Method and device for cloud management platform to apply for Microsoft Hyper-V virtual machine service

Abstract

The invention relates to the technical field of cloud computing and virtualization management, and particularly provides a method and device for applying for Microsoft Hyper-V virtual machine service by a cloud management platform, and the device comprises a user layer, a cloud management layer, a virtualization management layer, a Hyper-V computing resource layer and a storage and network layer. The user layer is used for providing a virtual machine application and management entrance and allowing a user to apply for a virtual machine according to service requirements and perform related configuration; the cloud management layer is used for uniformly managing and arranging Hyper-V resources and providing automatic deployment, resource monitoring and fault recovery; the virtualization management layer is used for managing and optimizing Hyper-V computing resources; the Hyper-V computing resource layer is used for providing computing cluster management and realizing high availability, load balancing and thermal migration of a VM (virtual machine); and the storage and network layer is used for providing storage and network management. Compared with the prior art, self-service application, automatic examination and approval, intelligent scheduling and dynamic capacity expansion and contraction of the Hyper-V virtual machine by a user can be realized, the utilization rate of virtualized resources is improved, and the manual operation and maintenance cost is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of cloud computing and virtualization management, and specifically provides a method and device for a cloud management platform to apply for Microsoft Hyper-V virtual machine services. Background Art

[0002] As enterprises deepen their digital transformation, more and more IT infrastructure is migrating to the cloud, and virtualization technology has become a crucial tool for resource management. Microsoft Hyper-V, as one of the mainstream virtualization platforms, is widely used in enterprise private clouds and data centers. Traditional Hyper-V virtual machine creation and management relies on manual operations, including resource allocation, network configuration, and storage management. This is inefficient and prone to errors. Furthermore, native Hyper-V management tools (such as Hyper-V Manager and SCVMM) lack self-service application and approval mechanisms, hindering the unified scheduling and automated management of enterprise IT resources.

[0003] Therefore, how to solve the problems of complex application, delayed approval, inflexible resource scheduling, etc. in the existing Hyper-V management is an urgent problem to be solved by those skilled in the art. Summary of the Invention

[0004] The present invention aims to address the deficiencies of the above-mentioned prior art and provides a method for applying for Microsoft Hyper-V virtual machine services on a cloud management platform with strong practicality.

[0005] A further technical task of the present invention is to provide a device for applying for Microsoft Hyper-V virtual machine services on a cloud management platform with a reasonable design and safe applicability.

[0006] The technical solution adopted by the present invention to solve its technical problem is:

[0007] A method for applying for Microsoft Hyper-V virtual machine services on a cloud management platform, comprising a user layer, a cloud management layer, a virtualization management layer, a Hyper-V computing resource layer, and a storage and network layer;

[0008] The user layer is used to provide a virtual machine application and management portal, allowing users to apply for virtual machines and perform related configurations according to business needs;

[0009] The cloud management layer is used to uniformly manage and orchestrate Hyper-V resources, providing automated deployment, resource monitoring, and fault recovery.

[0010] The virtualization management layer is responsible for the management and optimization of Hyper-V computing resources;

[0011] The Hyper-V computing resource layer is used to provide computing cluster management and achieve high availability, load balancing and hot migration of VMs;

[0012] The storage and network layer is used to provide storage and network management.

[0013] Furthermore, at the user layer, OpenLdap is used for user identity management, Spring CloudGateway is used as the unified API entrance, and the AI training model is used to provide the best VM configuration recommendation and optimize resource allocation.

[0014] JSON Schema validation allows administrators to define dynamic form structures and implement automated approval strategies in combination with the approval process engine. ELK collects and analyzes user operation logs, providing detailed auditing and backtracking capabilities.

[0015] Furthermore, in the cloud management layer, Terraform and Ansible are used for resource orchestration, supporting unified management of Hyper-V. Activiti implements custom approval policies, adopts a combination of roles and attributes for fine-grained permission control, and combines AI prediction to optimize quota policies.

[0016] Automated task scheduling is achieved based on Kubernetes+Celery, supporting periodic tasks and event-triggered tasks.

[0017] Furthermore, in the virtualization management layer, remote PowerShell+WMI is used for VM resource management, computing tasks are optimized based on the NUMA architecture, NVIDIA GRID is integrated, PCI device passthrough is provided, Dynamic Memory technology is supported, and dynamic adjustments are made within the VM.

[0018] Furthermore, Windows Server cluster technology is used in the Hyper-V computing resource layer to implement computing pools, dynamically migrate VMs based on VM resource usage, balance computing loads, optimize CPU and memory utilization, support hot migration of VMs across hosts and storage, and automatically expand computing nodes through HPA to improve resource elasticity.

[0019] Furthermore, in the storage and network layers, SSDs and HDDs are combined to optimize storage performance and costs, and distributed storage is performed based on StorageSpaces Direct.

[0020] Furthermore, IOPS limits are set for virtual disks, VXLAN isolation is performed, and Hyper-V VirtualSwitch is used for VXLAN, OpenFlow, and VLAN management;

[0021] Integrates with Azure DDoS Protection to detect abnormal traffic in real time and automatically block attacks.

[0022] A device for applying for Microsoft Hyper-V virtual machine services on an operation and management platform, comprising: at least one memory and at least one processor;

[0023] The at least one memory is configured to store a machine-readable program;

[0024] The at least one processor is used to call the machine-readable program to execute a method for a cloud management platform to apply for Microsoft Hyper-V virtual machine services.

[0025] Compared with the prior art, the method and device for applying for Microsoft Hyper-V virtual machine services on a cloud management platform of the present invention have the following outstanding beneficial effects:

[0026] (1) Automatically adjust computing resources through intelligent scheduling algorithms, improve CPU and memory utilization, and avoid resource waste. Support dynamic expansion and contraction, adjust VM specifications according to business needs, reduce idle resource costs, and improve overall computing efficiency.

[0027] (2) Automated configuration and deployment, supporting operating system pre-configuration and automatic software installation, reducing IT maintenance costs, intelligent fault detection and self-healing, reducing manual troubleshooting work, and improving business continuity.

[0028] (3) RBAC (Role-based Access Control) and MFA (Multi-factor Authentication) enhance system security and prevent unauthorized access. Comprehensive data encryption (disk encryption, network transmission encryption) effectively prevents data leakage and complies with regulations such as Information Security Protection 2.0 and GDPR. Log auditing and anomaly detection utilize AI log analysis technology to detect and prevent potential security risks in real time.

[0029] (4) Hyper-V Failover Cluster automatically migrates virtual machines in the event of a server failure, ensuring uninterrupted business operations. Hyper-V Replica enables cross-data center disaster recovery, switching to the backup site in seconds when the primary site fails, improving business reliability. Incremental backup and snapshot recovery, combined with AI-based prediction of failure risks, backs up data in advance and reduces the risk of data loss.

[0030] (5) Combined with AI intelligent load prediction, it optimizes resource scheduling and improves VM operating efficiency. In the future, it can be expanded to Windows containers, Kubernetes (K8s), and Azure Stack HCI, supporting hybrid cloud and edge computing scenarios and improving system flexibility.

[0031] (6) Reduce TCO (total cost of ownership) and improve ROI (return on investment). Through multi-tenant management, resource reuse is increased and duplicate investment is reduced. Storage optimization (tiered storage, data compression) reduces storage usage and hardware costs. Automated operations and maintenance reduce IT operations and maintenance costs, optimize human resource allocation, and improve operational efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0033] Attachment Figure 1 This is an architectural diagram of a method for a cloud management platform to apply for Microsoft Hyper-V virtual machine services;

[0034] Attachment Figure 2 The present invention is a flowchart of a method for applying for Microsoft Hyper-V virtual machine services on a cloud management platform. DETAILED DESCRIPTION

[0035] In order to enable those skilled in the art to better understand the solutions of the present invention, the present invention will be further described in detail below in conjunction with specific embodiments. Obviously, the embodiments described are only some embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0036] A best embodiment is given below:

[0037] like Figure 1 、 2 As shown, a method for a cloud management platform to apply for Microsoft Hyper-V virtual machine services in this embodiment includes a user layer, a cloud management layer, a virtualization management layer, a Hyper-V computing resource layer, and a storage and network layer;

[0038] The user layer provides a portal for virtual machine application and management, allowing users to apply for virtual machines and perform related configurations based on business needs.

[0039] OpenLdap is used for user identity management to ensure that different tenants can manage resources independently and support SSO (single sign-on).

[0040] Use Spring Cloud Gateway as the unified API entry point, supporting OAuth2.0 authentication, flow control, load balancing, and log tracking.

[0041] Through AI training models (based on user historical application data and business needs), we provide optimal VM configuration recommendations, optimize resource allocation, and improve resource utilization.

[0042] Supports JSON Schema validation, allowing administrators to define dynamic form structures and implement automated approval strategies in conjunction with the approval process engine.

[0043] ELK (Elasticsearch+Logstash+Kibana) is used to collect and analyze user operation logs, providing detailed auditing and backtracking functions.

[0044] The cloud management layer is used to uniformly manage and orchestrate Hyper-V resources, providing automated deployment, resource monitoring, and fault recovery.

[0045] Terraform+Ansible is used for resource orchestration, supporting unified management of Hyper-V.

[0046] Implement flexible custom approval strategies based on Activiti, such as single-level approval, multi-level approval, AI-based intelligent approval, etc.

[0047] A combination of roles (RBAC) and attributes (ABAC) is used to perform fine-grained permission control and ensure resource isolation between different tenants.

[0048] Supports tenant-level and project-level quota management to prevent over-application of resources, and combines AI prediction to optimize quota strategies.

[0049] Automated task scheduling is implemented based on Kubernetes+Celery, supporting periodic tasks, event-triggered tasks, etc., to optimize operation and maintenance efficiency.

[0050] The virtualization management layer is responsible for the management and optimization of Hyper-V computing resources;

[0051] Use remote PowerShell+WMI to manage VM resources, such as creation, modification, migration, and deletion.

[0052] Optimize high-performance computing tasks such as AI training and high-frequency trading based on the NUMA (Non-Uniform Memory Access) architecture.

[0053] Integrated with NVIDIA GRID, it supports high-load computing scenarios such as CAD, 3D rendering, and big data analysis.

[0054] Provides PCI device passthrough, such as FPGA, NVMe SSD, and network card passthrough, to improve I / O performance.

[0055] Supports Dynamic Memory technology to dynamically adjust VM memory and improve resource utilization.

[0056] The Hyper-V computing resource layer is used to provide computing cluster management and achieve high availability, load balancing, and hot migration of VMs;

[0057] Leveraging Windows Server clustering technology, we implement a high-availability computing pool, dynamically migrating VMs based on resource usage, balancing computing loads and optimizing CPU and memory utilization. We also support hot migration of VMs across hosts and storage to ensure uninterrupted business operations. We also automatically scale compute nodes based on the HPA (Horizontal Pod Autoscaler) to improve resource elasticity.

[0058] The storage and network layer is used to provide storage and network management to ensure the stability and security of VM operation.

[0059] Combining SSD+HDD, it optimizes storage performance and costs. Based on Storage Spaces Direct (S2D), it provides a high-performance distributed storage solution. It sets IOPS limits on virtual disks to prevent a single VM from excessively occupying storage resources. VXLAN isolation ensures network isolation between VMs of different tenants, improving security.

[0060] Uses Hyper-V Virtual Switch, supports VXLAN, OpenFlow, and VLAN management, and integrates Azure DDoS Protection to detect abnormal traffic in real time and automatically block attacks.

[0061] Provides a standardized virtual machine application process and supports automated approval, scheduling, and deployment.

[0062] User application: submit VM application through the web portal, supporting template deployment;

[0063] Resource audit: Audit based on strategies such as quota management, budget approval, and AI resource analysis.

[0064] Intelligent Scheduling: Combined with AI prediction models, it optimizes VM deployment and improves computing resource utilization.

[0065] Automatic deployment: Automated VM deployment, configuration, and initialization based on Ansible.

[0066] Provides real-time monitoring, intelligent alerts, and security compliance management to ensure stable operation of Hyper-V resources.

[0067] Monitor Hyper-V operating status, provide visual operation and maintenance data, implement centralized log collection, analysis, and alerting based on ELK, combine IAM+MFA for fine-grained access control, and implement VM disk encryption based on BitLocker to improve data security.

[0068] Provides VM high availability solutions to ensure uninterrupted business operations. Supports VM hot migration, Hyper-V Replica, cross-data center VM replication, and automated backup and recovery based on Veeam.

[0069] When managing Hyper-V virtual machines on a cloud management platform, resource optimization and intelligent scheduling are key to improving system performance and reducing costs. Through intelligent scheduling algorithms and AI-powered predictive analysis, dynamic optimization and rational allocation of computing, storage, and network resources are achieved.

[0070] 1. Computing resource optimization;

[0071] Dynamic CPU resource allocation: Based on Hyper-V's CPU resource scheduling policies (Weight, Reserve, Limit), it ensures that high-priority VMs have sufficient computing resources while avoiding resource competition that affects system stability.

[0072] NUMA (Non-Uniform Memory Access) optimization: Rationally allocate NUMA node resources on multi-CPU servers, reduce cross-NUMA access latency, and improve computing performance.

[0073] Train VM load models based on Prometheus+TensorFlow to predict future CPU / memory consumption and make resource adjustments in advance.

[0074] 2. Storage resource optimization;

[0075] High-frequency data is stored in SSDs, while low-frequency data is stored in HDDs, improving IOPS performance and reducing storage costs.

[0076] Based on the ReFS file system, data compression is automatically performed to improve storage utilization;

[0077] Regularly analyze unused VM disks and snapshots, and automatically clean them up to free up storage space.

[0078] 3. Network resource optimization;

[0079] Use SDN controllers to dynamically adjust VM network traffic paths, improve throughput, and reduce network bottlenecks.

[0080] Based on Hyper-V QoS policies, bandwidth is allocated to different VMs to ensure that business-critical VMs enjoy higher network priority.

[0081] Assign independent virtual networks to VMs of different tenants to enhance security and increase management flexibility.

[0082] The cloud management platform should have a complete high availability (HA) and disaster recovery (DR) mechanism to ensure business continuity and avoid single point failures affecting the production environment.

[0083] 1. Hyper-V Failover Cluster: Using Windows Server clustering, it supports automatic switching of VM resources to prevent business interruptions caused by physical server failures.

[0084] Automatic fault detection and recovery: SCOM monitors the operating status of Hyper-V. Once a VM downtime is detected, the system automatically migrates the VM to a healthy computing node.

[0085] Load balancing and scheduling: Based on Hyper-V Dynamic Optimization and AI prediction, it automatically balances computing loads, improves resource utilization, and reduces pressure on hotspot servers.

[0086] 2. Support cross-data center VM replication. In the event of a primary site failure, failover to the backup site occurs in seconds, ensuring uninterrupted business. Veeam performs regular incremental VM backups to ensure data integrity and enable rapid recovery. Combined with SD-WAN technology, data is replicated off-site to a disaster recovery center, improving data security and preventing single data center failures from impacting business.

[0087] Security protection and compliance management

[0088] Access Control

[0089] RBAC (Role-Based Access Control): User permissions are managed based on roles to ensure the principle of least privilege.

[0090] MFA (Multi-factor Authentication): Integrate with Azure AD for multi-factor authentication to improve login security.

[0091] Zero Trust Security Architecture: Implement identity-based secure access control through micro-segmentation and dynamic permission management.

[0092] Data Security:

[0093] VM disk encryption: Encrypt data based on BitLocker to prevent data leakage.

[0094] Transmission data encryption: Ensure VM network communication security through IPSec.

[0095] Log auditing and compliance testing: Based on ELK, VM operation logs are collected to provide audit traceability functions and meet the requirements of Information Security Protection 2.0.

[0096] Automated operation and maintenance and intelligent analysis:

[0097] (1) Operation and maintenance automation

[0098] Ansible + PowerShell DSC: Automates VM configuration, patch updates, service deployment, and other operations, reducing manual intervention.

[0099] Automated alerting: Monitors Hyper-V's operating status based on Prometheus and generates real-time alerts via email.

[0100] Self-healing mechanism: When the system detects a VM anomaly, it automatically restarts, migrates, or rolls back snapshots to ensure business continuity.

[0101] (2) AI intelligent analysis

[0102] Intelligent log analysis: Use the ELK+AI model to detect abnormal logs and automatically identify potential security threats.

[0103] Predictive O&M: Based on AI training data, it predicts VM failure trends, triggers O&M tasks in advance, and reduces the risk of downtime.

[0104] Automatic scaling: Combined with AI load prediction, it dynamically expands / contracts VM resources to improve system elasticity.

[0105] Future optimization and expansion:

[0106] Containerization support: Kubernetes (K8s) can be integrated in the future, Windows containers (Windows Containers) can be supported, and hybrid cloud computing capabilities can be provided.

[0107] Edge computing: Combined with Azure Stack HCI, Hyper-V can be used in edge computing scenarios such as IoT data processing and low-latency AI computing.

[0108] Quantum computing simulation support: Explore Hyper-V combined with Microsoft QDK to provide a quantum computing simulation environment.

[0109] Based on the above method, a device for applying for a Microsoft Hyper-V virtual machine service on an operation and management platform in this embodiment includes: at least one memory and at least one processor;

[0110] The at least one memory is configured to store a machine-readable program;

[0111] The at least one processor is used to call the machine-readable program to execute a method for a cloud management platform to apply for Microsoft Hyper-V virtual machine services.

[0112] The above-mentioned specific implementation methods are only specific cases of the present invention. The patent protection scope of the present invention includes but is not limited to the above-mentioned specific implementation methods. Any technical solutions that conform to the above-mentioned specific implementation methods of the present invention and any appropriate changes or substitutions made thereto by ordinary technicians in the relevant technical field shall fall within the patent protection scope of the present invention.

[0113] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A method for applying for Microsoft Hyper-V virtual machine services on a cloud management platform, characterized in that: Includes user layer, cloud management layer, virtualization management layer, Hyper-V computing resource layer, and storage and network layer; The user layer is used to provide a virtual machine application and management portal, allowing users to apply for virtual machines and perform related configurations according to business needs; The cloud management layer is used to uniformly manage and orchestrate Hyper-V resources, providing automated deployment, resource monitoring, and fault recovery. The virtualization management layer is responsible for the management and optimization of Hyper-V computing resources; The Hyper-V computing resource layer is used to provide computing cluster management and achieve high availability, load balancing and hot migration of VMs; The storage and network layer is used to provide storage and network management.

2. The method for applying for Microsoft Hyper-V virtual machine service on an operation management platform according to claim 1, characterized in that: In the user layer, OpenLdap is used for user identity management, Spring Cloud Gateway is used as the unified API entrance, and the AI training model is used to provide the best VM configuration recommendation and optimize resource allocation. JSON Schema validation allows administrators to define dynamic form structures and implement automated approval strategies in combination with the approval process engine. ELK collects and analyzes user operation logs, providing detailed auditing and backtracking capabilities.

3. The method for applying for Microsoft Hyper-V virtual machine service on an operation and management platform according to claim 2, characterized in that: In the cloud management layer, Terraform and Ansible are used for resource orchestration, supporting unified management of Hyper-V. Activiti implements custom approval policies, adopts a combination of roles and attributes for fine-grained permission control, and combines AI prediction to optimize quota policies. Automated task scheduling is achieved based on Kubernetes+Celery, supporting periodic tasks and event-triggered tasks.

4. The method for applying for Microsoft Hyper-V virtual machine service on an operation management platform according to claim 3, characterized in that: In the virtualization management layer, remote PowerShell+WMI is used for VM resource management, computing tasks are optimized based on the NUMA architecture, NVIDIA GRID is integrated, PCI device passthrough is provided, Dynamic Memory technology is supported, and dynamic adjustment within the VM is performed.

5. The method for applying for Microsoft Hyper-V virtual machine service on an operation and management platform according to claim 4, characterized in that: Use Windows Server cluster technology in the Hyper-V computing resource layer to implement computing pools, dynamically migrate VMs based on resource usage, balance computing loads, optimize CPU and memory utilization, support hot migration of VMs across hosts and storage, and automatically expand computing nodes through HPA to improve resource elasticity.

6. The method for applying for Microsoft Hyper-V virtual machine service on an operation and management platform according to claim 5, characterized in that: In the storage and network layers, SSDs and HDDs are combined to optimize storage performance and costs, and distributed storage is performed based on Storage SpacesDirect.

7. The method for applying for Microsoft Hyper-V virtual machine service on an operation and management platform according to claim 6, characterized in that: Set IOPS limits on virtual disks, perform VXLAN isolation, and use Hyper-V Virtual Switch for VXLAN, OpenFlow, and VLAN management; Integrates with Azure DDoS Protection to detect abnormal traffic in real time and automatically block attacks.

8. A device for applying for Microsoft Hyper-V virtual machine services on an operation and management platform, characterized in that: include: at least one memory and at least one processor; The at least one memory is configured to store a machine-readable program; The at least one processor is configured to call the machine-readable program to execute the method according to any one of claims 1 to 7.

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