CN109002354B - OpenStack-based computing resource capacity elastic expansion method and system - Google Patents
OpenStack-based computing resource capacity elastic expansion method and system Download PDFInfo
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Abstract
The invention provides a computing resource capacity elastic expansion method and system based on OpenStack, wherein the method comprises the steps of capacity expansion and capacity reduction; 1) capacity expansion: 1-1) making a computing node mirror image template and a switch network configuration template; 1-2) determining the number and network segment of hosts to be expanded, determining the management IP and host names of the hosts, restoring the hosts into computing node operating systems with different management IPs and host names in batches according to a computing node mirror image template, and automatically modifying configuration files; 1-3) uploading a switch network configuration template to a switch of the restored computing nodes and loading the switch network configuration template to enable the computing nodes to be in network communication, so that the computing nodes are added into OpenStack computing resources; 2) capacity reduction: 2-1) determining computing nodes to be removed, migrating or releasing virtual machines on the computing nodes, and clearing configuration information of corresponding switch ports; 2-2) removing the basic information and the computing related services of the computing nodes processed in the step 2-1) from the OpenStack cloud platform.
Description
Technical Field
The invention relates to the technical field of cloud computing, in particular to a computing resource capacity elastic expansion method and system based on OpenStack.
Background
With the rapid development of cloud computing technology, governments of various countries increasingly attach importance to the cloud computing service industry, and new opportunities for rapid development of the cloud computing service industry are taken as the national software industry. Cloud computing service has become one of national development strategies in China, and brings new power and new challenges to Chinese economic engines. As an emerging resource using platform, a cloud computing platform forms a relatively mature service mode, and more users can share and use resources.
OpenStack is one of the most popular cloud computing platforms at present, and can integrate huge infrastructure, software composition and data storage to form a huge resource pool, so as to provide computing resources, storage resources and network resource services for users. The system mainly comprises a control node, a network node, a computing node and a storage node. The computing nodes occupy main resources and serve as computing resources to provide computing power for the virtual machines. Thus, the computing resource consists of a batch of computing nodes, each node representing a physical server, and the computing resource capacity is the sum of the computing power of all the computing nodes.
The demand of computing resource capacity changes with the change of business, when the demand of computing resource is large, the computing resource is in shortage, and the capacity needs to be rapidly increased, which is called capacity expansion for short; when the demand of computing resources is small, a large amount of resources are idle, and in order to efficiently utilize the resources, the capacity needs to be quickly reduced, which is abbreviated as capacity reduction. OpenStack supports flexible capacity expansion of computing resources, at present, a common capacity expansion method is an automatic deployment mode and a manual deployment mode, and both the two methods need to install a host operating system, download a software package and configure related services, so that the time consumption is long, and the efficiency is low; meanwhile, the problem that the low version cannot be successfully downloaded due to the upgrade of the required software package is faced. OpenStack does not have a normalized fast capacity reduction function at present, and when computing resources are elastically reduced in capacity, information of removed computing nodes in a cloud platform cannot be automatically cleared, error information can interfere with normal application and operation of a virtual machine, and even stability of the OpenStack cloud platform is affected.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention provides the method and the system for computing resource capacity elastic expansion based on the OpenStack, an elastic expansion flow is designed, under the condition that an operating system and a download software package are not required to be installed, the OpenStack computing resource can be expanded in batch and rapidly, the elastic expansion time is greatly saved, and the resource utilization efficiency is improved; meanwhile, the computing resources can be quickly reduced, the residual information of the cloud platform can be automatically cleared, and the stability of the cloud platform is guaranteed.
In order to solve the technical problems, the technical scheme provided by the invention is as follows:
a computing resource capacity elastic expansion method based on OpenStack comprises expansion and contraction;
1) capacity expansion:
1-1) making a computing node mirror image template and a switch network configuration template;
1-2) determining the number and network segment of hosts to be expanded, determining the management IP and host names of the hosts, restoring the hosts into computing node operating systems with different management IPs and host names in batches according to a computing node mirror image template, and automatically modifying configuration files;
1-3) uploading a switch network configuration template to a switch of the restored computing nodes and loading the switch network configuration template to enable the computing nodes to be in network communication, so that the computing nodes are added into OpenStack computing resources;
2) capacity reduction:
2-1) determining computing nodes to be removed, migrating or releasing virtual machines on the computing nodes, and clearing configuration information of corresponding switch ports;
2-2) removing basic information and computing related services of the computing nodes processed in the step 2-1) from the OpenStack cloud platform, wherein the basic information comprises management IP (Internet protocol) and host name information of the computing nodes; the computing-related services include nova-computer computing services and OpenVSwitch virtual network services.
Further, the computing node image template is an image file made of a computing node operating system through image making software, and the computing node operating system is a clean operating system which is deployed with computing related services, cloud disk services and virtual switch services and does not have a virtual machine to run.
Further, the switch network configuration template is a configuration file generated by a switch for configuring the connection of the computing node, and the switch is shared by a public network and a private network of the computing node.
Further, the management IP and the host name of each host are determined according to the unique identification code of each host in the step 1-2).
Further, in the step 1-2), mirror image restoration software is adopted to carry out batch restoration through a mirror image private network, and the host is set to be network started.
Further, after the step 1-3) is finished, after the restored computing node operating system normally runs the computing related service, the service monitoring program is started automatically, service state and performance monitoring are carried out, the collected monitoring data are sent to the monitoring server side to be collected, and the running condition of the service is displayed through the monitoring page.
Further, after the step 1-3) is finished, integrating the restored computing node operating systems, including virtual machine rebalancing, tenant resource quota adjustment and resource use monitoring;
the virtual machine rebalancing means that a virtual machine part on a computing node with high load is migrated to a newly expanded computing node according to a balancing algorithm so as to ensure the balance of computing resources;
the tenant resource quota adjustment means that the computing resource occupation ratio of each tenant is set according to the requirement of each tenant, and then the quota of each tenant is adjusted according to a formula Ti-N Pi, wherein Ti represents the computing resource quota of the ith tenant, N represents the total computing resource of the whole OpenStack cloud platform, and Pi represents the computing resource occupation ratio of the ith tenant;
the resource use monitoring means that the use conditions of the total computing resources and the computing resources of each tenant are monitored in real time, and the acquired data are sent to the monitoring server for processing.
Further, the unavailable state of the computing node processed in the step 2-1) is discovered through a heartbeat mechanism in the OpenStack cloud platform.
Further, after the step 2-2) is finished, service verification is carried out, wherein the service verification is to verify the state and the performance of the calculation-related service through service monitoring and logging.
An OpenStack-based computing resource capacity elastic scaling system, comprising:
an initial unit, making a computing node mirror image template and a switch network configuration template;
the expansion unit is used for restoring to obtain computing node operating systems with different management IPs and host names according to the computing node mirror image template, and loading a switch network configuration template to a switch of the restored computing node so as to enable the computing nodes to be added into OpenStack computing resources and carry out service state and performance monitoring and data acquisition;
the integration unit is used for carrying out virtual machine rebalancing, tenant resource quota adjustment and resource use monitoring on the restored computing node operating system;
and the capacity reduction unit is used for migrating or releasing the virtual machine on the computing node to be removed, clearing the configuration information of the corresponding switch port, clearing the basic information and the computing related service from the OpenStack cloud platform and carrying out service verification.
Compared with the prior art, the invention has the following advantages:
1. physical hosts can be added into or removed from the OpenStack cloud platform rapidly in a large batch, so that the flexible expansion effect of the computing resource capacity of OpenStack is achieved;
2. operating systems do not need to be installed on the physical hosts one by one, and software packages for calculating related services do not need to be downloaded, so that the problems of downloading failure and complex service configuration are avoided;
3. the program can automatically modify the service-related configuration and automatically clear the compute node service;
4. the system has the advantages of service monitoring and resource monitoring, and can be adaptively monitored and managed;
5. designing a resource quota calculation formula of each tenant;
6. the virtual machine of the computing node can carry out rebalance adjustment;
7. the method simplifies the flexible expansion process of the OpenStack computing resources and improves the resource utilization efficiency.
Drawings
FIG. 1 is a flowchart of a method for computing resource capacity elastic scaling according to the present invention.
Detailed Description
In order to make the aforementioned and other features and advantages of the invention more comprehensible, embodiments accompanied with figures are described in detail below.
The embodiment provides a computing resource capacity elastic scaling method and system based on an OpenStack, which are implemented by technologies such as wildcard mirroring, adaptive modification, service monitoring, and adaptive networking, as shown in fig. 1.
1. The specific capacity expansion process comprises the following steps:
step 1: the initial unit is mainly used for manufacturing templates and comprises a computing node mirror image template and a switch network configuration template. And manufacturing a computing node operating system into a mirror image through mirror image manufacturing software, and using the mirror image as a computing node mirror image template. The compute node operating system must be a clean operating system with compute-related services, virtual switch services, and cloud disk services deployed, and without virtual machines running. Each computing node has two networks, namely a public network and a private network, wherein the public network is a network for the computing node to access the Internet, and the private network is a network for the virtual machines on the computing node to mutually access. Each server is provided with an exchanger, the two networks share the exchanger, and after the exchanger is configured, the configuration file is downloaded to be used as an exchanger network configuration template.
Step 2: the capacity expansion unit is used for batch flashing, and OpenStack computing nodes can be added rapidly in large batches. Firstly, determining the number of hosts and network segments to be expanded, and determining a management IP and a host name according to the unique identification code of each host; and then, restoring the physical hosts set as network startup into computing node operating systems with different management IP and host names in batch through a mirror image private network by using the computing node mirror image template and mirror image restoration software manufactured in the step 1.
And step 3: in the self-adaptive modification process of the configuration of the computing node, although the management IP and the host name of different restored computing nodes are different, the configuration files of the computing-related services such as nova-computer computing service and OpenVSwitch virtual network service which run on an operating system cannot be modified during restoration, and are the same, so that the conflict is easily caused. Therefore, after the restored computing node operating systems are started, the self-adaptive modification program correspondingly self-starts, automatically modifies the computing related service configuration files, and keeps consistent with the basic configuration information of the computing nodes, such as management IP (Internet protocol), host names and the like, thereby ensuring that the services of each restored computing node operating system are not conflicted and can be uniquely identified.
And 4, step 4: and (2) loading a switch network configuration template, switching in network configuration, uploading the switch network configuration templates manufactured in the step (1) to switches on the restored computing node cabinets respectively, and loading the uploaded switch network configuration templates by the switches respectively, so that the switches ensure the network connectivity of the restored computing nodes, and the restored computing nodes formally add OpenStack computing resources.
And 5: after the computing related service on the restored computing node operating system runs normally, the service monitoring program starts automatically, monitors the state and performance of the service, sends the collected monitoring data to the monitoring server for collection, and can directly observe the running condition of the service through the monitoring page.
Step 6: and the integration unit comprises virtual machine rebalancing, tenant resource quota adjustment and resource use monitoring. And a large number of virtual machines run on the computing nodes with high loads before capacity expansion, and the newly expanded computing nodes have no virtual machines, and the virtual machine parts on the computing nodes with high loads are migrated to the newly expanded computing nodes according to a balance algorithm, so that the balance of computing resources is guaranteed.
And 7: and the tenant resource quota adjustment is to set the calculation resource ratio of each tenant according to the service requirement of each tenant, and then adjust the quota of each tenant according to the following formula.
Ti＝N*Pi
Wherein, Ti represents the computing resource quota of the ith tenant, N represents the total computing resource quota of the whole cloud platform, and Pi represents the computing resource occupation ratio of the ith tenant.
And 8: and the resource use monitoring is to monitor the total computing resource use condition and the detailed computing resource use condition of each tenant in real time and send the acquired data to the monitoring server for processing.
2. The specific capacity reduction process comprises the following steps:
step 1: and the capacity reduction unit can remove the OpenStack cloud platform from the computing nodes quickly and massively. And determining the computing nodes to be removed, and migrating or releasing the virtual machines on the computing nodes.
Step 2: clearing the switch network configuration templates (i.e. the configuration information of the switch ports) corresponding to the computing nodes, disconnecting the computing nodes from the OpenStack cloud platform, and discovering that the computing nodes are in an unavailable state by a heartbeat mechanism in the OpenStack cloud platform.
And step 3: and starting an automatic clearing program, and clearing computing node information and services, namely clearing basic information and computing related services of unavailable computing nodes from the OpenStack cloud platform, wherein the computing nodes are removed from computing resources of OpenStack.
And 4, step 4: and service verification, namely verifying the state and performance of the computing related service through service monitoring and logs, so that the stability of the OpenStack cloud platform is ensured.
And finally, the OpenStack computing resource is expanded again only by repeating the steps of the expansion unit and the integration unit, and the capacity is reduced again only by repeating the step of the capacity reduction unit.
Claims (10)
1. A computing resource capacity elastic expansion method based on OpenStack comprises expansion and contraction;
1) capacity expansion:
1-1) making a computing node mirror image template and a switch network configuration template;
1-2) determining the number and network segment of hosts to be expanded, determining the management IP and host names of the hosts, restoring the hosts into computing node operating systems with different management IPs and host names in batches according to a computing node mirror image template, and automatically modifying configuration files;
1-3) uploading a switch network configuration template to a switch of the restored computing nodes and loading the switch network configuration template to enable the computing nodes to be in network communication, so that the computing nodes are added into OpenStack computing resources;
2) capacity reduction:
2-1) determining computing nodes to be removed, migrating or releasing virtual machines on the computing nodes, and clearing configuration information of corresponding switch ports;
2-2) removing the basic information and the computing related services of the computing nodes processed in the step 2-1) from the OpenStack cloud platform.
2. The method of claim 1, wherein the compute node image template is an image file created by imaging software of a compute node operating system, and the compute node operating system is a clean operating system deployed with computing-related services, cloud disk services, virtual switch services, and no virtual machine running.
3. The method of claim 1, wherein the switch network configuration template is a configuration file generated for a switch that configures connections of the computing node, the switch being common to both a public network and a private network of the computing node.
4. The method of claim 1, wherein the management IP and host name of the host are determined in step 1-2) based on the unique identifier of each host.
5. The method according to claim 1, wherein in step 1-2), batch restoration is performed by using mirror restoration software through a mirror private network, and the host is configured to be network-started.
6. The method according to claim 1, wherein after the step 1-3) is finished, after the restored computing node operating system normally runs its computing related service, the service monitoring program is self-started, and performs service state and performance monitoring, sends the collected monitoring data to the monitoring server for collection, and displays the service running condition through the monitoring page.
7. The method according to claim 1, wherein after steps 1-3) are finished, the restored compute node operating systems are integrated, including virtual machine rebalancing, tenant resource quota adjustment, and resource usage monitoring;
the virtual machine rebalancing means that a virtual machine part on a computing node with high load is migrated to a newly expanded computing node according to a balancing algorithm so as to ensure the balance of computing resources;
the tenant resource quota adjustment means that the computing resource occupation ratio of each tenant is set according to the requirement of each tenant, and then the quota of each tenant is adjusted according to a formula Ti-N Pi, wherein Ti represents the computing resource quota of the ith tenant, N represents the total computing resource of the whole OpenStack cloud platform, and Pi represents the computing resource occupation ratio of the ith tenant;
the resource use monitoring means that the use conditions of the total computing resources and the computing resources of each tenant are monitored in real time, and the acquired data are sent to the monitoring server for processing.
8. The method according to claim 1, wherein the unavailable state of the computing node processed in step 2-1) is discovered through a heartbeat mechanism in an OpenStack cloud platform.
9. The method according to claim 1, wherein step 2-2) is completed and then service verification is performed, wherein the service verification is performed by verifying the state and performance of the computation-related service through service monitoring and logging.
10. An OpenStack-based computing resource capacity elastic scaling system, comprising:
an initial unit, making a computing node mirror image template and a switch network configuration template;
the expansion unit is used for restoring to obtain computing node operating systems with different management IPs and host names according to the computing node mirror image template, and loading a switch network configuration template to a switch of the restored computing node so as to enable the computing nodes to be added into OpenStack computing resources and carry out service state and performance monitoring and data acquisition;
the integration unit is used for carrying out virtual machine rebalancing, tenant resource quota adjustment and resource use monitoring on the restored computing node operating system;
and the capacity reduction unit is used for migrating or releasing the virtual machine on the computing node to be removed, clearing the configuration information of the corresponding switch port, clearing the basic information and the computing related service from the OpenStack cloud platform and carrying out service verification.
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| CN109788032B (en) * | 2018-12-17 | 2021-12-14 | 深圳壹账通智能科技有限公司 | Method and device for acquiring mirror image file, computer equipment and storage medium |
| CN110580198B (en) * | 2019-08-29 | 2023-08-01 | 上海仪电（集团）有限公司中央研究院 | Method and device for adaptively switching OpenStack computing node into control node |
| CN110708612B (en) * | 2019-10-10 | 2021-12-03 | 珠海与非科技有限公司 | Gold brick super-fusion cloud server capable of rapidly expanding capacity |
| CN114327645A (en) * | 2020-10-12 | 2022-04-12 | 宝能汽车集团有限公司 | Capacity expansion method and device for vehicle computing capacity, vehicle and storage medium |
| CN115145736B (en) * | 2022-09-05 | 2022-12-06 | 中国人寿保险股份有限公司上海数据中心 | Cloud platform quota intelligent distribution system based on Spark distributed computing |
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