42results about How to "Realize elastic scaling" patented technology

The invention provides a service-uninterrupted load balancing method and system, and the method comprises the steps: S1, enabling a load balancing device to judge whether the service of a rear-end instance is available or not in real time, and updating the service state of the rear-end instance to a service availability list stored in a shared memory; S2, the shared memory writes the updated service availability list into a configuration file of each load balancing device in real time, and persistently stores the configuration file; And S3, when the load balancing device receives the user request, selecting an available back-end instance to process the user request according to the service availability list. Updating the service state of the rear-end instance to a service availability liststored in a shared memory in real time; The shared memory writes the service availability list change information into a configuration file in an asynchronous manner, and notifies other load balancing devices to update related configuration files; The load may be dynamically requested to a backend instance absent in the configuration file without restarting the load balancing device.

The invention discloses a configuration method for executing a timed task under a distributed system. A server side is of a distributed architecture, view display is achieved at the front end of the server side by means of react, a rest data interface is provided for the front end by the rear end of the server side by means of spring mvc, data operation authorization is guaranteed by means of spring security, access to data and modification of data by unauthorized users are avoided, configured tasks are triggered by means of quartz, a service discovery tool is used for dynamically finding and coordinating different machines to work, and redis is used as arbitration of resource competition; a client side registers a node as a task node and processes task logic. The invention further provides a configuration system for executing a timed task under a distributed system.

The invention provides an account book database component, an operation method and a storage medium. The account book database component comprises an account book data protocol component, which is used for deconstructing an account book of a block chain network from a plurality of dimensions to form a data set in the form of a key-value pair; and an account book storage component for storing the formed data set in the form of the key-value pair.

The invention provides a distributed file system. The distributed file system comprises a client, a metadata node, a data node and a volume management node, wherein the client corresponds to one or more containers. The metadata node is used for storing a first corresponding relationship, the first corresponding relationship is a corresponding relationship between file system attributes and a storage position of data, and the data is actual data in a file. The data node is used for storing data. The volume management node is used for responding to a received volume creation request of the client, and creating one or more volumes, wherein each volume is an instance of a file system which can be mounted by at least one container, each file system attribute comprises an index node and corresponding index node identification information, and the index node identification information comprises a file name and any one or more of the following information: a file size, creation time, modification time, a link number, a user, a user group and a file permission. The invention further provides a computer system and a computer readable storage medium.

The invention relates to a firewall policy query method and system, an elastic scaling method and system, equipment, a storage medium. The firewall policy query method comprises the steps: S1, obtaining firewall policy configuration information, analyzing the firewall policy configuration information into standardized format data, and constructing a firewall policy information base; S2, automatically judging a safe area to which a source IP address and a destination IP address in the firewall configuration information belong according to the query information, and automatically judging that the source IP address and the destination IP address flow pass through firewall equipment; S3, automatically calculating strategy correlation between the query information and a firewall strategy; and feeding back a query result according to the strategy correlation.

Embodiments of the invention provide a fund investment supervision index obtaining method and device. The method comprises the steps of obtaining a corresponding index generation task based on a received index data processing instruction; splitting the index generation task into a plurality of sub-tasks by applying a preset dimension; according to the fund single-day data corresponding to each sub-task and pre-stored self-defined index configuration information, concurrently executing each sub-task to obtain an index calculation result corresponding to each sub-task; aggregating the calculation results corresponding to the sub-tasks to obtain an index calculation result corresponding to the index generation task, and taking the index calculation result as a fund investment supervision index corresponding to the index data processing instruction and used for fund investment supervision. The method can effectively improve the obtaining accuracy, flexibility and efficiency of the fund investment supervision index, can effectively reduce the development period of the fund investment supervision index, and can effectively improve the reliability and accuracy of fund investment supervision.

The invention discloses a cloud service system. Service orchestration of the cloud service system comprises the following steps: creating a service orchestration product, and performing service orchestration application deployment, wherein the creation process of the service orchestration product comprises the following steps: A1, creating an application group in the cloud platform; A2, verifyingthe availability of the created application group, and if the verification result is unavailable, returning to the step A1 for reconfiguration; A3, if the verification result is that the service orchestration product is available, publishing the service orchestration product to a service orchestration product library. The process of service orchestration application deployment comprises the following steps: B1, initiating a deployment order application in a cloud platform; B2, after the order application is passed, enabling the cloud platform to create a cloud host according to the cloud hostcreation sequence of the service orchestration; B3, after the cloud hosts are created, reading the information of the cloud hosts and the mapping relationship of the IPs among the cloud hosts; B4, according to the read information of the cloud hosts and the mapping relationship of the IPs among the cloud hosts, establishing the relationship among the cloud hosts and VIP setting.

The invention discloses an anti-wear adjustable clamping platform for forceps processing and relates to the technical field of forceps processing. The anti-wear adjustable clamping platform for forceps processing specifically comprises a horizontal table, a locking pipe and a binding clip. An outer ring chute and an inner ring chute are concentrically formed in the upper surface of the horizontaltable, a swing air cylinder is also fixed to the upper surface of the horizontal table, the moving end of the end part of the swing air cylinder is connected to a swing connecting rod, the locking pipe is fixed to the outer wall of a moving plate core, and the binding clip is clamped to the outer port of the locking pipe. According to the anti-wear adjustable clamping platform for forceps processing, a tray is connected to the moving plate core through the connecting rod, the moving plate core swings back and forth along with the swing air cylinder through the swing connecting rod, a forceps jaw and the tray are bonded and fixed, so that after the swing connecting rod swings, the binding clip swings back and forth therealong under the action of the connecting rod and the tray, and therefore, the multi-angle and multi-position processing demands of auxiliary processing equipment on binding clip are met, and the moving pressure of the auxiliary processing equipment is alleviated.

The embodiment of the invention discloses a distributed task processing method, device and equipment, a storage medium and a system. The method comprises: according to the node role of a local node ina target node set, obtaining matched sub-tasks from a target task to be processed, and jointly processing all the sub-tasks in the target task by all nodes in the target node set; when it is detectedthat the target node set is changed, suspending the current processing process; and re-determining a new node role of the local node in the changed target node set, and according to the new node role, obtaining a matched sub-task from the target task to continue processing. By using the technical scheme of the invention, the elastic expansion and contraction of the nodes during task processing can be realized, and the task processing efficiency is improved.

A data security assurance method in a hybrid cloud environment based on a service grid relates to the technical field of computers, and comprises the following steps: an administrator configures access security between services, defines security policies between services A, B and C and storage services, determines encrypted communication and non-encrypted communication, and issues the informationto the intelligent agent side by the control plane in a unified manner; after an external entry request arrives at the service A, the service A analyzes the address of the service B through the DNS and initiates calling; the request of the service A for calling the service B is intercepted by the sidecar, and traffic transparent transmission is performed; and the service B calls the service C, andthe DNS analyzes the address of the service C as a public cloud address to configure a security policy. According to the method, the limitation of public cloud manufacturers can be removed, and the network transmission layer security among multiple clouds, the application communication security in the public cloud and the data storage security can be ensured; secure transmission can be flexibly customized, and cross-cloud services are defined to enable secure access.

Provided is a filter tuning system, and relates to the technical field of filter tuning; the system comprises a transfer robot and a tuning head, the transfer robot comprises an X conveying shaft, a Yconveying shaft and a Z conveying shaft, and the tuning head comprises a fixed disc, a mounting disc, a servo motor, a first gear, a rotating shaft, a limiting disc, a mounting hole, a second gear, afastener, a clamper, an extrusion tool, an extrusion head, a fastening head, a clamping head, a connecting rod, a connecting sleeve and a spring. According to the invention, the measuring equipment can measure electrical data of the filter, the depth needing to be extruded can be calculated, and movement of the extrusion tool in the X, Y and Z directions can be realized; the filter can be automatically and accurately extruded and tuned, the three parts are driven to move through one moving part, power equipment of the device can be reduced, and the size of the device can be reduced; elastic stretching and retracting of the fastener, the clamper and the extrusion tool can be achieved, and adverse effects caused by simultaneous lifting of the three parts can be avoided.

The invention discloses a scheduling model construction method, a scheduling model, a scheduling method and a scheduling system of a cluster, belongs to the technical field of big data processing, and aims to solve the technical problems that the cluster lacks scheduling decisions and the scheduling basis is single. Comprising the following steps: collecting sample data of an optimal adjustment point number through actual set resource scheduling; performing normalization processing on the sample data to obtain preprocessed sample data; a prediction model is constructed based on the deep neural network of back propagation, and the prediction model takes the big data cluster specification, the cluster load and the expected cluster adjustment load input, and takes the optimal adjustment node number as the output; and training a prediction model based on the preprocessed sample data, and adjusting the weight of each layer of neurons of the prediction model based on a back propagation method according to an error between a predicted value output by the prediction model and an actual value of the sample data to obtain a trained prediction model.