382 results about "High availability" patented technology

The invention discloses a key value storage system indexing method oriented to an NVM-NVMe SSD (Non-Volatile Memory-Non-Volatile Memory Express Solid State Disk) hybrid architecture, which comprises the following steps of: constructing a heterogeneous storage architecture taking cold and hot data perception as a core driving mechanism, coordinating and managing two types of storage media, namely a non-volatile memory NVM and a solid state disk NVMe SSD, and realizing efficient identification, layered writing and dynamic migration of cold and hot data. According to the method, the characteristics of low delay, durability and byte addressing of the NVM are utilized, the frequency and I / O overhead of Flush and Compaction operations are reduced in a data write-in path, meanwhile, the problem of mixed storage of cold and hot data is avoided, and therefore the overall performance and storage efficiency of a system are remarkably improved. In addition, by introducing an asynchronous migration module, the method can dynamically adapt to the change of data popularity along with time evolution, and effectively support high performance and high availability of the key value system in long-term operation.

The invention provides a data center interconnection link fault self-healing and path switching method, which comprises the following steps of: acquiring multi-dimensional link performance monitoring data, establishing a standardized time sequence database, realizing link health degree multi-index trend prediction by combining an LSTM-Attention model, and determining the link health degree according to the LSTM-Attention model. Risk-aware dynamic path selection and switching for multiple business scenes are realized by combining business service sensitivity modeling, path inherent stability quantification, nonlinear adaptive switching criteria and a debounce switching process, the response accuracy and the business adaptation degree of path switching are improved, false triggering and service interruption risks can be remarkably reduced, and the path switching efficiency is improved. And the high availability and robustness of routing in a complex network environment are enhanced.

The invention relates to the technical field of distributed storage, can be applied to business scenes of financial science and technology, medical health and the like, and discloses a data storage method, device, equipment and medium based on partition identifier mapping, and the method comprises the following steps: receiving a file and dividing the file into data blocks to generate block identifiers; generating a partition identifier based on the file identifier and the block identifier through hash mapping; creating a partition disk pack mapping table and writing an initial relationship; querying the mapping table to obtain a disk group, and writing the data block into a physical disk to generate a copy; monitoring the health of the disk, keeping the partition identifier and the block identifier unchanged when a fault occurs, and updating the mapping relation to a new disk group; and receiving a read-write request of the target partition identifier, querying the mapping table to obtain the target disk pack, and executing access. According to the method, the partition identification and the block identification are kept unchanged, fast fault tolerance is achieved only by updating the mapping relation, metadata updating expenditure is reduced, bottom layer change is shielded through partition identification routing, and access transparency and high availability are achieved.

The invention discloses a failover method and device, electronic equipment and a storage medium, and relates to the technical field of distributed storage, and the failover method comprises the following steps: determining a first disk resource group corresponding to a first storage node and a second disk resource group corresponding to a second storage node; and establishing a double-control relationship between the first disk resource group and the second disk resource group. And after the establishment of the double-control relationship is completed, carrying out fault switching on different disk resource groups under the double-control relationship based on the first mechanism and the second mechanism. The technical problem that in a distributed storage system, efficient and safe disk resource management and data access control of a fault controller cannot be effectively achieved under a double-controller architecture is solved, and the technical effects of improving rapidness, smoothness and automatic back-switching of fault switching and remarkably improving the high availability of the distributed storage system are achieved.

Techniques are described for enabling a container service of a cloud provider network to detect imbalances of container placements across a selected set of availability zones (AZs) and to automatically rebalance placement of the containers, if needed. An actual distribution of containers may differ from an expected distribution according to a configured placement strategy, e.g., due to an outage or other operational issue affecting one or more of the AZs, scaling operations over time, and the like. In these and other scenarios, the container service can rebalance placement of the containers by terminating one or more containers in one or more of the AZs and launching additional containers in one or more other AZs to restore a more desirable balance. The periodic rebalancing of containers in this manner improves a container-based application's ability to load balance demand and further improves application availability by ensuring sufficient capacity is spread across multiple AZs.

The invention discloses a road berth charging and control system for realizing multi-level fault tolerance and a method thereof, and belongs to the technical field of intelligent traffic systems and Internet of Things. The system adopts an edge computing and distributed sensing collaborative architecture, and is composed of an edge controller (ECU) and a sensing and control unit (SCU) deployed in a berth. High availability of the system is ensured through fault-tolerant design of three core dimensions: firstly, perception layer fault tolerance dynamically adjusts data fusion weights of geomagnetism, millimeter wave radar and visual AI according to real-time environment data such as rainfall and electromagnetic interference by integrating an environment perception sub-module; secondly, network layer fault tolerance utilizes an immutable transaction log and a Saga distributed transaction compensation mechanism to realize local charging and digital RMB double offline payment when cloud connection is interrupted, and data consistency is ensured after network recovery; and finally, a hardware layer establishes a neighborhood cooperation protocol based on a signature agent command through fault tolerance, and a healthy node is allowed to act as an agent fault node through safety verification to execute an unlocking instruction. According to the invention, the problems of environmental interference, network interruption, single-point hardware failure and the like in unattended parking management are effectively solved, and the robustness and financial security of the system are remarkably improved.

The invention provides a high-availability system based on a container platform, a container calling method and electronic equipment, and the method comprises the steps: pre-creating and activating a container copy through a container scheduling module according to the resource state of each container node and a priority constraint condition in the early stage of fault occurrence, and then when a fault event occurs, calling the container copy in advance; and in response to the fault event reminding message, calling an interface of the container scheduling module to create a new service instance in the container copy, carrying out synchronous processing on the container state based on the new service instance, and migrating the flow on the fault container instance to the new container instance. Therefore, in a high-concurrency scene, by selecting the embodiment of the invention, the flow is immediately taken over through the pre-activated standby container copy when a fault occurs, so that zero-shutdown container switching is realized, the high availability of a container platform is remarkably improved, and smooth operation of services is ensured.

The invention relates to the technical field of containers and micro-service architecture, and discloses a K8s-based Juser Notebook container arrangement method, which comprises the following steps of: S1, packaging Notebook into a Docker mirror image file; s2, mounting a Notebook configuration file on the K8s cluster through a ConfigMap (Configuration Map); s3, deploying and defining the number of copies of the Notebook application through Deployment; S4, configuring a service network and an ingress network; S3, deploying and defining the number of copies of the Notebook application through Deployment; s5, a cloud storage mode is adopted, and calculation and storage are separated; and S6, K8s API automatic management is carried out. The deployment process is simplified, the maintenance and management difficulty is reduced, and the resource utilization rate is improved; a cloud storage mode is adopted, separation of calculation and storage is achieved, and environment configuration is simplified; the Ingress provides network functions such as flow management and reverse proxy, so that the Notebook service is easier to access and integrate; the K8s cluster can ensure the high availability of the Notebook service; and when a fault occurs, quick recovery is realized, service interruption time is reduced, monitoring and management are easy, and management and operation and maintenance efficiency is improved.

The invention provides a rule engine management method and device, equipment, a storage medium and a program product. Rule definition data is acquired, the availability of an external cache service is detected, and in response to the fact that the external cache service is unavailable, rule cache data is constructed through a local cache service; analyzing the rule execution request in response to the rule execution request, and constructing rule execution context information based on a request analysis result; selecting a rule engine based on the rule type information, and matching the rule cache data of the target version based on the rule execution context information; analyzing condition expression information in the rule cache data of the target version, and obtaining execution path information based on a rule analysis result and a rule execution context information evaluation condition combination; and executing the rule cache data of the target version based on the execution path information, and processing node logic based on the rule engine to generate a rule execution result. Wherein the high availability of the system is ensured by automatically detecting and switching the cache service.

The invention provides a training method, a server, equipment, a medium and a product, and the method comprises the steps: obtaining the key information of a plurality of teacher models trained by a first server from the first server, and the training data of each teacher model comprises a first group of wafer sample images, training a first pre-trained student model based on the key information of each teacher model and each second group of wafer sample images to obtain each candidate student model, determining a target momentum parameter based on the performance index of each candidate student model and the momentum parameters of the plurality of teacher models, and obtaining a target momentum parameter of the candidate student model based on the candidate student model corresponding to the target momentum parameter. And determining a wafer defect detection model. The wafer defect detection model trained by the method can give full play to the potential adaptive ability, generalization ability, high availability and high reliability of AI, thereby ensuring that the model can adapt to the requirements of the semiconductor manufacturing industry.

The invention provides a firmware non-inductive updating method and system for storage equipment, and belongs to the technical field of the storage equipment, and the system for the firmware non-inductive updating of the storage equipment comprises the following steps: reserving an RAM (Random Access Memory) area; a context management module; a firmware update processing module; a reset control module; and a context recovery module. According to the method, device reset and service interruption caused by firmware updating are thoroughly eliminated, and strict requirements of high-availability scenes such as a cloud server and an industrial control system are met; state decoupling is carried out between front-end and back-end / firmware transactions, and a key front-end operation state is solidified in an RAM (Random Access Memory), so that new firmware can'thermally take over all unbiased transactions, and seamless switching in a real sense is realized.

The invention provides a server delivery and operation and maintenance automation system oriented to multi-platform collaboration, and aims to solve the problems of split delivery process, lagging expansion response, high operation and maintenance complexity and the like in a heterogeneous infrastructure environment. According to the system, by constructing a multi-platform adaptive abstraction layer, bottom layer differences of private cloud, job scheduling platforms and the like are shielded, and unified modeling and standardization of delivery and operation and maintenance processes are achieved; on the basis, key links such as installation file generation, expansion file generation, configuration injection and deployment verification are integrated, an end-to-end one-key delivery assembly line is built, and rapid and consistent deployment of a cross-platform environment is supported; meanwhile, an automatic operation and maintenance closed loop is constructed, and operation and maintenance operations such as health examination, fault warning, configuration repair, service restart, node replacement and elastic capacity expansion and contraction are automatically executed by collecting operation states, logs and performance indexes of the server and the service in real time and combining a preset strategy or an intelligent analysis model. By means of the method, efficient delivery and intelligent capacity expansion of server resources are achieved, and the autonomous operation and maintenance capacity, the high availability and the service continuity guarantee level of the system in a complex multi-platform mixed deployment scene are remarkably improved.

The invention discloses a sub-health node switching method and device of a database cluster, equipment and a medium. Comprising the steps of collecting multi-dimensional resource indexes of all database nodes in a database cluster based on a preset period, and calculating a real-time health score of each database node by using a health assessment model; when the real-time health score is lower than a sub-health judgment threshold in a preset step length, marking the real-time health score as a sub-health master node; acquiring the real-time health score, the resource margin and the data synchronization delay of the standby node, and selecting a target standby node; switching the data service access from the sub-health master node to the target standby node, and changing the role identifier of the target standby node as the master node; and taking the sub-health main node as a standby node, completing state reconstruction of the database cluster, and putting into a next acquisition period. According to the embodiment of the invention, active identification and seamless switching of the sub-health nodes are realized, service interruption is effectively avoided, and high availability and service continuity of a distributed database cluster are improved.

The invention provides an intelligent operation and maintenance method and system for an industrial computing network, electronic equipment and a storage medium, and the method comprises the steps: deploying computing power agents at heterogeneous computing power nodes to obtain operation and maintenance events in a unified manner, and carrying out the centralized root cause analysis of the operation and maintenance events through a cloud end, so as to match an operation and maintenance strategy, the method comprises the following steps: acquiring an operation and maintenance strategy library, issuing the operation and maintenance strategy to a corresponding computing power agent for execution and feeding back a result, and finally performing closed-loop updating on the operation and maintenance strategy library and an artificial intelligence model based on a complete event case, thereby realizing unified perception of heterogeneous dispersed computing power nodes through the computing power agent, and solving the problem that unified management and monitoring are difficult due to resource dispersion; through automatic root cause analysis and strategy matching, a fault root cause can be rapidly and accurately positioned and an operation and maintenance scheme can be generated so that serious dependence on artificial experience can be eliminated and fault processing time can be substantially shortened. Through continuous optimization of a closed-loop learning mechanism, the operation and maintenance automation level is greatly improved, and high availability and stability of an industrial computing network are guaranteed.

The invention discloses an electric power information system safety test system and method, and the system comprises a test management scheduling platform, a multi-level test execution engine, a real-time lossless collection and monitoring module, an intelligent analysis and decision engine, a digital twin simulation test platform, and a system self-protection and toughness evaluation module. According to the security test system and method for the electric power information system, all-around and deep security coverage of the electric power information system is realized, the breadth and depth of vulnerability discovery are remarkably improved, meanwhile, a real-time security test with lossless business is realized, high continuity and high availability of electric power production business are guaranteed, and secondly, the security of the electric power information system is improved. The intelligent and automatic testing process is realized, and the testing efficiency and the accurate decision-making capability of safety management are greatly improved.

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 relates to a distributed cognitive map construction and dynamic updating system and method. The distributed cognitive map construction and dynamic updating system comprises a map construction module, an incremental updating module, a distributed consistency module and a query optimization module. The graph construction module is used for converting multi-source and multi-mode heterogeneous fashion data into a unified and structured knowledge graph; the incremental updating module is used for realizing dynamic maintenance and real-time performance of the knowledge graph; the distributed consistency module is used for ensuring high consistency, high availability and change traceability of knowledge graph data among a plurality of nodes; and the query optimization module is used for providing efficient and flexible knowledge graph query capability and carrying out rapid retrieval and complex analysis on fashion knowledge. By means of the design, high-availability, high-consistency and semantic-rich fashion cognitive map construction, maintenance and updating are achieved.

The invention relates to a server cluster load balancing method based on improved consistency Hash and Redis, and the method comprises the steps: firstly constructing a modular cluster architecture comprising a user management layer, a load balancing layer and the like, and collecting node hardware performance parameters and real-time load data through a cluster state monitoring layer; the load balancing layer dynamically calculates the number of virtual nodes based on parameters such as a node performance ratio, maps a hash ring and positions a target physical node by adopting an improved consistency hash algorithm, and allocates a request in combination with a dynamic scheduling strategy; and the cluster high-availability layer realizes high-efficiency switching of main and standby devices through an election queue mechanism, and completes redundant backup and synchronous sharing of Session data by means of a Redis cluster. According to the method, the problems of data inclination, low efficiency of master-slave switching, inconsistent Session sharing and the like in the traditional technology are solved, the cluster load balancing efficiency and high availability are improved, and the method is suitable for high-concurrency scenes such as medical treatment, finance and e-commerce.

The invention discloses a data sharing and deployment system and method of a cross-hierarchical regional independent system, and a medium, and aims to solve the problem that global strong-consistency basic data is difficult to manage due to high autonomy of a regional system in the prior art. According to the method, three technologies of service double-instance disaster recovery, CDC real-time data synchronization and Nacos dynamic routing are fused, a mixed mode of central centralized reading and writing and local disaster recovery backup is constructed, two service instances connected with a central database and a local backup database are deployed in each region, data are synchronized to the local backup database in real time by utilizing the CDC technology, and the data are stored in the local backup database in real time. And the online state of the service instance is dynamically adjusted through Nacos, so that the central data is accessed when the network is normal to ensure strong consistency, and the local backup service is automatically switched to ensure high availability when the network fails.

To provide high availability scheduler event tracking for scheduler configuration such as IBM Z workload scheduler configuration.SOLUTION: By a controller, an operational status of a tracker system that is configured to track and record a current status of a job and to report completion of the job to the controller, is monitored. The recording includes storing two copies of the current status. In response to determining, based on the monitoring, that the tracker system is operational, reception of a job completion message from the tracker system is waited for, and a job completion action based on the reception of the job completion message is performed. In response to determining that the tracker system is not operational, the current status of the job is obtained from a shared memory location, and the job completion action based on the current status indicating that the job has completed is performed.SELECTED DRAWING: Figure 1

The application discloses a cloud measurement and control arrangement architecture, method and system based on micro services, belongs to the field of combination of spaceflight measurement and control and cloud computing, and comprises: a service arrangement architecture after cloudization of a measurement and control baseband, which adopts micro services and a layered thought, performs hierarchical and service division of the arrangement architecture, and realizes high availability, high cohesion, low coupling and scalability of the cloud baseband arrangement architecture; a customizable arrangement rule model, which realizes self-arrangement and scalability of rules, and improves richness of the micro service arrangement architecture; and open access capability of a scheduling algorithm service, which can randomly access diversified scheduling services online, forms a dynamically scalable online algorithm library, provides flexible, balanced and optimized deployment for measurement and control application arrangement, and enhances scheduling capability of the micro service arrangement architecture. The application can comprehensively realize service, diversification and open arrangement of measurement and control resources.

The invention relates to the technical field of computer science, and discloses an efficient file storage system with a distributed architecture, which comprises the following modules: a distributed file storage module for segmenting file data and distributing the file data to a plurality of storage nodes by adopting a distributed storage technology to ensure high availability and expansibility of the data; the intelligent data management module is used for dynamically managing data loads among storage nodes based on a data distribution algorithm and supporting automatic expansion and optimization of storage resources; the high-speed file access module is used for ensuring that a user can efficiently perform file read-write operation through a distributed access mechanism and an optimized data transmission protocol; and the data redundancy and backup module is used for providing a flexible redundancy strategy and combining a replica redundancy technology and an erasure code technology. By optimizing the file storage technology, the storage efficiency can be improved, the storage space can be reasonably utilized, dynamic expansion of the system is supported, and the problems that an existing system is slow in response and poor in expansibility when coping with large-scale data are solved.

The application discloses a Java-based distributed transaction management system and relates to the technical field of distributed systems. In view of the contradiction between transaction consistency and high concurrency and high availability in a distributed system, the scheme comprises the following: a transaction coordination module, which is used for constructing a cluster based on a Raft protocol to guarantee continuous availability of a service, realizing transaction full-life cycle management by relying on an extended state machine engine, and dynamically selecting an optimal communication path of a transaction according to scheduling decisions and a real-time network topology state; a local transaction management module, which is embedded in each microservice and is used for realizing local execution and state reporting of a transaction; a multi-level log module, which is used for realizing traceability of a transaction state and recovery of a fault through multi-level storage and event tracing; an intelligent scheduling module, which is used for realizing dynamic optimization of transaction processing based on an LSTM model and QoS indicators; and a monitoring and alarming module, which is used for collecting transaction full-link logs and performance indicators in real time and realizing full-link observability. The application is suitable for high-reliability and high-concurrency scenarios.

The application discloses a mirror backup method and device, electronic equipment and a computer readable storage medium. The method comprises the following steps: starting a mirror warehouse service, and constructing a node local warehouse; acquiring a node label, acquiring a node mirror corresponding to the node label from a complete mirror warehouse, and saving the node mirror to the node local warehouse; if it is detected that polling backup of a target mirror is required, acquiring the target mirror from the complete mirror warehouse, and saving the target mirror to the node local warehouse; the target mirror is a mirror which does not exist in the node local warehouse and the number of backup is less than two; the method adopts a non-consistent distributed backup mechanism to backup the mirror, all the mirrors have at least two backups in the cluster, when any node is abnormal, all the mirrors in the cluster can be guaranteed, the high availability of the cluster is guaranteed, and the bandwidth and disk space occupied by mirror transmission and storage can be reduced.

The application discloses a kind of Python model distributed online deployment method and system, data processing and feature engineering code converter designed by the application convert the logic of offline data processing and feature engineering of Python model training front-end into online Python code;Model engine designed by the application can quickly load various different kinds of Python models such as machine learning, deep learning, natural language processing etc.Through the Python model distributed deployment method and system provided by the application, Python model can be quickly deployed online, and can easily meet the requirements of high concurrency, high availability and fault tolerance etc.Algorithm engineers only need to spend time and effort on modeling, thereby improving the model development efficiency and shortening the model iteration cycle.

The invention discloses a method for explaining an error alarm. The method comprises the following steps of: presenting description information of a plurality of alarm records output by analyzing a code file of a detected item to a user; according to the description information of the multiple alarm records, extracting target code snippets associated with the multiple alarm records and rule description of a target rule; retrieving at least one of a description text of a defect code, a description text of a misinformation scene or an example code snippet identified by the target rule from a knowledge base according to the rule description; according to the description text of the defect code, the description text of the false alarm scene or the example code snippet and the rule description and the target code snippet of the target rule, generating a false alarm conclusion and reason explanation of the multiple alarm records through a language model; and presenting a false alarm conclusion and reason explanation to the user. According to the method, the rule check principle is interpreted through the language model, the program execution process is analyzed and deduced, the reason explanation for generating the misinformation is generated, evidence is provided for the misinformation conclusion, and high availability and reference are achieved.

The embodiment of the present specification provides a task processing method and a distributed storage system, wherein the task processing method comprises: obtaining a service request for a first logical unit, wherein the first logical unit is stored in a first service node; sending the service request to the first service node to obtain a first request result; in the case that the first request result indicates that the first service node is faulty, sending the service request to a candidate service node of the first logical unit to obtain a target request result fed back by a target service node, wherein the target service node is a candidate service node storing the first logical unit after the first service node is faulty. When the first service node is faulty, the client does not need to inquire the control node about the service node where the first logical unit is currently located, and can directly initiate a service request to the known candidate service node, so that the service request of the client is restored to no longer depend on the control node, and the fault tolerance and high availability of task processing are improved.

A service monitoring method comprises: obtaining node information of a plurality of nodes to be monitored, and obtaining at least one node information set based on the node information of the plurality of nodes to be monitored, wherein the node information set comprises node information of at least one node to be monitored; starting at least one service instance based on the at least one node information set, the service instance corresponding to the node information set, the service instance being used for monitoring each node to be monitored in the corresponding node information set; creating at least one instance monitoring node, the instance monitoring node corresponding to the service instance, the instance monitoring node being used for monitoring a state of the corresponding service instance; and monitoring the at least one service instance based on the at least one node information set and the at least one instance monitoring node. In this way, each node to be monitored is intelligently monitored by one instance monitoring, each instance monitoring different nodes to be monitored, which can reduce the problem of data consistency and the problem of double data storage, and can realize high availability of the service.

The disclosure provides a database consistency verification method and device, electronic equipment and computer readable storage medium, and relates to the field of databases. The database consistency verification method comprises: in response to a verification instruction, performing a verification operation on a first backup library and a second backup library based on a checksum algorithm, wherein a reference code is generated based on the verification operation for the first backup library, and a verification code is generated based on the verification operation for the second backup library; determining the consistency between the first backup library and the second backup library based on the comparison result of the reference code and the verification code; and determining the consistency between the master library and the backup library based on the consistency between the first backup library and the second backup library. Through the technical scheme of the disclosure, the consistency verification can be performed while ensuring the normal operation of the master library, which is conducive to reducing the probability of intrusion into the database, thereby ensuring the high availability and strong consistency of the database.