the service mesh and the external virtual application network based on a comparison of the first telemetry data and the second telemetry data. The connection point can include a flow of network traffic between the service mesh and the external virtual application network. Additionally, the system can generate a graphical user interface, which can include a first section associated with the service mesh, a second section associated with the external virtual application network, and a visual indicator of the connection point between service mesh and external virtual application network.

Systems, apparatus, articles of manufacture, and methods for providing hardware enforcement security for a service grid are disclosed. An example first server for a service grid, disclosed herein, to provide hardware-enforced security for the service grid, includes programmable circuitry, the programmable circuitry is to implement at least one of instantiating the machine-readable instructions or executing the machine-readable instructions to detect a second server of the service grid, store a public key of the second server in the first enclave, and add the second server to the service grid after attestation of the second enclave is obtained.

Embodiments of the present disclosure relate to a data processing method and device of a DPU service grid and a medium, wherein the method comprises: listening to socket mapping start information set in a preset socket mapping setting component through a preset socket control component; in response to listening to the socket mapping start information, obtaining candidate resource configuration information issued by a data control plane; determining whether the candidate resource configuration information corresponds to a DPU service grid that matches the DPU service grid corresponding to the socket mapping start information; when the DPU service grid corresponding to the socket mapping start information is matched, adding socket mapping configuration information in the candidate resource configuration information to generate target resource configuration information; and sending the target resource configuration information to the corresponding DPU service grid, so that the corresponding DPU service grid performs socket mapping processing on a data request according to the target resource configuration information. In this technical solution, the throughput and response speed of the system are improved.

The invention provides a configuration management method and system for service layer routing, the method is executed by a routing control component, and the method comprises the following steps: obtaining normalized routing data which is generated by a centralized arrangement point and contains a target service node identifier of a source service and a target service, and analyzing the target service node identifier of the target service; querying a real physical routing attribute corresponding to a target service node identifier of the target service from the service discovery component, and replacing the target service node identifier in the normalized routing data with the real physical routing attribute to form an executable routing configuration; the executable routing configuration is distributed to the service side vehicle associated with the source service, so that the service side vehicle generates a service layer routing table, and the service layer routing table is used for guiding the flow sent by the source service to be forwarded, so that batch configuration and efficient dynamic updating of service layer routing in the service grid are realized; the problems of insufficient batch processing capability and low dynamic updating efficiency in the prior art are solved.

A system and method for optimized generation of cloud deployment configurations for an application is provided. The invention provides for receiving parameters associated with application deployment configuration generation and deployment of application on a target cloud platform. The parameters are processed for generating an application source code template. Cloud deployment configuration is generated based on generated application source code template. Package deployment associated with application deployment is automated by integrating with Application Programing Interfaces (API) for abstracting packaging applications to be deployed on target cloud platform. Pipeline inputs associated with target cloud platform are processed for determining cloud deployment configuration constraints associated with application source code. Service mesh configuration files are generated for deployment of application to target cloud platform by processing cloud deployment configuration constraints associated with application source code. A cloud deployment template is generated for deploying application associated with application source code to target cloud platform.

The application discloses a data request method and device based on a service grid and electronic equipment, the method is applied to the technical field of cloud computing, and the method comprises the following steps: receiving a data request initiated by a client; determining a service node which needs to be called from a service node in which a service grid is in a running state according to the data request, and obtaining a target service node; accessing the target service node through a target control plane, and obtaining request data corresponding to the data request. Through the application, the problem that the response time of a data request is relatively long due to a long calling link when a service is called through a distributed micro-service architecture in the related art is solved.

The invention discloses a request monitoring method, a server, an electronic device, a storage medium and a program product, and relates to the technical field of computers, the method is applied to a target server, and the target server provides at least one service; comprising the steps of obtaining target original monitoring data through a target service grid under the condition that a monitoring query request for a target service is received; performing target processing on the target original monitoring data through a target data processing component, and obtaining service request monitoring data for the target service in a target time period; the target processing comprises at least one of filtering processing, induction processing, supplementary processing and calculation processing, the service request monitoring data comprises the service request amount and the service feedback delay duration, and the technical problem that the request monitoring data acquired based on the target service grid in the target time period is inaccurate is solved.

The embodiment of the disclosure relates to a DPU service grid distributed flow limiting method and device, equipment and medium; each Sidecar agent corresponding to each service on a host is unloaded, and a centralized agent corresponding to each service is installed on a DPU, and the method comprises the following steps: the centralized agent receives a service request and obtains a target service; whether flow limiting is performed is determined based on the target service and a pre-cached flow limiting rule; in the case of performing flow limiting, a control plane component on the host requests a distributed lock corresponding to the target service from Kubernetes; when the centralized agent receives the distributed lock sent by the control plane component, a current remaining flow limiting quota of the distributed lock is obtained; and when the request traffic of the service request is less than or equal to the current remaining flow limiting quota, the service request is responded. Therefore, flow limiting execution is unloaded to the DPU, the burden of the host CPU is reduced, flow limiting processing is performed through the centralized agent, and the processing efficiency and accuracy are improved.

Embodiments of the present disclosure relate to a data processing method, system, device and medium based on DPU service grid, wherein the method comprises: in response to initiating a first service request to a second container group, calling a preset DPU tracking data packet in a host to generate first tracking header information corresponding to the first service request, and sending the first service request carrying the first tracking header information to the DPU service grid; wherein the DPU service grid generates second tracking header information of the second container group according to the parsed first tracking header information, and sends a second service request carrying the second tracking header information to the DPU service grid corresponding to the second container group according to the first service request. In the technical solution, the addition of tracking header information is realized based on the preset DPU tracking data packet in the specific directory of the host, which reduces the occupation of related resources, improves the performance of business application, and dynamically selects the tracking protocol to realize flexible tracking management.

The invention relates to a method for flow limiting of a micro-service. The method comprises the following steps: generating a control plane configuration of a service grid for flow limiting of the micro-service based on a flow limiting demand for the micro-service and according to the flow of the micro-service and measurement of system resources; a control plane component of the service grid converts the control plane configuration of the micro-service flow limitation into data plane configuration of the service grid for the micro-service flow limitation of the micro-service and pushes the data plane configuration to an agent of the service grid; and performing traffic limiting by an agent of the service grid on traffic sent to the micro-service based on the data plane configuration of the micro-service traffic limiting. The disclosure also relates to a system and a computer program product for microservice traffic limiting.

A packet is received by a hypervisor from a first container, the packet to be provided to a second container, the packet including a header including a first network address associated with the second container. A network policy is identified for the packet in view of the first network address. A second network address corresponding to the second container is determined in view of the network policy. A network address translation is performed by the hypervisor to modify the header of the packet to include the second network address corresponding to the second container.

Systems and methods for data plane management are disclosed herein. An exemplary method includes deploying a native module embedded in a service routing layer of a service grid; distributing a security policy to the native module from a bootstrap layer of the service grid, wherein the security policy enables the native module to detect a mode indicating sensitive information in service grid data; evaluating service grid data through the native module by using the security policy; and when the native module detects a pattern in the service grid data, transmitting telemetry data to a cloud-based command module.

In one embodiment, a method herein comprises: determining, by a service mesh process, whether a problematic metric for an application is based on a transport network to a cloud infrastructure or is within the cloud infrastructure; delineating, in response to the problematic metric being within the cloud infrastructure, cloud infrastructure network contribution versus application microservice architecture contribution to the problematic metric; determining, in response to the application microservice architecture contribution being a primary contributor to the problematic metric as compared to the cloud infrastructure network contribution, whether the problematic metric is due to a software issue or a hardware issue of the cloud infrastructure, a high load issue with application microservices of the cloud infrastructure for the application, or else an issue with the application itself; and exporting a corresponding determination related to whether the problematic metric is due to the transport network, the cloud infrastructure, or the application itself.

A seamless pod migration system for Kubernetes environments is disclosed. It includes: a predictive analytics module; a traffic management module which manages traffic routing using a service mesh tool; a volume management module which creates snapshots of a volume of a pod in a source node and clones the volume to a target node; a migration controller which determines migration needs, initiates migration requests to a Kubernetes control plane, checks compatibility between the source node and the target node, and manages data migration; a monitoring module which continuously monitors metrics when data migration is proceeded and reporting performance of the data migration to the traffic predicting server; and a readiness probe module which informs the migration controller when new pods in the target node are available, prompting it to initiate migration requests to the Kubernetes control plane to serve data traffic.