1477 results about "Multitenancy" patented technology

The invention discloses a distributed multi-tenant data security isolation system and method, and relates to the technical field of data isolation, and the system comprises a data isolation module which is responsible for distributing independent container instances and hardware resources for each tenant, and adjusting the data access authority according to an access control strategy; the dynamic access control module is responsible for generating an access control strategy according to the user identity, the authority, the tenant strategy and the access behavior; the distributed data management module is responsible for storing data fragments on different storage nodes; the resource scheduling and optimizing module is responsible for collecting resource demand data of each tenant, calling an intelligent scheduling algorithm, performing dynamic prediction and analysis on resource demands, and then automatically adjusting a resource allocation strategy according to a prediction result; and the security auditing and monitoring module is responsible for collecting operation logs and event records of each module and carrying out comprehensive analysis. The invention aims to solve the problems of data security and resource management in a multi-tenant environment.

Various aspects of methods, systems, and use cases for multi-entity (e.g., multi-tenant) edge computing deployments are disclosed. Among other examples, various configurations and features enable the management of resources (e.g., controlling and orchestrating hardware, acceleration, network, processing resource usage), security (e.g., secure execution and communication, isolation, conflicts), and service management (e.g., orchestration, connectivity, workload coordination), in edge computing deployments, such as by a plurality of edge nodes of an edge computing environment configured for executing workloads from among multiple tenants.

The invention relates to the technical field of communication, in particular to a micro-segmentation-based multi-tenant zero-trust security system, which comprises a tenant network topology sensing module for acquiring network structures and service dependencies of tenants and generating a tenant-level network topology graph and a communication graph; a strategy rule automatic generation module generates a micro-segment access control strategy; the context-aware risk assessment module collects a user identity, an equipment state and a behavior track, and generates an access risk score; the strategy dynamic adjustment and application module updates the access control strategy; and the tenant isolation and zero-trust interaction module deploys a security sandbox to complete trust verification and isolation protection of cross-tenant requests. According to the method, the micro-segmentation strategy is generated by automatically identifying the service dependency boundary, the access control rule is dynamically adjusted based on the context, and refined isolation and risk-driven defense in a multi-tenant environment are realized in combination with the security sandbox and the zero-trust mechanism, so that the security and controllability of the system are remarkably improved.

Techniques for leveraging a large language model (LLM) in software development are described. A description of an error message associated with a software system hosted by the multi-tenant provider network is received. An LLM is prompted with an analysis prompt to generate an analysis of the error message, the analysis prompt including the description of the error message, and the analysis of the error message is received from the LLM. The LLM is prompted with a suggested resolution prompt to generate a suggested resolution to a cause of the error message, the suggested resolution prompt including the description of the error message and the analysis of the error message, and the suggested resolution is received from the LLM. A change to resolve the cause of the error message is sent to an originator of the received description, the change based at least in part on the suggested resolution.

The invention relates to the technical field of cloud computing, and discloses a distributed management system and method for a cloud container cluster, and the system comprises a data collection module which is used for collecting the resource remaining amount of each node in the cloud container cluster and the resource demand of a tenant, and providing real-time data updating support; the state modeling module is used for establishing a state variable model for describing the dynamic change of tenant resources based on the resource data acquired by the data acquisition module, and state variables comprise the resource occupation amount, the resource application amount and the resource release rate of the tenants; the scheduling optimization module is used for generating a resource allocation strategy based on the tenant resource dynamic change characteristics and the multi-tenant competition relationship; according to the invention, through system architectures of data acquisition, state modeling, scheduling optimization and the like which are modularly designed, dynamic acquisition frequency and resource dynamic change modeling are introduced, the data acquisition real-time performance and the resource allocation accuracy are improved, and the problems of low resource utilization rate and slow scheduling response in the prior art are solved.

The invention discloses a data space multi-tenant isolation method and system based on a zero-trust architecture, particularly relates to the technical field of multi-tenant authority control, and is used for solving the problems of cross-tenant authority conflict and insufficient resource isolation caused by frequent strategy adjustment in the prior art. The method comprises the following steps: constructing a strategy dependence topological structure by acquiring a dynamic access strategy change request in real time so as to model a dependency relationship among a tenant permission node, a resource access path node and a time sequence connection edge; dynamically marking a resource sensitivity weight based on a historical access behavior, and analyzing and screening high-sensitivity conflict nodes in combination with a logic coupling degree; separating an independent resource access chain which directly depends on through reverse backtracking, and generating a hierarchical permission correction rule; finally, rules are injected, and blocking conditions are triggered to execute hierarchical verification and risk marking on the cross-tenant operation requests; the influence of strategy execution on a global system is reduced, and the permission boundary clearness and resource security of a multi-tenant data space are ensured.

The invention relates to the technical field of distributed computing and cloud computing, in particular to a multi-service and multi-tenant-oriented micro-service method and system, and the method comprises the steps: constructing a dynamic modular service framework based on a pluggable service component, a cross-tenant service module based on resource sharing, and a multi-service and multi-tenant service module based on resource sharing; modeling the calling relationship between the micro-services and calculating each resource demand weight coefficient of the micro-services; and scheduling the resource-shared cross-tenant service module by using the dynamic resource allocator. According to the method, the dynamic modular service framework based on the pluggable service component is constructed, so that accurate loading and unloading of each service module of the micro-service can be completed within hundreds of milliseconds, and the agility of the system is remarkably improved. According to the method, calling relation modeling is carried out on the cross-tenant service module, the resource demand weight coefficient is calculated, basic data is provided for resource scheduling, load changes are considered, optimal configuration of resources is achieved, and the overall performance and the response speed of the system are improved.

The invention relates to a Kubernetes cluster automatic deployment system based on modularization, and the system comprises a modularized cluster mirror image system which is used for providing a mirror image containing all assemblies of cluster operation and the optimal practice configuration of each assembly, and is used for flexibly customizing the assembly combination of a cluster according to different demands, and rapidly generating a customized cluster mirror image, the standardization of the delivery of the Kubernetes cluster is realized; the automatic deployment engine is used for defining a topological structure and configuration parameters of the cluster by adopting a declarative API (Application Program Interface), completing full-life-cycle automatic management through an architecture mode of a controller, and providing a monitoring alarm function which is ready to use after box opening; the application management system is used for providing application store based on Web, templated application configuration management and application real-time monitoring management; and the multi-tenant management system is used for providing resource isolation management, tenant authority management and security isolation management. According to the invention, the complexity of cluster deployment and management is greatly reduced, and the application efficiency and reliability of the cloud native technology are improved.

Methods and apparatus for application aware memory patrol scrubbing techniques. The method may be performed on a computing system including one or more memory devices and running multiple applications with associated processes. The computer system may be implemented in a multi-tenant environment, where virtual instances of physical resources provided by the system are allocated to separate tenants, such as through virtualization schemes employing virtual machines or containers. Quality of Service (QoS) scrubbing logic and novel interfaces are provided to enable memory scrubbing QoS policies to be applied at the tenant, application, and / or process level. This QoS policies may include memory ranges for which specific policies are applied, as well as bandwidth allocations for performing scrubbing operations. A pattern generator is also provided for generating scrubbing patterns based on observed or predicted memory access patterns and / or predefined patterns.

The invention discloses a computing power analysis method used in a cloud computing environment, a matching method and a computer device. The computing power analysis method used in the cloud computing environment comprises the steps that historical task operation data of different types of computing power nodes in a cloud computing platform are acquired, associated computing power portraits corresponding to the computing power nodes are generated through preprocessing, and then a target model is trained in combination with the historical task operation data to obtain a task-computing power mapping model; performing multi-dimensional dynamic and static analysis on a to-be-executed user calculation task to obtain task feature information; and analyzing the task feature information based on the task-computing power mapping model to obtain analysis information of each type of computing power nodes. According to the method, the required computing power resources and the analysis information of each type of computing power nodes can be accurately predicted according to the dynamic and static analysis feature information of the task before the task is executed, so that accurate computing power identification and intelligent matching are realized, the reasonability and efficiency of task allocation are improved, the resource waste rate is effectively reduced, and the adaptation accuracy in a multi-tenant environment is improved.

Methods, systems, and devices for data processing are described. A server host may receive a login request that includes a clear text password for an account associated with a tenant of a multi-tenant cloud platform. The server host may retrieve an encrypted payload associated with the account. The encrypted payload may include a hash value of a user-configured password for the account and an indication of a hashing algorithm used to transform the user-configured password into the hash value. The server host may obtain a wrapped symmetric key provisioned by a symmetric key distribution service. The server host may transmit a request that includes the encrypted payload, the clear text password, and the wrapped symmetric key. The server host may receive a response that indicates whether a hash value of the clear text password from the login request corresponds to the hash value of the user-configured password.

Techniques for managing cloud computing resources hosting burstable performance instances are described. A host computer system of a provider network executes burstable performance compute instances. Compute capacity usage data is obtained from the host computer system, the compute capacity usage data including a first indication of a first compute capacity used by a first burstable performance compute instance. A first weight for the first burstable performance compute instance is calculated, the first weight being inversely related to the first compute capacity. A scheduler of the host computer system is updated with process prioritization weights, the process prioritization weights including a first process prioritization weight that is based at least in part on the first weight. The scheduler allocates compute capacity based on the process prioritization weights.

The invention discloses an operation and maintenance knowledge intelligent question and answer interaction method, device and equipment based on an LLM large model. According to the method, questions of operation and maintenance personnel are received through a natural language interaction interface, semantics are analyzed through a pre-trained LLM, candidate answers are generated, the accuracy of the answers is verified in combination with a dynamic operation and maintenance knowledge graph (including equipment model and fault code mapping, a historical case library and a real-time updating knowledge base), and finally a verification result is returned. The device comprises an input module, a processing module, a verification module and an output module, the processing module integrates domain knowledge fine tuning and real-time data integration functions, and the verification module supports multi-source data fusion and confidence evaluation. The platform adopts a multi-tenant architecture, supports visual diagnosis, automatic equipment operation and knowledge use report generation, and ensures that data cannot be tampered through a block chain technology.

The invention provides a distributed computing platform which is oriented to a big data scene and is based on a Serverless framework. The platform comprises an elastic computing resource pool composed of multiple nodes, and computing power resources can be supplied as required by combining a dual capacity expansion and contraction mechanism and intelligent resource analysis scheduling. The platform adopts a Serverless task operation model, simplifies big data application deployment, and realizes performance isolation in a multi-tenant scene through uniform resource management. In addition, the visual monitoring platform is assisted by intelligent analysis, and decision support is provided for operation and maintenance management. Compared with traditional static resource scheduling, the method has the advantages that the resource utilization rate can be remarkably increased, the operation and maintenance complexity is reduced, powerful resource isolation and fairness guarantee are provided in a multi-tenant environment, and technical innovation and application expansion of distributed computing in the big data era are effectively supported.

Methods, systems and apparatuses for sharing video data across tenants of a multi-tenant security system. The methods may include maintaining a first tenant account of a security server and a second tenant account of the security server. The first tenant account is unrelated to the second tenant account. The second tenant account is configured to include partner account privileges for the first tenant account. A request from the second tenant account to access a resource associated with video data included in a resource registry of the first tenant account is accessed. The resource registry is made accessible to the second tenant account based on the partner account privileges. The request may be approved or denied. The video data is stored in a tenant database in association with the second tenant account based on the request being approved. The request may be processed by an image processing device.

The invention provides a multi-tenant large model reasoning service architecture and an operation method thereof, and the architecture comprises a multi-level cache module which is used for managing the storage of a LoRA model in a video memory, an internal memory, a disk and a remote memory according to the priority; the route registration module is used for recording the model cache position and the load state of each server; the dynamic routing module is used for allocating requests according to the tenant identifiers and the server states; and the parameter fusion module is used for superposing the LoRA model and the basic model to generate a personalized inference model. According to the method, efficient resource utilization and low-delay service are realized through multi-stage cache management, a dynamic routing strategy and a load balancing mechanism. The framework supports on-demand loading and parameter fusion of the tenant personalized LoRA model, and the reasoning service efficiency in a multi-tenant scene is remarkably improved.

Systems and methods are described for providing multitenancy in an artificial intelligence (AI) platform. The platform can provide a user interface (UI) that allows for creation of an organization, tenants within that organization, and groups within tenants. This hierarchy can dictate resource permissions that impact which AI pipelines and AI pipeline objects are available to a user. The different tenants can have segregated data and utilize different pipeline objects, such as different prompts, datasets, or models. A marketplace UI can prioritize additional marketplace pipelines for approval and inclusion with the tenant.

In one embodiment, a method comprises accessing information associated with a user that is trying to login to an application, generating a first session identifier corresponding to the information, sending a first notification to an authentication client that the user is trying to login using an authentication service, receiving a first request from an authentication provider for authenticating a second session identifier, determining that the second session identifier is identical to the first session identifier by comparing the second session identifier with stored first session identifier, and causing the authentication provider to patch one or more authentication tokens with the information regarding the tenant, where the one or more authentication tokens are used for accessing the application.

The disclosure provides a method for assigning containerized workloads to isolated network constructs within a networking environment associated with a container-based cluster. The method generally includes receiving, at the container-based cluster, a subnet port custom resource specification to initiate creation of a subnet port object to assign a node to a subnet within the networking environment, wherein one or more containerized workloads are running on the node, in response to receiving the subnet port custom resource specification, creating the subnet port object, and modifying a state of the container-based cluster to match a first intended state of the container-based cluster at least specified in the subnet port object, wherein modifying the state comprises assigning the node to the subnet in the networking environment.

The invention relates to the field of data isolation, and provides a flying saucer shooting athlete training data isolation method based on a multi-tenant architecture. The method aims at solving the problem that a traditional data isolation technology effectively isolates tenant data in a multi-tenant environment. According to the main scheme, the method comprises the steps of designing a database architecture, determining a fragmentation key and designing a fragmentation strategy. The dependency of ShardingSphere is introduced, a data source is configured, and a fragmentation rule is configured according to a fragmentation strategy; the method comprises the following steps: initializing fragmentation databases and tables, creating a plurality of databases according to a fragmentation rule, creating the same table structure in each database, and creating a corresponding fragmentation table in each database according to the fragmentation rule; by monitoring data in a database table created after fragmentation, a dynamic fragmentation adjustment strategy is adopted to reduce the occurrence of a data skew condition, and a dynamic scaling strategy is adopted to adjust system resource distribution; according to the tenant ID, fragment key values are calculated, which database table the data is routed to is determined, access control is achieved, and only authorized tenants can access the data to which the tenants belong.

The invention relates to the technical field of data center high availability, in particular to a cross-data center fault isolation and switching method and system in a multi-tenant environment. The resource mapping table is constructed by taking the tenants as the minimum control units, the affected tenants are accurately identified, logic isolation is executed, the problem of waste of full-tenant service migration resources caused by node-level or cluster-level switching in the prior art is avoided, and the fault influence range is minimized. The optimal data center is dynamically selected by combining the multi-factor objective function with the tenant SLA level, the defects that an existing scheduling strategy is opaque and tenant priorities cannot be distinguished can be overcome, and it is ensured that key tenant services are preferentially recovered. And finally, through combination of a gray takeover mechanism and health feedback confirmation and multi-dimensional recovery verification after migration, the condition that an existing recovery mechanism is extensive can be changed, the fault processing precision and the resource scheduling efficiency of the data center in a multi-tenant environment are remarkably enhanced, and the service continuity is guaranteed.

The invention provides a multi-tenant data pushing method, and relates to the technical field of computer software and information, and the method comprises the steps: achieving unified identity authentication through single sign-on, and dynamically distributing a pushing authority based on an authority strategy; defining conversion rules and tasks by utilizing a visual interface of the low-code configuration center, and generating a standardized data packet; and centralized scheduling is carried out in a multi-tenant management and control center, and the stability of the system is guaranteed by combining a current limiting and dynamic retry mechanism. Source system data are collected in real time, and format conversion is completed through a rule engine after grammar, permission and event state verification. And pushing in an asynchronous mode, and recording full-link information including a tracking ID, a timestamp, a data fingerprint and a response state. And when pushing fails, a compensation mechanism is triggered, degradation or retry is carried out according to a preset rule, final consistency of data is ensured, and the reliability and maintainability of the system are improved.

Techniques are disclosed for usage-tracking of various information security (InfoSec) entities for tenants / organization onboarded on an instant multi-tenant security assurance platform. The InfoSec entities include policies, procedures, controls and evidence tasks. A policy or procedure is enforced by implementing one or more controls, and the collection of one or more evidence tasks proves / verifies the implementation of a control. The InfoSec entities are linked to each other across the platform and accrue a number of benefits for the tenants. These include automatically / continuously creating asset populations and drawing samples from the asset populations for auditing. The population samples may be generated by entering natural language queries in the platform. Asset data from the asset populations is used to feed / populate various other modules and systems used by the tenant of the platform.

Techniques are disclosed herein for onboarding users from a single tenant cloud environment to a multi-tenant cloud environment. In one aspect, a method is provided that includes in response to an eligibility status check indicating that a first cloud service instance running a first version of a cloud service in a first cloud environment is eligible for the upgrade, exporting a copy of data from the first cloud service instance to a common storage device, provisioning a second cloud service instance running on the second version of the cloud service in a second cloud environment, importing the first copy of the data from the common storage device to the second cloud service instance, and activating the second cloud service instance to run the second version of the cloud service. During the exporting, provisioning, and importing the first cloud service instance continues to run the first version of the cloud service.

The invention relates to the technical field of power dispatching control, in particular to a V2G-based multi-tenant virtual power plant dispatching method and a server, and the method comprises the steps: obtaining the information of all target vehicles connected to a power grid within a preset duration, taking a target vehicle cluster as a virtual power plant, and enabling each virtual power plant to form a micro-grid; acquiring target information including off-grid time, target electric quantity and initial electric quantity uploaded by each target vehicle, and performing charging and discharging scheduling control on the target vehicle through a model prediction control algorithm based on the target information; aiming at the output power of the target vehicle in the micro-grid, preferentially meeting the target vehicle with the power requirement under the same micro-grid; new energy vehicles in a certain area are gathered together to form a virtual power plant, each virtual power plant forms a micro-grid, and the established power grid transmission and feed of the vehicles in the area are uniformly allocated according to the requirements of the power grid through a model prediction control algorithm, so that ordered charging and discharging are realized.

Techniques are disclosed for usage-tracking of various information security (InfoSec) entities for tenants / organization onboarded on an instant multi-tenant security assurance platform. The InfoSec entities include policies, procedures, controls and evidence tasks. A policy or procedure is enforced by implementing one or more controls, and the collection of one or more evidence tasks proves / verifies the implementation of a control. The InfoSec entities are linked to each other across the platform and accrue a number of benefits for the tenants. These include generating a security questionnaire response (SQR), defining a readiness project and an audit project, sharing InfoSec entities encompassing the various products of a tenant, automating risk assessment, automatic collection of evidence tasks for verifying the implementation and / or operational state / status of various mitigating controls, etc.

Some embodiments provide a method for monitoring a multi-tenant network management system deployed in a public cloud to manage groups of datacenters. Each respective datacenter group includes one or more datacenters of a respective tenant that defines the datacenter group. For each datacenter group of a set of datacenter groups managed by the multi-network management system, the method deploys a set of network management service instances in the cloud specified by the tenant for the datacenter group. Each of the network management service instances provides a specified service to the datacenters of the datacenter group. For each datacenter group, the method deploys a metric monitoring service instance in the cloud for the datacenter group. The metric monitoring service instance is for collecting and analyzing metrics from services belonging to each of the network management service instances deployed for the datacenter group.

The invention provides a multi-tenant-based centralized authentication and authorization method, system, device and medium, and belongs to the technical field of security and identity management, and the system comprises a unified portal layer, an authentication layer, an authorization layer, a strategy center and an audit monitoring layer. The unified portal layer receives a user request, identifies and injects a tenant identifier, and executes WAF rule verification, JWT signature verification and Token blacklist check; the authentication layer performs user or client credential verification on different accessed identity sources, generates and issues a JWT, and monitors the life cycle of a token; the authorization layer extracts an authority statement in the JWT and a locally cached strategy snapshot; the strategy center provides centralized storage, version management and visual editing of multi-tenant strategies; through cooperative work of each layer, accurate identification, unified authentication, centralized strategy management and comprehensive audit monitoring of tenants are realized. And the security, the expandability and the management efficiency of the system are effectively improved.

The invention relates to the field of front-end technology, can be applied to the field of digital medical / financial science and technology, and discloses a front-end multi-tenant management method and device, electronic equipment and a storage medium. The method comprises the following steps: returning a security access token corresponding to a target tenant by using an authentication mechanism based on a token or third-party authorization according to a tenant registration request; when registration succeeds, role configuration data and permission configuration data of the target tenant are generated; when it is monitored that login is successful by using the security access token, creating a micro-front-end application and different micro-front-end modules of the target tenant according to the role configuration data and the authority configuration data; starting a micro-front-end application, and dynamically loading a micro-front-end module according to the role configuration data and the authority configuration data; and executing mixed mode rendering on the front-end module at the server side and the tenant side through the integrated front-end framework to obtain a front-end rendering page of the target tenant. According to the method, multi-tenant security isolation is realized, resources are loaded as required, and system performance and expansibility are guaranteed.

The invention relates to an intelligent IT asset management system, and the system comprises a configuration asset management module which is used for automatically collecting IT asset information in a network, building a complete configuration item relation model, and supporting the dependency relation mapping and impact analysis between configuration items; the service desk management module is used for establishing a service catalog, defining a processing flow, response time and a service level protocol, automatically carrying out classification and priority evaluation on the received service requests through an intelligent classification engine, and distributing the service requests to proper processing personnel according to a preset rule; the contract supplier management module is used for full-life-cycle management of suppliers and contracts; the IT service financial module is used for multi-dimensional budget management and fine management of IT cost; and the multi-tenant management module is used for realizing entity separation and authority control. The problems of a traditional IT asset management system in the aspects of asset tracking, service management, cost control and the like are solved, and a set of complete IT service management solution is provided for enterprises.