Method for carrying out full-life-cycle management on multi-cloud service

Abstract

The invention relates to the field of cloud service management, in particular to a method for carrying out full-life-cycle management on multi-cloud services. Comprising the steps of S1, adding a multi-cloud management account required by a project user for a business department based on a project resource demand initiated by the business department; s2, initiating a cloud resource demand through a multi-cloud management account; s3, examining and approving the cloud resource demand, and generating cloud resources or recycling the cloud resources; s4, distributing cloud resources from the multi-cloud resource pool to project users; in the step S3, the use condition of the cloud resources is monitored, adjusted and optimized, and the cloud resources are released and recycled after the use of the cloud resources is finished. According to the invention, the resources of different cloud service providers are integrated, network configuration, storage, resource calculation and security setting are carried out, the cloud resources are monitored and optimized, the performance and cost of the cloud service are monitored in real time, the use efficiency of the cloud resources is improved, and the cost is reduced.

Description

Technical Field

[0001] The present invention relates to the field of cloud service management, and more particularly to a method for full life cycle management of multi-cloud services. Background Art

[0002] The implementation of multi-cloud management is a complex and critical process, which involves unified management of resources, services, and applications from different cloud service providers to ensure efficient utilization of resources, cost optimization, and business continuity. There are the following problems in existing multi-cloud management platforms: insufficient multi-cloud integration, mostly only being able to integrate the cloud products of the manufacturer itself; lack of unified management of cloud resources, being limited to cloud host resources rather than all infrastructure resources utilized by the multi-cloud platform; the scheduling management of cloud resources is relatively scattered, and it is not easy to master resource utilization and performance bottlenecks. Summary of the Invention

[0003] The object of the present invention is to provide a method for full life cycle management of multi-cloud services to solve the above technical problems;

[0004] The technical problems solved by the present invention can be achieved by the following technical solutions:

[0005] A method for full life cycle management of multi-cloud services includes:

[0006] Step S1: Based on the project resource requirements initiated by the business department, add multi-cloud management accounts required by project users for the business department;

[0007] Step S2: The project users initiate cloud resource requirements through the multi-cloud management accounts;

[0008] Step S3: Approve the cloud resource requirements, and the multi-cloud resource pool management generates or recycles cloud resources;

[0009] Step S4: Allocate cloud resources from the multi-cloud resource pool and distribute them to the project users;

[0010] In step S3, it also includes monitoring the usage of cloud resources and adjusting and optimizing, and releasing and recycling cloud resources when the use of cloud resources ends.

[0011] Preferably, the project resource requirements in step S1 at least include processor, memory, bandwidth, access control, and load balancing requirements; the cloud resource requirements are initiated in the form of a service level agreement or a request form.

[0012] Preferably, in step S3, by analyzing the cloud resource requirements, the cloud resources required by the cloud resource requirements are obtained, a resource template is generated, a resource pool is selected from several cloud platforms as the multi-cloud resource pool according to the cloud resource requirements, and the cloud resources of the multi-cloud resource pool are deployed to the cloud environment specified by the project user to complete the distribution of cloud resources.

[0013] Preferably, in step S3, the method for generating cloud resources includes,

[0014] Generating a configuration file according to the cloud resource requirements and defining the type of virtual machine;

[0015] Allocating cloud resources from the available multi-cloud resource pools according to the configuration file and associating them with the corresponding user requirements and resource types;

[0016] Calling the interface of the cloud platform to create a virtual machine instance, connecting the virtual machine to a pre-configured network, allocating an IP address, and configuring firewall and network resources for testing and inspection.

[0017] Preferably, the cloud resources in step S3 at least include computing resources, storage resources, network resources, security resources, and backup and disaster prevention resources.

[0018] Preferably, the method for monitoring the usage of the cloud resources in step S3 and adjusting and optimizing includes,

[0019] Collecting the usage data and pricing information of the cloud resources, matching the usage data with the pricing model of the cloud resources, and generating a cost analysis report for each project;

[0020] Monitoring the cost, and predicting future cost expenditures according to the historical data and current usage trends of the cost;

[0021] Providing cost optimization suggestions according to the usage data; setting a cost budget and issuing an alarm when the cost exceeds the cost budget.

[0022] Preferably, the method for monitoring the usage of the cloud resources in step S3 and adjusting and optimizing further includes,

[0023] Collecting real-time monitoring data on the usage of cloud resources;

[0024] Analyzing the usage status of the cloud resources according to the real-time monitoring data;

[0025] Analyzing the usage trend of the cloud resources, determining whether the current usage status of the cloud resources exceeds the preset resource usage threshold. If it exceeds, trigger an alarm. If not, analyze the usage trend of the cloud resources to identify bottleneck situations and waste situations in future cloud resource usage.

[0026] Preferably, the method for releasing and recycling cloud resources in step S3 includes

[0027] Continuously detect the usage status of cloud resources. If the detection result is normal, determine whether to end the operation of the cloud service. If it ends, recycle the cloud resources;

[0028] If it does not end, continue to maintain the normal use of cloud resources; if the detection result is abnormal, handle the abnormal status and optimize the resource configuration, determine whether the abnormal status is resolved, return to determine whether to end the operation of the cloud service. If it is not resolved, notify the background to intervene.

[0029] Preferably, in step S3, the method for handling the abnormal status and optimizing the resource configuration includes

[0030] Collect abnormal information through logs and monitoring, analyze the error codes and performance metrics in the logs, and enable the troubleshooting tool to repair the faults;

[0031] Analyze the actual usage of cloud resources and identify the bottlenecks of cloud resources;

[0032] Adjust the number of virtual machine instances according to the load change, distribute the traffic to multiple servers through the load balancer, and reallocate cloud resources.

[0033] Preferably, in step S3, receive the released cloud resources, add the cloud resources back to the multi-cloud resource pool. The recycled cloud resources at least include computing resources, storage resources, and network resources; the recycled cloud resources are reallocated to the remaining project users.

[0034] Advantages of the present invention: Due to the above technical solutions, the present invention integrates cloud resources from different cloud platforms, monitors and optimizes cloud resources, monitors the performance and cost of cloud services in real time, optimizes resources according to the monitoring data, improves the utilization efficiency of cloud resources and reduces costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 It is a schematic diagram of the steps of the method for full life cycle management of multi-cloud services in an embodiment of the present invention;

[0036] Figure 2 It is a flowchart of the method for full life cycle management of multi-cloud services in an embodiment of the present invention. DETAILED DESCRIPTION

[0037] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0038] It should be noted that, without conflict, the embodiments in the present invention and the features in the embodiments can be combined with each other.

[0039] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments, but it is not intended to limit the present invention.

[0040] A method for full life cycle management of multi-cloud services, as Figure 1 , Figure 2 shown, includes

[0041] Step S1: Based on the project resource requirements initiated by the business department, add multi-cloud management accounts required by the project users for the business department.

[0042] Step S2: The project users initiate cloud resource requirements through the multi-cloud management accounts.

[0043] Step S3: Approve the cloud resource requirements, and the multi-cloud resource pool management generates or recovers cloud resources.

[0044] Step S4: Allocate cloud resources from the multi-cloud resource pool and distribute them to the project users.

[0045] In Step S3, it also includes monitoring the usage of cloud resources and adjusting and optimizing them, and releasing and recovering the cloud resources when the use of cloud resources ends.

[0046] Specifically, in view of the problem of the lack of unified management of cloud resources in the prior art, the present invention establishes a suitable multi-cloud management system, formulates and implements multi-cloud management strategies, monitors, optimizes and continuously improves, and forms a method for full life cycle management of multi-cloud services. The cloud resources can obtain full life cycle control from application, creation, delivery, operation and maintenance to final release in the present invention.

[0047] In the life cycle management of cloud resources, the cloud resources involved include but are not limited to: computing, storage, network, security group, load balancer (SLB), relational database service (RDS), object storage service (OSS), physical server, etc.

[0048] The method for full life cycle management of multi-cloud services provided by the present invention is integrated in the cloud management platform (CMP), and can collect, analyze and display various data related to the cloud infrastructure. The cloud management platform integrates monitoring tools to continuously monitor the resources.

[0049] The present invention integrates resources from different cloud service providers, configures network, storage, computing resources, and security settings to ensure that cloud services can work together, monitors and optimizes cloud resources, and real-time monitors the performance and cost of cloud services. Resource optimization is performed based on the monitoring data, including adjusting resource allocation, automatic scaling, etc., to improve efficiency and reduce costs.

[0050] The management of cloud resources in the present invention includes security management and cost management. Security management adopts a multi-cloud security strategy, including authentication, access control, data encryption, compliance checks, etc., to ensure the security of data and applications.

[0051] Cost management optimizes resource usage and reduces unnecessary resource overhead by tracking and analyzing costs in a multi-cloud environment. After the use of cloud services ends, the released cloud resources are recycled into the resource pools of the corresponding cloud service providers and dynamically re-allocated to new users according to demand.

[0052] The present invention tracks the status of cloud resources to ensure the maximization of the utilization rate of the resource pool and avoid resource idleness.

[0053] The present invention also includes application management, evaluation, and iteration of cloud resources. Application management is to manage application programs deployed in a multi-cloud environment, including version control, updates, backups, and disaster recovery plans.

[0054] Evaluation and iteration is to regularly evaluate the effects of multi-cloud services and continuously iterate and improve multi-cloud management strategies and practices according to business development and technological progress.

[0055] Through the method for full-life cycle management of multi-cloud services proposed by the present invention, full-life cycle management of multi-cloud services is realized, ensuring the efficient, secure, and economical operation of the multi-cloud environment.

[0056] In a preferred embodiment, the project resource requirements in step S1 at least include processor, memory, bandwidth, access control, and load balancing requirements; the cloud resource requirements are initiated in the form of a service level agreement or a request form.

[0057] Specifically, the business department initiates project resource requirements, which at least include the required processor, memory, bandwidth, access control, and load balancing information;

[0058] The administrator adds a multi-cloud management account for the business department; the project users of the business department initiate cloud resource requirements in the form of a service level agreement or a request form through the multi-cloud management account, apply for the required cloud resources, and after the administrator approves the cloud resource requirements, step S4 is executed to allocate cloud resources.

[0059] In a preferred embodiment, in step S3, by parsing the cloud resource requirements, the cloud resources required by the cloud resource requirements are obtained, a resource template is generated, a resource pool is selected from several cloud platforms as a multi-cloud resource pool according to the cloud resource requirements, and the cloud resources of the multi-cloud resource pool are deployed to the cloud environment specified by the project user to complete the distribution of cloud resources.

[0060] Specifically, the method for full life cycle management of multi-cloud services provided by the present invention is deployed on a multi-cloud management platform. Users submit cloud resource requirements through the multi-cloud management platform, such as virtual machines (VMs), storage, network bandwidth, etc. The cloud resource requirements are submitted in the form of a service level agreement (SLA) or a request form.

[0061] The multi-cloud management platform parses the cloud resource requirements, including computing power, storage space, network bandwidth, etc., and generates a resource template according to the requirements.

[0062] Further specifically, the multi-cloud management platform of the present invention selects a suitable resource pool from different cloud platforms according to the cloud resource requirements and resource policies, such as cost, performance, compliance requirements, etc.

[0063] The resource pool can include public clouds, such as Alibaba Cloud, Tencent Cloud, private clouds, such as ZStack Cloud, VMware, or a hybrid cloud architecture.

[0064] The multi-cloud management platform of the present invention will allocate resources according to the real-time resource availability and load conditions.

[0065] In a preferred embodiment, in step S3, the method for generating cloud resources includes,

[0066] Generating a configuration file according to the cloud resource requirements to define the type of virtual machine;

[0067] Allocating cloud resources from the available multi-cloud resource pool according to the configuration file and associating them with the corresponding user requirements and resource types;

[0068] Calling the interface of the cloud platform to create a virtual machine instance, connecting the virtual machine to a pre-configured network, allocating an IP address, and configuring the firewall and network resources for testing and inspection.

[0069] Specifically, the steps for generating cloud host resources of the present invention include,

[0070] Step 1, resource request parsing: The platform receives the cloud resource requirements and generates a configuration file according to the requirements to define the type of virtual machine, such as vCPU, memory, storage type.

[0071] Step 2, resource allocation: Allocate resources from the available resource pool according to the configuration file and associate them with the corresponding computing, storage, and network resources.

[0072] Computing resources: including virtual CPUs (vCPUs) and memory (RAM). Resources can be dynamically adjusted according to user needs during creation, such as selecting different specifications of instance types, such as high-performance computing instances, large storage instances, etc.

[0073] Storage resources: External storage includes block storage, object storage, and file storage. The CMP will allocate storage capacity according to user needs to ensure data persistence and access speed. Such as using Huawei's (Elastic Block Storage) or Inspur storage, etc.

[0074] Network resources: Network bandwidth, Virtual Private Network (VPN), firewall rules, Load Balancer (LoadBalancer), and other network resources. The CMP will ensure that the cloud host is connected to the appropriate virtual network and allocate corresponding bandwidth resources to meet the network traffic needs of project users. In addition, it may involve configuring security groups, Virtual Network Isolation (VLAN), cross-site connections, etc.

[0075] Step 3, virtual machine instantiation: Call the cloud platform interface (API) to create a virtual machine instance, start the operating system, and install necessary software packages or applications.

[0076] Step 4, network and security configuration: Connect the virtual machine to a pre-configured network, assign an IP address, and configure network resources such as firewalls and load balancers.

[0077] Step 5, testing and delivery: Conduct health checks to ensure that resources work as expected, and return relevant information such as IP addresses and credentials to the user.

[0078] More specifically, after the configuration is completed, the platform of the present invention will trigger an automated deployment process, deploy the configured resources to the cloud environment specified by the user, and provide corresponding access credentials and monitoring tools. The entire process is achieved through a Continuous Integration / Continuous Delivery (CI / CD) pipeline, thereby realizing the rapid and automated delivery of resources.

[0079] In a preferred embodiment, the cloud resources in step S3 at least include computing resources, storage resources, network resources, security resources, and backup and disaster prevention resources.

[0080] Specifically, the cloud host resources involved in the present invention include,

[0081] Computing resources, including virtual CPUs, memory, and if there is a high-performance computing requirement, also including GPUs.

[0082] Storage resources, including local storage, block storage, object storage, and file storage.

[0083] Network resources, including Virtual Private Network (VPC), subnets, network security groups, load balancing, Elastic IP addresses, bandwidth configuration, etc.

[0084] Security resources, including firewalls, encryption services, Identity and Access Management (IAM), key management, etc.

[0085] Backup and disaster recovery, including backup services and disaster tolerance services.

[0086] In a preferred embodiment, the method for monitoring the usage of cloud resources in step S3 and adjusting and optimizing includes,

[0087] Collect the usage data and pricing information of cloud resources, match the usage data with the pricing model of cloud resources, and generate a cost analysis report for each item;

[0088] Monitor the cost, and predict future cost expenditures based on the historical data and current usage trends of the cost;

[0089] Provide cost optimization suggestions based on the usage data; set a cost budget, and issue an alarm when the cost exceeds the cost budget.

[0090] Specifically, the platform of the present invention automatically collects the usage data and pricing information of cloud services by integrating with the APIs of different cloud service providers. The usage data includes the real-time usage and billing details of various resources such as cloud host instances, storage, network, data transmission, etc.

[0091] Combined with the pricing documents of cloud service providers, match the collected usage data with the corresponding pricing model. For example, the CPU, memory, and storage usage of virtual machines are billed separately.

[0092] The platform matches the usage data with the pricing model of cloud services, and generates a cost breakdown report for each item. For example, break down the virtual machine cost (by CPU, memory, disk), storage cost (by capacity, storage type), network transmission cost, etc. Refine the cost to specific business units or projects through a tagging system.

[0093] The present invention has a real-time monitoring function, and can predict future cost expenditures based on historical data and current usage trends. It is used to understand the change trend of cloud expenditures in advance and avoid unnecessary expenditures; time series analysis or regression analysis can be used to predict future costs based on historical data.

[0094] Provide cost optimization suggestions based on the usage data and analysis, such as saving costs by reducing underutilized resources, selecting low-cost storage, using reserved instances or on-demand instances, etc.

[0095] Identify underutilized resources through data analysis, evaluate instances with usage rates below a certain threshold, and generate optimization suggestions

[0096] Allow enterprises to set cost budgets and quotas, and ensure timely notification to users when costs exceed through an alert mechanism to help achieve budget control. When costs exceed the cost budget or are close to the cost budget, notifications are sent via email, text message, or an application within the platform.

[0097] More specifically, the multi-cloud service platform of the present invention not only provides support during resource allocation, but also continuously monitors, adjusts, and optimizes resources throughout their entire life cycle.

[0098] The platform regularly evaluates whether the cloud hosts in use meet the expected performance requirements, whether resources are overused or approaching bottlenecks, provides various optimization suggestions, and provides a graphical management interface to assist managers and users in operation and maintenance.

[0099] The present invention integrates monitoring tools to monitor resource performance, designs a regular evaluation program, such as checking the usage efficiency and performance of resources weekly or monthly to see if they meet expectations. A management interface can be built using front-end frameworks such as React or Angular to display resource status, performance metrics, and optimization suggestions.

[0100] In a preferred embodiment, the method for releasing and recycling cloud resources in step S3 includes

[0101] Continuously detect the usage status of cloud resources. If the detection result is normal, determine whether to end the operation of the cloud service. If so, recycle the cloud resources;

[0102] If not, continue to maintain the normal use of the cloud resources;

[0103] If the detection result is abnormal, handle the abnormal status and optimize the resource configuration. Determine whether the abnormal status is resolved, and return to determine whether to end the operation of the cloud service. If not resolved, notify the background to intervene.

[0104] In a preferred embodiment, the method for monitoring the usage of cloud resources and adjusting and optimizing in step S3 further includes

[0105] Collect real-time monitoring data on the usage of cloud resources; analyze the usage status of cloud resources based on the real-time monitoring data;

[0106] Analyze the usage trend of cloud resources, determine whether the current usage status of cloud resources exceeds the preset resource usage threshold. If it exceeds, trigger an alarm. If not, analyze the usage trend of cloud resources to identify bottleneck and waste situations in future cloud resource usage.

[0107] Specifically, the present invention uses Prometheus to collect, store, and query real-time monitoring data of cloud resources, which is applicable to monitoring performance metrics such as CPU, memory, disk I / O, and network traffic. It is used in combination with Grafana to visualize the monitoring data and generate a monitoring dashboard.

[0108] In step B22, the important performance or status monitored includes

[0109] CPU utilization rate, which monitors the CPU load of the cloud host. If it exceeds 80%, it is regarded as high load.

[0110] Memory usage. When the memory usage rate is close to 90%, it is determined that there is a bottleneck.

[0111] Network bandwidth, which monitors the network traffic flowing in and out. When the network utilization rate exceeds 70%, it is determined to be overloaded.

[0112] Disk I / O, which measures the read and write performance. If the disk I / O waiting time exceeds the set time, it indicates a disk bottleneck.

[0113] Instance status, which monitors whether the virtual machine is running normally and whether there is a downtime.

[0114] When the current usage status of the cloud resources exceeds the preset resource usage threshold, for example, the CPU exceeds 80% utilization rate, an alarm is triggered; the platform will notify by means of emails, text messages, automated operations, etc. when the resources exceed the set threshold.

[0115] The present invention can also analyze the trend of resource usage through time series analysis or regression analysis methods to predict whether a bottleneck will occur; or predict whether the resource utilization rate is too low and there is wasted resources.

[0116] In a preferred embodiment, in step S3, the method for handling abnormal status and optimizing resource allocation includes

[0117] Collecting abnormal information through logs and monitoring, analyzing the error codes and performance metrics in the logs, and enabling the troubleshooting tool to repair the faults.

[0118] Analyzing the actual usage situation of the cloud resources to identify the bottlenecks of the cloud resources.

[0119] Adjusting the number of virtual machine instances according to the load change, distributing the traffic to multiple servers through a load balancer, and reallocating the cloud resources.

[0120] Specifically, the troubleshooting process includes fault detection and root cause analysis. Abnormal information is captured through a logging system (such as the ELK stack) and monitoring tools, and the error codes and performance metrics in the logs are analyzed.

[0121] Automatically restart instances or reallocate resources through automation tools such as Terraform or Ansible to quickly resume services when a failure is detected.

[0122] The present invention analyzes the actual usage of resources through a monitoring tool to identify bottlenecks in the CPU, memory, network, or storage.

[0123] The multi-cloud management platform continuously collects data, analyzes the resource usage in different time periods, and discovers potential sources of bottlenecks. The present invention analyzes and statistically processes the monitoring data of resource usage such as CPU utilization rate, memory usage, network bandwidth, and disk I / O, and uses statistical analysis methods to detect and mark outliers to discover the sources of bottlenecks.

[0124] Comparing the resource usage in different time periods can compare the resource usage during peak and off-peak periods, identify the changing trends of resource usage over time, and find the correlation between events and resource usage. By comparing the usage of different resources, their correlation can be analyzed. For example, if the CPU utilization rate is high while the memory utilization rate is normal, it indicates an increase in the computational load of the application.

[0125] More specifically, resource reallocation includes,

[0126] Auto-scaling, automatically increasing or decreasing the number of virtual machine instances according to usage to reasonably allocate resources according to load changes.

[0127] Load balancing, distributing traffic to multiple servers through a load balancer to avoid overloading a single machine.

[0128] Reconfiguring resources, when the configuration of a specific resource is unreasonable, the platform can automatically reconfigure it, such as adjusting the vCPU and memory of a virtual machine, or switching to a higher-performance storage solution.

[0129] In a preferred embodiment, in step S3, the released cloud resources are received, and the cloud resources are re-added to the multi-cloud resource pool. The recycled cloud resources at least include computing resources, storage resources, and network resources; the recycled cloud resources are reallocated to the remaining project users.

[0130] When a project user finishes using cloud resources and no longer needs them, for example, when the user ends the use of a service instance, the platform communicates with each cloud platform through the API to automatically release the computing, storage, network, and other cloud resources of the service. The cloud resources are released and recycled, and the process turns to step A.

[0131] Through step A for multi-cloud resource pool management, the released cloud resources are received and added back to the resource pool.

[0132] The resources recycled into the resource pool include

[0133] Computing resources: Release the vCPUs and memory of the virtual machine to make them return to the available resource pool and wait for reallocation.

[0134] Storage resources: Release block storage and object storage. When these storages are no longer needed, they will be returned to the storage pool.

[0135] Network resources: Release the allocated IP addresses, network bandwidth, VPN channels, etc. to make them available for other service instances.

[0136] Perform resource pool management. The released resources will be recycled into the corresponding cloud service provider's resource pool and dynamically reallocated to new users according to requirements. The platform will track the status of these resources to ensure the maximization of resource pool utilization and avoid resource idleness.

[0137] In summary, the present invention integrates the resources of different cloud service providers, configures network, storage, computing resources and security settings, monitors and optimizes cloud resources, monitors the performance and cost of cloud services in real time, optimizes resources according to the monitoring data, improves the utilization efficiency of cloud resources and reduces costs.

[0138] The above are only the preferred embodiments of the present invention, and do not limit the implementation manners and protection scope of the present invention. For those skilled in the art, it should be realized that all equivalent replacements and obvious changes made by using the description and illustrations of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for full life cycle management of multi-cloud services, characterized in that: include, Step S1, based on the project resource requirements initiated by the business department, adding a multi-cloud management account required by the project user for the business department; Step S2, the project user initiates cloud resource demand through the multi-cloud management account; Step S3, approving the cloud resource demand, and the multi-cloud resource pool management generates cloud resources or recycles cloud resources; Step S4, allocating cloud resources from the multi-cloud resource pool and distributing them to the project users; The step S3 also includes monitoring the usage of the cloud resources and adjusting and optimizing them, and releasing and recycling the cloud resources after the usage of the cloud resources is completed.

2. The method for full life cycle management of multi-cloud services according to claim 1, characterized in that: The project resource requirements in step S1 include at least processor, memory, bandwidth, access control, and load balancing requirements; the cloud resource requirements are initiated in the form of a service level agreement or a request form.

3. The method for full life cycle management of multi-cloud services according to claim 1, characterized in that: In step S3, the cloud resource requirements are parsed to obtain the cloud resources required for the cloud resource requirements, a resource template is generated, a resource pool is selected from several cloud platforms as the multi-cloud resource pool according to the cloud resource requirements, and the cloud resources of the multi-cloud resource pool are deployed to the cloud environment specified by the project user to complete the distribution of cloud resources.

4. The method for full life cycle management of multi-cloud services according to claim 3, characterized in that: In step S3, the method for generating cloud resources includes: Generate a configuration file based on the cloud resource requirements to define the type of virtual machine; Allocate cloud resources from the available multi-cloud resource pool according to the configuration file and associate them with the corresponding user requirements and resource types; Call the interface of the cloud platform to create a virtual machine instance, connect the virtual machine to a pre-configured network, assign an IP address, configure the firewall and network resources, and perform testing and inspection.

5. The method for full life cycle management of multi-cloud services according to claim 3, characterized in that: The cloud resources in step S3 include at least computing resources, storage resources, network resources, security resources and backup and disaster prevention resources.

6. The method for full life cycle management of multi-cloud services according to claim 1, characterized in that: Step S3: The method for monitoring the usage of the cloud resources and adjusting and optimizing the cloud resources includes: Collecting usage data and pricing information of cloud resources, matching the usage data with the pricing model of cloud resources, and generating cost analysis reports for each project; Monitor costs and forecast future cost expenditures based on historical cost data and current usage trends; providing cost optimization recommendations based on said usage data; Set a cost budget and get an alert when costs exceed the budget.

7. The method for full life cycle management of multi-cloud services according to claim 1, characterized in that: Step S3: The method of monitoring the usage of the cloud resources and adjusting and optimizing the cloud resources also includes: Collect real-time monitoring data on cloud resource usage; Analyze the usage status of cloud resources based on real-time monitoring data; Analyze the usage trend of cloud resources to determine whether the current usage status of cloud resources exceeds the preset resource usage threshold. If it exceeds, trigger an alarm. If not, analyze the usage trend of cloud resources to identify bottlenecks and waste in future cloud resource usage.

8. The method for full life cycle management of multi-cloud services according to claim 1, characterized in that: Step S3: The method for releasing and recovering cloud resources includes: Continuously detect the status of cloud resource usage. If the detection result is normal, determine whether to end the cloud service. If so, recycle the cloud resources. If it is not ended, continue to use the cloud resources normally; If the detection result is abnormal, handle the abnormal state and optimize resource allocation, determine whether the abnormal state is resolved, return to determine whether to end the operation of the cloud service, and if not resolved, notify the background to intervene.

9. The method for full life cycle management of multi-cloud services according to claim 8, characterized in that: In step S3, the method for handling abnormal conditions and optimizing resource allocation includes: Collect exception information through logs and monitoring, analyze error codes and performance indicators in logs, and use troubleshooting tools to fix faults; Analyze the actual usage of cloud resources and identify bottlenecks of cloud resources; Adjust the number of virtual machine instances according to load changes, distribute traffic to multiple servers through load balancers, and redistribute cloud resources.

10. The method for full life cycle management of multi-cloud services according to claim 1, characterized in that: In step S3, released cloud resources are received and added back to the multi-cloud resource pool, where the recovered cloud resources include at least computing resources, storage resources and network resources; the recovered cloud resources are reallocated to the remaining project users.

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