CN114327484A - Multi-architecture supporting K8S integration and deployment method, system and storage medium - Google Patents
Multi-architecture supporting K8S integration and deployment method, system and storage medium Download PDFInfo
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Abstract
The application relates to a K8S integration and deployment method, system and storage medium supporting multiple architectures, wherein the method comprises the following steps: performing cross compilation on codes stored in a code warehouse in advance, and storing cross compilation results to a Kubernetes mirror image and a software warehouse; and the dispatching center issues the received deployment instruction to a remote deployment system, the remote deployment system performs environment verification on the target cluster, compares the environment verification result with the expected environment of the target cluster corresponding to the deployment instruction, and completes the cluster deployment service according to the comparison result. According to the scheme, the purposes of automatic integration and deployment can be achieved in a multi-architecture service node mode through a unified standard process.
Description
Technical Field
The application relates to a method, a system and a storage medium for supporting multi-architecture K8S integration and deployment, and belongs to the technical field of cloud computing.
Background
In today's cloud computing environment, containers are the foundation of modern facilities, greatly improve service granularity, optimize application architecture, and standardize service runtime of development and production environments, but at the same time increase complexity of deployment management, bringing integration and deployment challenges. K8S provides a standard and environmentally portable way to describe, manage and run a complete system, now becoming an industry standard and ultimate fact for container deployment.
However, with the rapid development of CPUs with different architectures and the continuous expansion of the scale of the K8S cluster, the traditional architecture mode has increasingly prominent limitations facing the automated integration and deployment of multi-architecture service nodes, and lacks balance between agile development and continuous integration deployment. Many enterprises with K8S are gradually faced with too many isolated, individually managed K8S deployed systems, resulting in significant inefficiency and complexity, and greater burdens that make security compliance extremely difficult to manage.
One of the pain points of enterprises today is how to implement automated integration and deployment in a multi-architecture service node mode with a unified flow.
Disclosure of Invention
The application provides a multi-architecture supporting K8S integration and deployment system, a method and a storage medium, so as to achieve the purpose of realizing automatic integration and deployment by a unified flow under a multi-architecture service node mode.
In order to solve the technical problem, the application provides the following technical scheme:
in a first aspect, a method for supporting multi-architecture K8S integration and deployment is provided according to an embodiment of the present application, including:
performing cross compilation on codes stored in a code warehouse in advance, and storing cross compilation results to a Kubernetes mirror image and a software warehouse;
and the dispatching center issues the received deployment instruction to a remote deployment system, the remote deployment system performs environment verification on the target cluster, compares the environment verification result with the expected environment of the target cluster corresponding to the deployment instruction, and completes the cluster deployment service according to the comparison result.
In one embodiment, the result of the environment check includes: whether the service exists, the version of the service and the corresponding configuration information of the service are consistent; the configuration information of the service comprises software and hardware corresponding to the service, the type of the architecture node, the number of virtual machines on the node and the mounted storage of the virtual machines.
In one embodiment, the completing the cluster deployment service according to the comparison result includes:
when the comparison result shows that the expected environment is different from the current environment, the following steps are executed:
feeding the comparison result back to the dispatching center;
after the remote deployment system receives the operation instruction which is sent by the dispatching center and needs to be deployed or not, if the deployment instruction needs to be executed continuously, the remote deployment system pulls the dependency related to the target expected environment corresponding to the deployment instruction from the K8s mirror image software warehouse.
In one embodiment, before the cross-compiling the code stored in the code warehouse in advance, the method further includes:
and the dispatching center sends the received codes to a code inspection system for inspection, and incorporates the codes meeting the inspection conditions into a K8S code warehouse.
In a second aspect, a K8S integration and deployment system supporting multiple architectures is provided according to an embodiment of the present application, including:
the cross compiling module is used for carrying out cross compiling on the codes stored in the code warehouse in advance to form a cross compiling result;
the Kubernetes mirror image and the software warehouse are used for storing a cross compiling result formed by cross compiling of the cross compiling module;
the dispatching center receives the deployment instruction and issues the deployment instruction to the remote deployment system;
and the remote deployment system carries out environment verification on the target cluster after receiving the deployment instruction, compares an environment verification result with the expected environment of the target cluster corresponding to the deployment instruction, and completes the cluster deployment service according to the comparison result.
In one embodiment, the verification result obtained by the remote deployment system performing the environmental verification on the target cluster includes: whether the service exists, the version of the service and the corresponding configuration information of the service are consistent; the configuration information of the service comprises software and hardware corresponding to the service, the type of the architecture node, the number of virtual machines on the node and the mounted storage of the virtual machines.
In one embodiment, when the comparison result indicates that there is a difference between the expected state and the current state, the remote deployment system performs operations including:
feeding the comparison result back to the dispatching center;
after the remote deployment system receives an operation instruction which is issued by the dispatching center and needs to be deployed or not, if the type of the operation instruction is 'the deployment instruction needs to be executed', the remote deployment system pulls the dependency related to the target expected environment corresponding to the deployment instruction from the K8s mirror image software warehouse.
In one embodiment, the multi-architecture supporting K8S integration and deployment system further includes:
and the code examination system is used for examining the codes received by the dispatching center and integrating the codes meeting the examination conditions into the K8S code warehouse.
In a third aspect, according to an embodiment of the present application, there is provided a system for supporting multi-architecture K8S integration and deployment, where the system includes a processor, a memory, and a computer program stored in the memory and executable on the processor, and the computer program is loaded and executed by the processor, so as to implement any one of the above-mentioned multi-architecture supporting kubernets integration and deployment methods.
In a fourth aspect, according to an embodiment of the present application, there is provided a computer-readable storage medium storing a computer program, where the computer program is configured to, when executed by a processor, implement any one of the foregoing kubernets integration and deployment method supporting multiple architectures.
The beneficial effect of this application lies in:
according to the Kubernets integration and deployment system, the Kubernets integration and deployment method, the Kubernets integration and deployment system and the storage medium supporting multiple architectures, codes of target version target software can be cross-compiled through cross-compiling, so that a mirror image file applicable to multiple types of architecture nodes is formed, the technical problem that enterprises with Kubernets face too many independent and separately managed Kubernets deployment systems in the prior art is effectively solved, and the purpose of automatic integration and deployment can be achieved through a unified standard process in a mode of multiple architecture service nodes.
The foregoing description is only an overview of the technical solutions of the present application, and in order to make the technical solutions of the present application more clear and clear, and to implement the technical solutions according to the content of the description, the following detailed description is made with reference to the preferred embodiments of the present application and the accompanying drawings.
Drawings
Fig. 1 is a schematic application scenario diagram of a kubernets integration and deployment method and system supporting multiple architectures according to an embodiment of the present application;
fig. 2 is a flowchart of a kubernets integration and deployment method supporting multiple architectures according to an embodiment of the present application;
fig. 3 is a flowchart of a kubernets integration and deployment method supporting multiple architectures according to another embodiment of the present application;
fig. 4 is a flowchart of a kubernets integration and deployment method supporting multiple architectures according to yet another embodiment of the present application;
fig. 5 is a schematic diagram of a kubernets integration and deployment system supporting multiple architectures according to an embodiment of the present application;
fig. 6 is a schematic diagram of a kubernets integration and deployment apparatus supporting multiple architectures according to an embodiment of the application.
Detailed Description
The following examples are intended to illustrate the present application but are not intended to limit the scope of the present application.
The embodiment of the application provides a Kubernetes (K8S for short) integration and deployment method supporting multiple architectures, which is applied to a scene that Kubernetes (K8S for short) is integrated and deployed after a deployment instruction is received by a dispatching center shown in FIG. 1, various types of architecture nodes, such as x86 architecture nodes, arm architecture nodes or other types of architecture nodes, are stored in a cluster, and after a remote deployment system receives the dispatching instruction issued by the dispatching center, a comparison result is compared with a target cluster expected environment corresponding to the deployment instruction, and if the comparison result is inconsistent, the comparison result is fed back to the dispatching center; and after the remote deployment system receives the operation instruction which is sent by the dispatching center and needs to be deployed or not, if the remote deployment system determines that the deployment instruction needs to be continuously executed, the remote deployment system pulls the dependency related to the target expected environment corresponding to the deployment instruction from the K8s mirror image software warehouse. Specifically, referring to fig. 2, the Kubernetes (K8S for short) integration and deployment method supporting multiple architectures includes:
step S12, cross compiling the codes stored in the code warehouse in advance, and storing the cross compiling result to the Kubernetes mirror image and the software warehouse;
in the embodiment of the application, after the user passes the test qualification of the code which is developed and written at this time, the code which passes the test qualification is submitted to the scheduling center, the scheduling center submits the code of the target version which is submitted by the user to the code examination system, the code examination system examines the code which is submitted by the user, and after the examination qualification, the code which is uploaded at this time by the user is merged into the Kubernetes code warehouse.
After the codes uploaded by the user at this time are incorporated into the code warehouse, the cross compiling system can acquire the stored codes from the Kubernetes code warehouse, cross compile the acquired codes, and store the cross compiling results in the Kubernetes mirror image and the software warehouse. The result compiled in the invention can be stored in the Kubernetes mirror image and software warehouse in the forms of binary system, mirror image file, installation package, configuration file, running script, etc.
And step S14, the dispatching center issues the received deployment instruction to the remote deployment system, the remote deployment system performs environment verification on the target cluster, compares the environment verification result with the target cluster expected environment corresponding to the deployment instruction, and completes the cluster deployment service according to the comparison result.
In the embodiment of the application, after receiving a deployment instruction issued by a cluster deployment terminal, a scheduling center issues the received deployment instruction to a remote deployment system, so that the remote deployment system can implement cluster deployment. However, before cluster deployment, the remote deployment system firstly performs an environment checking process, specifically, checks whether the cluster environment is the same as an expected environment corresponding to the deployment instruction, and deploys the cluster according to the cluster deployment instruction if the cluster environment is the same as the expected environment corresponding to the deployment instruction. And if not, the subsequent operation will be performed.
In this embodiment of the present application, the result of the environment verification includes: whether the service exists, the version of the service and the corresponding configuration information of the service are consistent; the configuration information of the service comprises software and hardware corresponding to the service, the type of the architecture node, the number of virtual machines on the node and the mounted storage of the virtual machines.
That is to say, in the embodiment of the present application, the checking of the environment includes checking whether a service exists, and in the presence of the service, the version of the service is continuously checked, whether the configuration information corresponding to the service is consistent, and the configuration information of the service includes a software and hardware environment corresponding to the service, a type of a fabric node, a number of virtual machines on the node, and storage mounted by the virtual machines. In the present application, the types of fabric nodes deployed in the cluster may include X86 fabric nodes, arm fabric nodes, and other types of fabric nodes. Certainly, in other embodiments, in the environment checking process, there is no fixed precedence order in the order of whether the service to be checked exists, the version of the service, and whether the configuration information corresponding to the service is consistent, and similarly, there is no fixed precedence order in the checking of the configuration information corresponding to the service, such as the software and hardware environment corresponding to the service, the type of the architecture node, the number of virtual machines on the node, and the storage of the virtual machine mount.
In the embodiment of the application, deployment is not single-finger installation, and the remote control system can also comprise a remote control system integrating multiple automatic functions of installation, reset, upgrading and downgrading, scaling, fault detection, abnormal repair, dynamic update and the like for services, and the operation of class declaration is reasonably made according to the expected state and the current state.
In the embodiment of the application, the remote deployment system provides a working node of an automatic deployment suite, and the suite has the functions of automatic remote deployment and cluster cleaning, real-time synchronous deployment of states, abnormal retry, fault self-healing and the like.
In this embodiment of the present application, the instruction of the scheduling unit may include declaration types such as code submission and integrated deployment, and a specific interaction manner may be implemented by a grpc communication protocol, where it is noted that, as for whether the instruction of the scheduling unit is a code submission type or an integrated deployment type, a specific instruction type may be determined by a predefined identifier.
In the embodiment of the present application, referring to fig. 3, the completing the cluster deployment service according to the comparison result includes:
when the comparison result shows that the expected environment is different from the current environment, the following steps are executed:
1) feeding the comparison result back to the dispatching center;
2) after the remote deployment system receives an operation instruction which is issued by the dispatching center and needs to be deployed or not, if the deployment instruction needs to be executed, the remote deployment system pulls the dependency related to the target expected environment corresponding to the deployment instruction from the K8s mirror image and the software warehouse. In the embodiment of the application, when the comparison result is that the expected state and the current state are different, the remote deployment system feeds back the comparison result to the scheduling center so that the scheduling center can further decide whether to continue scheduling. And if the dispatching center receives the comparison result, the dispatching center needs to send an operation instruction for judging whether the deployment is needed to be carried out to the remote deployment system again.
If the remote deployment system determines that deployment still needs to be executed after receiving an operation instruction issued by the dispatching center, and the target environment based on the difference between the target environment and the target cluster expected environment corresponding to the deployment instruction, the dependency related to the target environment corresponding to the deployment instruction is pulled from the K8s mirror image software warehouse, wherein the related dependency comprises information such as binary system, mirror image file, installation package, configuration file, operation script and the like generated after the cross compiling of the codes by the cross compiling system. It can be understood that, in this embodiment, after the cross compiling system cross compiles the code, the generated cross compiling result may include information such as binary, image file, installation package, configuration file, and running script, and the information may be used as a dependency related to a target environment corresponding to the deployment instruction, and after the remote deployment system pulls the related dependency from the K8s image software warehouse, the system may automatically complete the deployment of the target cluster according to the dependency information.
In this embodiment of the present application, referring to fig. 4, before the cross-compiling the code stored in the code repository in advance in step S12, the method further includes:
and step S11, the dispatching center sends the received codes to a code examination system for examination, and codes meeting examination conditions are merged into a K8S code warehouse.
In the embodiment of the application, before the cross compiling system performs cross compiling on the codes, the scheduling center needs to send the received codes to the code examination system for examination, and after the examination is passed, the examined codes are stored in the kubernets code warehouse for scheduling to the cross compiling system for cross compiling.
In the embodiment of the application, the code examining unit mainly examines the security, the compliance and the conventional performance of the code, and avoids the situations such as plaintext password, illegal operation, memory leakage and the like. The cross-compiling unit compiles the code into all types of architecture versions on a unified platform (such as x86) according to the expectation of the user. The remote deployment unit is remotely connected to a target cluster of a system which is provided with a Kubernet supporting multiple Kubernet architectures and integrates and deploys the Kubernet architectures, or carries out communication on a deployment component of a target node end, so that the deployment process and the delivery work of a deployment target are realized, and the deployment of the required service on the target node is realized.
According to the Kubernets integration and deployment method supporting multiple architectures, codes stored in a code warehouse are subjected to cross compiling in advance, and cross compiling results are stored in a Kubernets mirror image and a software warehouse; and the dispatching center issues the received deployment instruction to a remote deployment system, the remote deployment system performs environment verification on the target cluster, compares the environment verification result with the expected environment of the target cluster corresponding to the deployment instruction, and completes the cluster deployment service according to the comparison result. Therefore, after receiving the software codes of the target software of the target version, the cross compiling system carries out cross compiling on the software codes, and stores the cross compiling results in a Kubernetes mirror image and a software warehouse in a binary form. Therefore, the scheme effectively solves the problems that in the prior art, enterprises with Kubernets gradually face too many independent and separately managed Kubernets deployment systems, serious low efficiency and complexity are caused, greater burden is brought, and safety compliance is extremely difficult to control.
As follows, a specific example is illustrated:
by adopting the system of the embodiment of the application, the cross compiling module can compile an executable file of arm64 in an x86 environment, and this scenario is often caused by environment differences under different architectures and incompleteness of a compiling tool, for example, when the compiling tool of a customized arm environment is missing or has an excessively large version difference, the arm executable file can be cross compiled in an x86 environment, so that the compiling problem caused by the environment difference is shielded.
In addition, for some embedded scenes, the embedded scenes cannot be compiled, and only cross-compilation can be realized.
An embodiment of the present application further provides a K8S integration and deployment system supporting multiple architectures, as shown in fig. 5, the system includes:
a cross compiling module 51, configured to perform cross compiling on codes stored in the code warehouse in advance to form a cross compiling result;
a Kubernetes mirror image and software warehouse 52 for storing the cross compiling result formed by cross compiling of the cross compiling module;
the dispatching center 53 receives the deployment instruction and issues the deployment instruction to the remote deployment system;
and the remote deployment system 54, after receiving the deployment instruction, performs environment verification on the target cluster, compares an environment verification result with the target cluster expected environment corresponding to the deployment instruction, and completes cluster deployment service according to the comparison result.
A K8s code repository 55 for storing codes;
in an embodiment of the present application, a verification result obtained by performing an environmental verification on a target cluster by a remote deployment system includes: whether the service exists, the version of the service and the corresponding configuration information of the service are consistent; the configuration information of the service comprises software and hardware corresponding to the service, the type of the architecture node, the number of virtual machines on the node and the mounted storage of the virtual machines.
In an embodiment of the present application, when the comparison result of the remote deployment system indicates that there is a difference between the expected environment and the current environment, the operations performed by the remote deployment system include:
feeding the comparison result back to the dispatching center;
after the remote deployment system receives the operation instruction which is sent by the dispatching center and needs to be deployed or not, if the deployment instruction needs to be executed continuously, the remote deployment system pulls the dependency related to the target expected environment corresponding to the deployment instruction from the K8s mirror image software warehouse.
In an embodiment of the present application, the provided multi-architecture supporting K8S integration and deployment system further includes:
and the code examination system is used for examining the codes received by the dispatching center and integrating the codes meeting the examination conditions into the K8s code warehouse.
In this embodiment of the present application, in the embodiment of the present application, deployment may be started according to a deployment instruction, that is, when a deployment instruction is received and it is continuously determined whether a target architecture node corresponding to target software of a target version is stored in a kubernets cluster, if yes, deployment of the target software of the target version is implemented. The remote deployment is realized by remotely connecting to a target machine of a system which is provided with Kubernets supporting multi-architecture Kubernets and integrates and deploys, or communicating with a deployment component at a target node end, so that the deployment process and the delivery work of a deployment target are realized, and the deployment of the required service on the target node is realized.
According to the Kubernetes integration and deployment system supporting multiple architectures, a cross compiling system carries out cross compiling on codes stored in a code warehouse in advance, and cross compiling results are stored in a Kubernetes mirror image and a software warehouse; and the dispatching center issues the received deployment instruction to a remote deployment system, the remote deployment system performs environment verification on the target cluster, compares the environment verification result with the expected environment of the target cluster corresponding to the deployment instruction, and completes the cluster deployment service according to the comparison result. Therefore, the cross compiling system can cross compile the software codes of the target software of the target version, and store the cross compiling results in the Kubernetes mirror image and the software warehouse in a binary form, and based on the cross compiling of the software codes, the compiling results can adapt to a plurality of versions, and each compiling result can be suitable for the target structure nodes of the corresponding type, thereby realizing the deployment on the target structure nodes of a plurality of types. Therefore, the scheme effectively solves the problems that in the prior art, enterprises with Kubernets gradually face too many independent and separately managed Kubernets deployment systems, serious low efficiency and complexity are caused, greater burden is brought, and safety compliance is extremely difficult to control.
Fig. 6 is a block diagram of a system supporting multi-architecture kubernets integration and deployment according to an embodiment of the present disclosure, where the system supporting multi-architecture kubernets integration and deployment may be a desktop computer, a notebook computer, a palm computer, a cloud server, and other computing devices, and the system may include, but is not limited to, a processor and a memory. The system for integrating and deploying kubernets supporting multiple architectures in this embodiment at least includes a processor and a memory, where the memory stores a computer program, the computer program is executable on the processor, and when the processor executes the computer program, the steps in the above-described embodiment of the image retrieval method are implemented, for example, the steps in the kubernets integrating and deploying supporting multiple architectures shown in any one of fig. 2 to 4. Or, when the processor executes the computer program, the functions of the modules in the system embodiment supporting the multi-architecture kubernets integration and deployment are realized.
Illustratively, the computer program may be partitioned into one or more modules that are stored in the memory and executed by the processor to implement the invention. The one or more modules may be a series of computer program instruction segments capable of performing certain functions, which are used to describe the execution of the computer program in the system supporting the multi-architecture kubernets integration and deployment. For example, the computer program may be partitioned into cross-compilation modules, kubernets mirror and software repositories, a dispatch center, and a remote deployment system, where the specific functions of each module are as follows:
the cross compiling module is used for carrying out cross compiling on the codes stored in the code warehouse in advance to form a cross compiling result;
the Kubernetes mirror image and the software warehouse are used for storing a cross compiling result formed by cross compiling of the cross compiling module;
the dispatching center receives the deployment instruction and issues the deployment instruction to the remote deployment system;
and the remote deployment system carries out environment verification on the target cluster after receiving the deployment instruction, compares an environment verification result with the expected environment of the target cluster corresponding to the deployment instruction, and completes the cluster deployment service according to the comparison result.
The processor may include one or more processing cores, such as: 4 core processors, 6 core processors, etc. The processor may be implemented in at least one hardware form of a DSP (Digital Signal Processing), an FPGA (Field-Programmable Gate Array), and a PLA (Programmable Logic Array). The processor 601 may also include a main processor and a coprocessor, where the main processor is a processor for Processing data in an awake state, and is also called a Central Processing Unit (CPU); the central processing unit is a low power consumption processor for processing data in a standby state. In some embodiments, processor 601 may also include an AI (Artificial Intelligence) processor for processing computational operations related to machine learning. The processor is a control center of the multi-architecture supporting Kubernets integrated and deployed system, and various interfaces and lines are used for connecting all parts of the whole multi-architecture supporting Kubernets integrated and deployed system.
The memory may be used to store the computer programs and/or modules, and the processor may implement the various functions of the image inspection system by running or executing the computer programs and/or modules stored in the memory, as well as by invoking data stored in the memory. The memory may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required by at least one function (such as a sound playing function, an image playing function), and the like; the storage data area may store data (such as audio data, a phonebook, etc.) created according to the use of the cellular phone, and the like. In addition, the memory may include high speed random access memory, and may also include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), at least one magnetic disk storage device, a memory device, or other volatile solid state storage device.
Those skilled in the art will appreciate that the system described in this embodiment is merely an example of a system supporting multi-architecture kubernets integration and deployment, and does not constitute a limitation of the system supporting multi-architecture kubernets integration and deployment, and in other embodiments, more or fewer components may be included, or certain components may be combined, or different components may be included, for example, the system supporting multi-architecture kubernets integration and deployment may further include an input and output device, a network access device, a bus, and the like. The processor, memory and peripheral interface may be connected by bus or signal lines. Each peripheral may be connected to the peripheral interface via a bus, signal line, or circuit board. Illustratively, peripheral devices include, but are not limited to: radio frequency circuit, touch display screen, audio circuit, power supply, etc.
Of course, the system supporting the kubernets integration and deployment of multiple architectures may also include fewer or more components, which is not limited by the embodiment.
Optionally, the present application further provides a computer-readable storage medium storing a computer program, which when executed by a processor is configured to implement the steps of the kubernets integration and deployment method supporting multiple architectures described above.
Optionally, the present application further provides a computer product, which includes a computer-readable storage medium, where a program is stored in the computer-readable storage medium, and the program is loaded and executed by a processor to implement the steps of the foregoing kubernets integration and deployment method embodiment supporting multiple architectures.
The technical features of the embodiments described above may be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the embodiments described above are not described, but should be considered as being within the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. A K8S integration and deployment method supporting multiple architectures, comprising:
performing cross compilation on codes stored in a code warehouse in advance, and storing cross compilation results to a Kubernetes mirror image and a software warehouse;
and the dispatching center issues the received deployment instruction to a remote deployment system, the remote deployment system performs environment verification on the target cluster, compares the environment verification result with the expected environment of the target cluster corresponding to the deployment instruction, and completes the cluster deployment service according to the comparison result.
2. The multi-architecture supported K8S integration and deployment method of claim 1, wherein: the result of the environment check includes: whether the service exists, the version of the service and the corresponding configuration information of the service are consistent; the configuration information of the service comprises software and hardware corresponding to the service, the type of the architecture node, the number of virtual machines on the node and the mounted storage of the virtual machines.
3. The multi-architecture supported K8S integration and deployment method of claim 1, wherein: the completing the cluster deployment service according to the comparison result comprises:
when the comparison result shows that the expected environment is different from the current environment, the following steps are executed:
feeding the comparison result back to the dispatching center;
after the remote deployment system receives the operation instruction which is sent by the dispatching center and needs to be deployed or not, if the deployment instruction needs to be executed continuously, the remote deployment system pulls the dependency related to the target expected environment corresponding to the deployment instruction from the K8s mirror image software warehouse.
4. The multi-architecture supported K8S integration and deployment method of claim 1, wherein: before the cross compiling of the code stored in the code warehouse in advance, the method further comprises the following steps:
and the dispatching center sends the received codes to a code inspection system for inspection, and incorporates the codes meeting the inspection conditions into a K8S code warehouse.
5. A multi-architecture supported K8S integration and deployment system, comprising:
the cross compiling module is used for carrying out cross compiling on the codes stored in the code warehouse in advance to form a cross compiling result;
the Kubernetes mirror image and the software warehouse are used for storing a cross compiling result formed by cross compiling of the cross compiling module;
the dispatching center receives the deployment instruction and issues the deployment instruction to the remote deployment system;
and the remote deployment system carries out environment verification on the target cluster after receiving the deployment instruction, compares an environment verification result with the expected environment of the target cluster corresponding to the deployment instruction, and completes the cluster deployment service according to the comparison result.
6. The multi-architecture enabled K8S integration and deployment system of claim 5, wherein: the verification result obtained by the remote deployment system performing the environment verification on the target cluster comprises: whether the service exists, the version of the service and the corresponding configuration information of the service are consistent; the configuration information of the service comprises software and hardware corresponding to the service, the type of the architecture node, the number of virtual machines on the node and the mounted storage of the virtual machines.
7. The multi-architecture enabled K8S integration and deployment system of claim 5, wherein: when the comparison result of the remote deployment system shows that the expected environment is different from the current environment, the remote deployment system performs the following operations:
feeding the comparison result back to the dispatching center;
after the remote deployment system receives the operation instruction which is sent by the dispatching center and needs to be deployed or not, if the deployment instruction needs to be executed continuously, the remote deployment system pulls the dependency related to the target expected environment corresponding to the deployment instruction from the K8s mirror image software warehouse.
8. The multi-architecture enabled K8S integration and deployment system of claim 1, further comprising:
and the code examination system is used for examining the codes received by the dispatching center and integrating the codes meeting the examination conditions into the K8S code warehouse.
And the code warehouse is used for storing the codes meeting the examination conditions after being examined by the code examination system and calling the target codes for cross compiling by the cross compiling system.
9. A system supporting multi-architecture K8S integration and deployment, the system comprising a processor, a memory, and a computer program stored in the memory and operable on the processor, wherein the computer program is loaded and executed by the processor to implement the multi-architecture supporting kubernets integration and deployment method of any one of claims 1-4.
10. A computer-readable storage medium, in which a computer program is stored, which, when being executed by a processor, is adapted to implement the kubernets integration and deployment method supporting multiple architectures according to any one of claims 1-4.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115185561A (en) * | 2022-07-20 | 2022-10-14 | 杭州雷数科技有限公司 | CICD system based on service Jenkins and implementation method |
| CN117112144A (en) * | 2023-09-22 | 2023-11-24 | 上海卓悠网络科技有限公司 | Method and system for deploying k3s on android system and storage medium |
-
2021
- 2021-12-31 CN CN202111666861.XA patent/CN114327484A/en active Pending
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115185561A (en) * | 2022-07-20 | 2022-10-14 | 杭州雷数科技有限公司 | CICD system based on service Jenkins and implementation method |
| CN117112144A (en) * | 2023-09-22 | 2023-11-24 | 上海卓悠网络科技有限公司 | Method and system for deploying k3s on android system and storage medium |
| CN117112144B (en) * | 2023-09-22 | 2024-03-12 | 上海卓悠网络科技有限公司 | Method and system for deploying k3s on android system and storage medium |
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