CN112948055A - Innovative course experiment automatic management method and system based on cloud computing - Google Patents
Innovative course experiment automatic management method and system based on cloud computing Download PDFInfo
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Abstract
The invention relates to an innovative course experiment automatic management method and system based on cloud computing, wherein the method adopts a RBD client of a Ceph cluster as a storage back end of a Glance component, a Nova component and a Cinder component in OpenStack, and uses a cloud hard disk snapshot as a course experiment template to automatically manage the course experiment of students, wherein the cloud hard disk snapshot is specifically generated as follows: the system comprises an experiment management node unit, a cloud platform control node unit, a mirror image node unit, a computing node unit and a storage node unit. Compared with the prior art, the problems of large communication flow, low storage efficiency and prolonged virtual machine starting time in the innovative course experiment management process of the colleges and universities experiment cloud platform are solved.
Description
Technical Field
The invention relates to the technical field of cloud computing, in particular to an innovative course experiment automatic management method and system based on cloud computing (OpenStack).
Background
The current innovative course experiment in colleges and universities has the following characteristics:
(1) in the experiment operation process, students have the requirements of independently updating and installing software, and hope to store the last installation environment and experiment state in the next class experiment;
(2) experiment operation often requires the use of a distributed cluster experiment environment;
(3) the experiment has higher requirements on the computing and storage environment of the experiment host.
The traditional experimental machine room of colleges and universities is developed around the management mode of one person and one machine, and the computer can be restored to the pre-installation state after being restarted, so that the requirements of the innovative course experiment can obviously not be met. Cloud computing is used as a new resource using mode, has the advantages of demand allocation, elastic expansion and the like, and the establishment of an experimental cloud platform in colleges and universities based on the cloud computing technology is an effective means for meeting the requirement of an innovative course experimental environment. In the field of cloud computing, OpenStack has gradually become a construction standard of current private cloud due to its loosely-coupled and modularized open-source design concept. Using OpenStack to carry out innovative course experiment management, firstly, creating a virtual machine for each student according to course experiment requirements during class practice, and establishing a mapping relation between student IDs and virtual machine IDs; then, performing snapshot operation on all virtual machines of each student during class giving, and establishing a mapping relation between student IDs and virtual machine snapshot IDs; and finally, creating a corresponding virtual machine for each student based on the mapping relation between the student ID and the virtual machine snapshot ID in the next class.
However, the above method has the following problems:
(1) the network communication flow is large, and the virtual machine snapshot needs to be repeatedly moved between the storage node and the computing node in the course of going to and going to the class;
(2) the system has low storage efficiency, and the system needs to independently store all the virtual machine snapshots of each student after class;
(3) the virtual machine is slow to start, the virtual machine snapshot needs to be transmitted from the storage node to the computing node in class, and then the virtual machine is created in the computing node based on the virtual machine snapshot.
In summary, how to avoid a snapshot content transmission link, improve system storage efficiency, accelerate deployment speed of a virtual machine, and simultaneously satisfy innovative course experiment requirements is a technical problem to be solved urgently by the experimental cloud platform in colleges and universities at present.
Disclosure of Invention
The invention aims to overcome the defects in the prior art, provides an innovative course experiment automatic management method and system based on cloud computing, and solves the problems of large communication flow, low storage efficiency and prolonged virtual machine starting time in the innovative course experiment management process of an experiment cloud platform in colleges and universities.
The purpose of the invention can be realized by the following technical scheme:
according to one aspect of the invention, an innovative course experiment automatic management method based on cloud computing is provided, the method adopts a radial client of a Ceph cluster as a storage back end of a Glance, Nova and a Cinder component in OpenStack, and uses a cloud hard disk snapshot as a course experiment template to automatically manage the course experiment of students (the cloud hard disk snapshot is used as the course experiment template to establish a one-to-many mapping relation between the students and the snapshot, so as to manage the course experiment of the students), wherein the cloud hard disk snapshot is specifically generated as follows: the method comprises the steps of uploading RAW format mirror images required by experimental courses, manufacturing the mirror images into cloud hard disks, and finally manufacturing snapshots for the cloud hard disks.
As a preferred technical scheme, the method comprises the following specific steps:
s1, calling an OpenStack mirror image service interface Glance-api to upload a RAW format basic mirror image according to the course experiment requirements;
s2, calling an OpenStack block storage service interface (render-api) to make the uploaded basic mirror image into a cloud hard disk;
s3, calling an OpenStack block storage service interface (render-api) to make a cloud hard disk into a cloud hard disk snapshot;
s4, storing a mapping relation table of cloud hard disk snapshot IDs and innovative course IDs in a business layer database;
s5, executing lesson taking operation, judging whether the innovative course is the first lesson taking, if so, executing the following steps:
s51) based on the cloud hard disk snapshot associated with the course in the business layer database, calling a circle-api service to create a corresponding cloud hard disk for each student, and storing the mapping relation between the ID of the student and the ID of the cloud hard disk in the business layer database;
s52) based on the cloud hard disk ID associated with each student ID in the business layer database, calling a Nova-api interface to create a corresponding virtual machine for the student, and storing the mapping relation between the student ID and the virtual machine ID in the business layer database;
if the innovative course is not a first class, based on the cloud hard disk ID associated with each student ID in the business layer database, invoking a Nova-api service to create a corresponding virtual machine for the student, and storing the mapping relation between the student ID and the virtual machine ID in the business layer database;
and S6, executing the course leaving operation, and calling Nova-api service to delete the virtual machine corresponding to each student (reserving a cloud hard disk of the virtual machine) according to the mapping relation between the ID of the student and the ID of the virtual machine in the service layer database.
As a preferred technical solution, the cloud disk snapshot in step S3 is created based on the rbd copy-on-write technology, and protection is performed on the snapshot based on rbd snap protect.
As a preferred technical solution, the mapping relationship table of the cloud hard disk snapshot ID and the innovative course ID in step S4 includes five key fields, i.e., CourseID, snapshot ID, InstanceName, flavonid, and OrderID; the InstanceName and the FlavorID fields respectively designate a name and resource configuration for the virtual machine created based on the snapshot Snapshot ID; the OrderID field is provided to address the distributed cluster experiment environment requirements of the innovative course and indicates the sequence number of the current snapshot in all snapshots associated with the course.
As a preferred technical solution, the association method of the lesson and the student in the step S5 includes: one is to automatically import student information through a connected educational administration system, and the other is to manually import and establish association with a course after storing the student information in an Excel table for a temporarily created course.
As a preferred technical solution, after the execution of the lesson operation in step S5 is completed, the user logs in the Web browser of the virtual machine based on the Guacamole, where the Windows operating system is connected by using the RDP protocol, the Linux operating system is connected by using the SSH protocol, and different experimental hosts in the distributed cluster are flexibly switched by using the Tab tag of the browser.
As a preferred technical scheme, the method allows the system to flexibly change the experiment template between two experiment courses; when the experiment template is replaced, the system needs to delete the existing cloud hard disks of all students under the course, and updates the mapping relation between the course and the new experiment template in the business database; after the template is replaced, the processing flow of the next lesson of the system is consistent with the lesson starting operation of the lesson for the first time.
According to another aspect of the present invention, there is provided a system for the automatic management method of course experiment based on cloud computing, the system comprising:
the experiment management node unit is deployed in a service layer application program and a corresponding database, provides course-centered on-off management service, and is used for performing process management and control on experimenters, experiment templates, experiment hosts and experiment resources related to innovative experiment courses;
the cloud platform control node unit is deployed in control services of Keystone and Neutron of OpenStack and Nova components, a Monitor of a Ceph storage cluster and a message middleware RabbitMQ, and is in charge of receiving lesson (virtual machine creation and deletion) requests of the experiment management node unit on one hand; on the other hand, the cooperative interaction among the computing nodes, the mirror nodes and the storage nodes is controlled and managed;
the mirror image node unit is deployed in the angle-api, angle-registration and python-rbd services and is used for providing access services of the system mirror image, including the uploading, downloading and deleting operations of the mirror image; the integration process of the mirror node and the Ceph needs to copy the Ceph. conf file to the/etc directory of the mirror node, and modify the Value of default _ store and rbd _ store _ pool options in the gland-api. conf file into: default _ store ═ rbd, rbd _ store _ pool ═ images;
the computing node unit is used for deploying Nova computing services Nova-computer and Neutron bridge proxy services Neutron-plugin-linux-agent and ceph-common in Nova computing services and Neutron, and is used for managing the life cycle of the virtual machine in the cloud platform; the integration process of the computing node and the Ceph needs to copy the Ceph. conf file to the/etc directory of the computing node, and modify the values of images _ type, images _ rbd _ pool and disk _ cachemode options in the nova. conf file into: image _ type ═ rb, image _ rb _ pool ═ instances, disk _ cachemode ═ network ═ writeback,;
the cloud hard disk node unit is used for deploying the inside of the ring-api, the ring-volume, the ring-scheduler and the cpeh-common and is used for being responsible for creating and deleting the cloud hard disk; the integration process of the cloud hard disk node and the Ceph needs to copy a Ceph. conf file to a/etc directory of the cloud hard disk node, and enable _ backups, volume _ driver and rbd _ pool options in the c/conf file are modified into: enabled _ backings _ rbd, volume _ driver _ volume _ driver _ rbd rbddriver, rbd _ pool _ volumes;
and the storage node unit is used for deploying the Ceph OSD, and providing block storage services for the company, Nova and circle components of the OpenStack by creating three block storage pools of images, instances and volumes through the RBD client.
As a preferred technical solution, the experiment management node unit uses OpenStack4j to call a computing and storage interface of a cloud platform control node to perform course management;
the experimental management node unit establishes a thread pool to perform concurrent scheduling on batch creation and deletion requests of the virtual machines involved in the course of going to and going from classes, and the number of active threads in the thread pool is consistent with the concurrent processing scale set by OpenStack.
As an optimized technical scheme, the mirror image node unit, the computing node unit, the cloud hard disk node unit and the storage node unit are communicated through a 10Gbps optical fiber network interface.
More preferably, the maximum clonable level RBD _ max _ clone _ depth parameter is set to 5 when a snapshot operation is performed based on the Cinder call Ceph RBD.
Compared with the prior art, the invention has the advantages that:
(1) the cloud hard disk snapshot is used as an experiment template, so that decoupling of computing resources and storage resources (cloud hard disks) of the virtual machine is realized, dynamic updating in an innovative course experiment process is met, and transmission of virtual machine mirror images between the computing nodes and the storage nodes is avoided;
(2) the cloud hard disk snapshot is realized based on a clone technology of copy-on-write, and an incremental file is created only when a virtual machine executes write operation to the cloud hard disk, so that the storage efficiency of a cloud platform is improved;
(3) once the innovative course finishes the first class-taking operation, each student has an associated bootable cloud hard disk to be stored in a storage node, and a virtual machine is created directly based on the existing bootable cloud hard disk of the student in the next class-taking operation, so that the starting speed of the virtual machine is effectively increased.
Drawings
FIG. 1 is a flow chart of the inventive course experiment automatic management method of the present invention;
FIG. 2 is a block diagram of the architecture of the inventive automatic course experiment management system of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, not all, embodiments of the present invention. All other embodiments, which can be obtained by a person skilled in the art without any inventive step based on the embodiments of the present invention, shall fall within the scope of protection of the present invention.
Example 1
As shown in fig. 1, in the method for automatically managing the innovative experimental course based on the OpenStack, firstly, an RBD client of a Ceph cluster is used as a uniform storage back end of Glance, Nova and finder components in the OpenStack, then a RAW format mirror image required by the experimental course is uploaded, then the uploaded mirror image is made into a cloud hard disk, finally the cloud hard disk is made into a snapshot, and the cloud hard disk snapshot is used as an innovative course experimental template to perform course experimental management on students; the method comprises the following specific steps:
s1, calling an OpenStack mirror image service interface (create image-create) to upload a RAW format basic mirror image required by a course experiment;
s2, calling an OpenStack block storage service interface circuit create the uploaded basic image into a bootable cloud hard disk;
s3, calling a circumferentially snapshot-create of an OpenStack block storage service interface to make a cloud hard disk into a cloud hard disk snapshot, and storing snapshot information in a snapshot table of a service database;
s4, establishing a mapping relation between the cloud hard disk snapshot ID and the innovative course ID, and storing the mapping relation in a course _ snapshot table of a business layer database;
s5, the laboratory manager or teacher executes the lesson-taking operation to the lesson through the lesson-taking interface provided by the experiment management node unit, if the operation is the first lesson-taking of the innovative lesson, the system executes the following steps:
1) based on the cloud hard disk snapshot associated with the course in the business layer database core _ snapshot table, calling a circle volume create command to create a corresponding cloud hard disk for each student, and storing the mapping relation between the ID of the student and the ID of the cloud hard disk in the business layer database user _ volume table;
2) calling an openstack server create command to bind a virtual machine to each cloud hard disk of the student based on the cloud hard disk ID associated with each student ID in the user _ volume, and storing the mapping relation between the student ID and the virtual machine ID in a user _ instance table of a service layer database;
if the innovative course is not a first course, directly calling an openstack server create command to create a corresponding virtual machine for the student based on the cloud hard disk ID associated with each student ID in the service layer database, and storing the mapping relation between the student ID and the virtual machine ID in the service layer database;
s6, the laboratory teacher or the administrator executes the course setting operation through the course setting interface provided by the experiment management node unit, and according to the mapping relation between the student ID and the virtual machine ID in the user _ instance table of the business layer database, the openstack server delete command is called to delete the virtual machine corresponding to each student, but the cloud hard disk mounted by the virtual machine is reserved;
the invention allows the system to flexibly change the experiment template between two experiment courses; when the experiment template is replaced, the system needs to delete the existing cloud hard disks of all students under the course, and updates the mapping relation between the course and the new experiment template in the business database; after the template is replaced, the processing flow of the next lesson of the system is consistent with the lesson starting operation of the lesson for the first time.
Example 2
As shown in fig. 2, the inventive experimental course management system based on OpenStack of the present invention includes:
the experiment management node unit is used for deploying a service layer application program and a corresponding database, providing course-centered on-off management service, and performing procedural management and control on experimenters, experiment templates, experiment hosts and experiment resources related to innovative experiment courses;
the cloud platform control node unit is used for deploying control services of Keystone and Neutron of OpenStack and Nova components, a Monitor of a Ceph storage cluster and a message middleware RabbitMQ, and is in charge of receiving lesson and class (virtual machine creation and deletion) requests of the experiment management node unit on one hand; on the other hand, the cooperative interaction among the computing nodes, the mirror nodes and the storage nodes is controlled and managed;
the mirror image node unit is used for deploying the work-api, the work-registration and the python-rbd services and is mainly responsible for providing access services of the system mirror image, including the uploading, downloading and deleting operations of the mirror image; the integration process of the mirror node and the Ceph needs to copy the Ceph. conf file to the/etc directory of the mirror node, and modify the Value of default _ store and rbd _ store _ pool options in the gland-api. conf file into: default _ store ═ rbd, rbd _ store _ pool ═ images;
the computing node unit is used for deploying Nova computing services Nova-computer and Neutron bridge proxy services Neutron-plug-linux-agent and ceph-common of Neutron by the computing node and is mainly responsible for managing the life cycle of the virtual machine in the cloud platform; the integration process of the computing node and the Ceph needs to copy the Ceph. conf file to the/etc directory of the computing node, and modify the values of images _ type, images _ rbd _ pool and disk _ cachemode options in the nova. conf file into: image _ type ═ rb, image _ rb _ pool ═ instances, disk _ cachemode ═ network ═ writeback,;
the cloud hard disk node unit is used for deploying a circle-api, a circle-volume, a circle-scheduler and a cpeh-common and is mainly responsible for creating and deleting the cloud hard disk; the integration process of the cloud hard disk node and the Ceph needs to copy a Ceph. conf file to a/etc directory of the cloud hard disk node, and enable _ backups, volume _ driver and rbd _ pool options in the c/conf file are modified into: enabled _ backings _ rbd, volume _ driver _ volume _ driver _ rbd rbddriver, rbd _ pool _ volumes;
the storage node unit is used for deploying Ceph OSD and providing block storage service for the Glance, Nova and circle components of OpenStack by creating three block storage pools of images, instances and volumes through the RBD client; the storage node is connected with the mirror image node, the computing node and the cloud hard disk node through 10Gbps optical fiber network ports.
While the invention has been described with reference to specific embodiments, the invention is not limited thereto, and various equivalent modifications and substitutions can be easily made by those skilled in the art within the technical scope of the invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. An innovative course experiment automatic management method based on cloud computing is characterized in that an RBD client of a Ceph cluster is used as a storage back end of a Glance component, a Nova component and a Cinder component in OpenStack, and cloud hard disk snapshots are used as course experiment templates to automatically manage course experiments of students, wherein the cloud hard disk snapshots are specifically generated as follows: the method comprises the steps of uploading RAW format mirror images required by experimental courses, manufacturing the mirror images into cloud hard disks, and finally manufacturing snapshots for the cloud hard disks.
2. The innovative course experiment automatic management method based on cloud computing as claimed in claim 1, characterized by comprising the following specific steps:
s1, calling an OpenStack mirror image service interface Glance-api to upload a RAW format basic mirror image according to the course experiment requirements;
s2, calling an OpenStack block storage service interface (render-api) to make the uploaded basic mirror image into a cloud hard disk;
s3, calling an OpenStack block storage service interface (render-api) to make a cloud hard disk into a cloud hard disk snapshot;
s4, storing a mapping relation table of cloud hard disk snapshot IDs and innovative course IDs in a business layer database;
s5, executing lesson taking operation, judging whether the innovative course is the first lesson taking, if so, executing the following steps:
s51) based on the cloud hard disk snapshot associated with the course in the business layer database, calling a circle-api service to create a corresponding cloud hard disk for each student, and storing the mapping relation between the ID of the student and the ID of the cloud hard disk in the business layer database;
s52) based on the cloud hard disk ID associated with each student ID in the business layer database, calling a Nova-api interface to create a corresponding virtual machine for the student, and storing the mapping relation between the student ID and the virtual machine ID in the business layer database;
if the innovative course is not a first class, based on the cloud hard disk ID associated with each student ID in the business layer database, invoking a Nova-api service to create a corresponding virtual machine for the student, and storing the mapping relation between the student ID and the virtual machine ID in the business layer database;
and S6, executing the course leaving operation, and calling Nova-api service to delete the virtual machine corresponding to each student according to the mapping relation between the student ID and the virtual machine ID in the service layer database.
3. The method as claimed in claim 2, wherein the cloud hard disk snapshot in step S3 is created based on rbd copy-on-write technology, and protected based on rbd snap protect.
4. The method for automatically managing innovative course experiments based on cloud computing as claimed in claim 2, wherein the mapping relationship table of cloud hard disk snapshot IDs and innovative course IDs in step S4 includes five key fields of CourseID, snapshot ID, InstanceName, flavonid and OrderID; the InstanceName and the FlavorID fields respectively designate a name and resource configuration for the virtual machine created based on the snapshot Snapshot ID; the OrderID field is provided to address the distributed cluster experiment environment requirements of the innovative course and indicates the sequence number of the current snapshot in all snapshots associated with the course.
5. The method as claimed in claim 2, wherein the step S5 of associating the course with the student comprises: one is to automatically import student information through a connected educational administration system, and the other is to manually import and establish association with a course after storing the student information in an Excel table for a temporarily created course.
6. The method as claimed in claim 2, wherein after the lesson-taking operation in step S5 is completed, the user logs in a Web browser of the virtual machine based on Guacamole, wherein the Windows operating system is connected by RDP protocol, the Linux operating system is connected by SSH protocol, and different experimental hosts in the distributed cluster are flexibly switched by Tab tags of the browser.
7. The cloud computing-based innovative course experiment automatic management method as claimed in claim 2, characterized in that the method allows the system to flexibly change the experiment template between two experimental courses; when the experiment template is replaced, the system needs to delete the existing cloud hard disks of all students under the course, and updates the mapping relation between the course and the new experiment template in the business database; after the template is replaced, the processing flow of the next lesson of the system is consistent with the lesson starting operation of the lesson for the first time.
8. A system for the cloud computing-based innovative course experiment automatic management method of claim 1, characterized in that it comprises:
the experiment management node unit is deployed in a service layer application program and a corresponding database, provides course-centered on-off management service, and is used for performing process management and control on experimenters, experiment templates, experiment hosts and experiment resources related to innovative experiment courses;
the cloud platform control node unit is deployed in control services of Keystone and Neutron of OpenStack and Nova components, a Monitor of a Ceph storage cluster and a message middleware RabbitMQ, and is in charge of receiving a class-leaving request of the experiment management node unit on one hand; on the other hand, the cooperative interaction among the computing nodes, the mirror nodes and the storage nodes is controlled and managed;
the mirror image node unit is deployed in the angle-api, angle-registration and python-rbd services and is used for providing access services of the system mirror image, including the uploading, downloading and deleting operations of the mirror image; the integration process of the mirror node and the Ceph needs to copy the Ceph. conf file to the/etc directory of the mirror node, and modify the Value of default _ store and rbd _ store _ pool options in the gland-api. conf file into: default _ store ═ rbd, rbd _ store _ pool ═ images;
the computing node unit is used for deploying Nova computing services Nova-computer and Neutron bridge proxy services Neutron-plugin-linux-agent and ceph-common in Nova computing services and Neutron, and is used for managing the life cycle of the virtual machine in the cloud platform; the integration process of the computing node and the Ceph needs to copy the Ceph. conf file to the/etc directory of the computing node, and modify the values of images _ type, images _ rbd _ pool and disk _ cachemode options in the nova. conf file into: image _ type ═ rb, image _ rb _ pool ═ instances, disk _ cachemode ═ network ═ writeback,;
the cloud hard disk node unit is used for deploying the inside of the ring-api, the ring-volume, the ring-scheduler and the cpeh-common and is used for being responsible for creating and deleting the cloud hard disk; the integration process of the cloud hard disk node and the Ceph needs to copy a Ceph. conf file to a/etc directory of the cloud hard disk node, and enable _ backups, volume _ driver and rbd _ pool options in the c/conf file are modified into: enabled _ backings _ rbd, volume _ driver _ volume _ driver _ rbd rbddriver, rbd _ pool _ volumes;
and the storage node unit is used for deploying the Ceph OSD, and providing block storage services for the company, Nova and circle components of the OpenStack by creating three block storage pools of images, instances and volumes through the RBD client.
9. The system of claim 8, wherein the experiment management node unit uses OpenStack4j to invoke a computing and storage interface of a cloud platform control node for class attendance process management;
the experimental management node unit establishes a thread pool to perform concurrent scheduling on batch creation and deletion requests of the virtual machines involved in the course of going to and going from classes, and the number of active threads in the thread pool is consistent with the concurrent processing scale set by OpenStack.
10. The system according to claim 8, wherein the mirror node unit, the computing node unit, the cloud disk node unit and the storage node unit are communicated with each other through a 10Gbps optical fiber network interface.
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| CN113467890A (en) * | 2021-07-05 | 2021-10-01 | 信阳农林学院 | Distributed virtual college laboratory management method, system and storage device |
| CN113504903A (en) * | 2021-07-06 | 2021-10-15 | 上海商汤智能科技有限公司 | Experiment generation method and device, electronic equipment and storage medium |
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