CN113590494B - Automatic testing method for cloud native environment vulnerability - Google Patents
Automatic testing method for cloud native environment vulnerability Download PDFInfo
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- CN113590494B CN113590494B CN202111002106.1A CN202111002106A CN113590494B CN 113590494 B CN113590494 B CN 113590494B CN 202111002106 A CN202111002106 A CN 202111002106A CN 113590494 B CN113590494 B CN 113590494B
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/36—Preventing errors by testing or debugging software
- G06F11/3668—Software testing
- G06F11/3672—Test management
- G06F11/3684—Test management for test design, e.g. generating new test cases
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/36—Preventing errors by testing or debugging software
- G06F11/3668—Software testing
- G06F11/3672—Test management
- G06F11/3688—Test management for test execution, e.g. scheduling of test suites
Abstract
The invention discloses an automatic testing method of cloud native environment vulnerability, which comprises S1, initializing a system to an application cluster, creating related custom resources by adopting an Operator expansion mode and a custom controller for managing the custom resources, wherein the custom controller comprises a fault definition controller, a vulnerability testing result controller and a testing automation working flow controller which are operated in a K8S by a default mode; and S2, the test automation workflow controller monitors whether a test task needing to be executed exists at the current time through the K8S Api Server, if so, the step is S3 and the like. The advantages are that: various fault scenes in the real world which may be met by the system can be simulated, bug of the system or weak point of the system can be found out to the maximum extent in advance, and reliability and toughness of the cloud native environment can be effectively improved through advanced reinforcement and optimization.
Description
Technical Field
The invention relates to the technical field of cloud-native environment, in particular to an automatic testing method for vulnerability of a cloud-native environment.
Background
In recent years, various industries are facing to the wave of digital transformation, and with the understanding and practice of enterprises on cloud computing being deepened, micro-servitization, development, operation and maintenance integration, continuous integration and continuous release and distributed architecture based on cloud originality have become more and more preferred schemes for enterprise application construction. By adopting the cloud native architecture, the system can be fully decoupled, and the system can be quickly and iteratively upgraded, so that the development efficiency is greatly improved. Meanwhile, compared with the traditional single architecture, some challenges are brought, for example, local faults of the system may cause the breakdown of the whole system, a great amount of micro services cause failure investigation without help, whether the elasticity of the system meets design targets, how to verify the high availability of the system, the fault tolerance of the micro services, whether the arrangement of kubernets (hereinafter referred to as k8s) is reasonable, whether the disaster recovery system is really effective, and the like. Aiming at a complex cloud primary architecture, how to quickly and comprehensively discover the weakness of the system, thereby reinforcing and optimizing the system in advance and improving the toughness of the system becomes a problem to be solved urgently.
Conventional software testing, such as unit testing, functional testing, integration testing, system testing, and performance and stress testing, cannot fully solve the challenge of the cloud-native architecture, because the conventional testing is to give a specific condition and perform a specific action, and the system outputs a specific result. Generally, a test will only produce binary results, i.e., verify whether a result is true or false, and thus determine whether the test passed. This practice does not allow us to exploit vulnerabilities of the system that are unknown or not yet known, but merely tests possible values of known system properties.
In order to fully discover the vulnerability of the cloud native architecture and fully improve the toughness of the system, an automated testing method is urgently needed to fully simulate the fault characteristics in the real world, such as randomness, uncertainty and the like, to test the system so as to automatically and rapidly discover the vulnerability of the cloud native system.
Disclosure of Invention
The invention aims to provide an automatic testing method for cloud native environment vulnerability, so as to solve the problems in the prior art.
In order to achieve the purpose, the technical scheme adopted by the invention is as follows:
an automatic test method for cloud native environment vulnerability comprises the following steps,
s1, initializing the system to an application cluster, and creating related custom resources and a custom controller for managing the custom resources by adopting an Operator expansion mode, wherein the custom controller comprises a fault definition controller, a vulnerability test result controller and a test automation workflow controller which are operated in K8S in a Deployment mode;
s2, the test automation workflow controller monitors whether a test task needs to be executed at the current time point through a K8S Api Server, if yes, the test automation workflow controller enters S3; if not, continuing monitoring;
s3, the Step of the test task is decomposed by the test automation workflow controller, the Step is decomposed into a plurality of independent tasks, and a first task Step is randomly acquired;
s4, the test automation workflow controller calls K8sApi to create a vulnerability test object according to the template definition of the task Step;
s5, when the vulnerability test controller monitors that a vulnerability test object is created, starting to execute the vulnerability test;
s6, the vulnerability test result controller acquires the test result of the task Step and feeds the test result back to the test automation working flow controller;
s7, the test automation workflow controller judges whether the task Step is executed in parallel or in sequence, if the task Step is executed in parallel, the test automation workflow controller directly returns to S3 to obtain the next task Step; if the task is executed sequentially, the execution of the task Step is waited to be completed, and then the Step is returned to S3 to obtain the next task Step;
and S8, returning to S2 to continue monitoring until the plurality of independent tasks are executed completely.
Preferably, the vulnerability test controller performs the vulnerability test including a procedure,
a1, starting initialization Init Container, creating k8s Job according to the vulnerability test definition to execute the initialization phase, and starting Watch Container to wait for the task execution to be completed;
a2, acquiring an actual fault definition from the fault controller according to the vulnerability test definition, and starting a Main Container to execute the fault test;
a3, starting a reverse Container execution environment recovery action according to the vulnerability test definition;
a4, the Watch Container obtains the test result and sends the test result to the K8s Api Server, namely, the vulnerability test result object is created.
Preferably, the custom resources include,
the HaTechVulFault is used for defining a self-defined resource object of the K8s fault; the authority required for executing the corresponding fault, the mirror image for executing the corresponding fault, a command line for executing the corresponding fault, a parameter for executing the corresponding fault and an environment variable for executing the corresponding fault can be defined;
the HaTechVulEngine is used for defining a self-defined resource object of the k8s vulnerability test; the method comprises the steps of containing faults needing to be executed and authority and environment variables needed for executing the faults;
the HaTechVulEnginesesrault is used for defining a self-defined resource object of the k8s vulnerability test result; the vulnerability testing system comprises a vulnerability testing object and execution state information of the vulnerability testing;
the HaTechVulWorkFlow is used for defining a self-defined resource object of the k8s vulnerability testing automation workflow; including all the vulnerability tests that need to be performed and the order of execution of the individual vulnerability tests.
Preferably, the fault definition controller is used for managing a fault library for testing, and the fault definition controller manages the mirror image of fault execution, fault starting commands and parameters, environment variables for fault execution and authority required for fault execution; the fault definition controller defaults to provide basic faults for a fault library, wherein the basic faults comprise downtime aiming at basic resources, node network abnormity, high node CPU load and full disk, and Pod termination, Container termination and Pod network abnormity aiming at a K8s cluster; the fault definition controller supports user-defined extension faults and supports adding, modifying, checking and deleting faults in a fault library through a Kubectl command or by calling a RESTMaper interface.
Preferably, the vulnerability test controller is used for managing fault tests, and contains a fault and an environment variable for executing the fault in real time; the fault testing method can receive a testing request from the testing automation workflow controller aiming at the fault, execute fault testing according to the request and send a testing result to the vulnerability testing result controller.
Preferably, the test automation workflow controller comprises a plurality of vulnerability tests and a pre-action and an environment recovery action for executing the corresponding vulnerability tests; multiple vulnerability tests may be performed in parallel or sequentially; the test automation workflow controller supports immediate execution at a time and repeated execution at regular intervals.
The invention has the beneficial effects that: 1. by using the workflow engine and the testing thought of chaotic engineering, various fault scenes in the real world which may be met by the system can be simulated, bug of the system or weakness of the system can be found out to the maximum extent in advance, and the reliability and toughness of the cloud native environment can be effectively improved through advanced reinforcement and optimization. 2. The characteristics of simulating real-world faults support complex scenes, multiple faults occur in parallel or in sequence, the time point of the fault occurrence is any time point which can be completely defined by a user, and the fault occurrence can be repeated once or repeatedly, for example, the simulation node is restarted at an irregular time, and the Pod is deleted at an irregular time, so that whether the Kubernets cluster can be normally scheduled or not and whether the application can be normally accessed or not can be observed, the weakness of the system can be found out in advance, the reinforcement system is optimized in advance, and the toughness of the system is enhanced.
Drawings
FIG. 1 is a schematic diagram of an automated testing method in an embodiment of the invention;
FIG. 2 is a flowchart illustrating an automated testing method according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail below with reference to the accompanying drawings. It should be understood that the detailed description and specific examples, while indicating the invention, are intended for purposes of illustration only and are not intended to limit the scope of the invention.
As shown in fig. 1 and fig. 2, in the present embodiment, an automated testing method for cloud-native environment vulnerability is provided, which includes the following steps,
s1, initializing the system to an application cluster, and creating related custom resources and a custom controller for managing the custom resources by adopting an Operator expansion mode, wherein the custom controller comprises a fault definition controller, a vulnerability test result controller and a test automation workflow controller which are operated in K8S in a Deployment mode;
s2, the test automation workflow controller monitors whether a test task (HaTechVulWorkFlow object) needing to be executed exists at the current time point through a K8S Api Server, if yes, the test automation workflow controller enters S3; if not, continuing monitoring;
s3, the test automation workflow controller decomposes the Steps of the test task (HaTechVulWorkFlow object), decomposes the Steps into a plurality of independent task Steps, and randomly acquires a first task Step;
s4, the test automation workflow controller calls K8S Api to create a vulnerability test object (HaTechVulEngine object) according to the template definition of the task Step;
s5, the vulnerability testing controller monitors that a vulnerability testing object (HaTechVulEngine object) is created, and starts to execute the vulnerability testing;
s6, the vulnerability test result controller acquires the test result of the task Step and feeds the test result back to the test automation working flow controller;
s7, the test automation workflow controller judges whether the task Step is executed in parallel or in sequence, if the task Step is executed in parallel, the test automation workflow controller directly returns to S3 to obtain the next task Step; if the task is executed sequentially, the execution of the task Step is waited to be completed, and then the Step is returned to S3 to obtain the next task Step;
and S8, returning to S2 to continue monitoring until the plurality of independent tasks are executed completely.
In this embodiment, the vulnerability test controller performs the vulnerability test including the following processes,
a1, starting initialization Init Container, creating k8s Job execution initialization phase according to the definition of vulnerability test (HaTechVulEngine object), and starting Watch Container to wait for the completion of task execution;
a2, acquiring an actual fault definition from a fault controller according to a vulnerability test definition (HaTechVulEngine object), and starting a Main Container to execute a fault test;
a3, starting a reverse Container execution environment recovery action according to a vulnerability test definition (HaTechVulEngine object);
a4, Watch Container obtains the test result, and sends the test result to K8s Api Server, namely creates the vulnerability test result object (HaTechVulEnginesesult object).
In this embodiment, the custom Resource crd (custom Resource definition) includes,
the HaTechVulFault is used for defining a self-defined resource object of the K8s fault; the authority required for executing the corresponding fault, the mirror image for executing the corresponding fault, a command line for executing the corresponding fault, a parameter for executing the corresponding fault and an environment variable for executing the corresponding fault can be defined; the faults include various basic resources, application or cloud-native faults, such as machine cpu load, high memory occupation, network delay, network packet loss, machine shutdown, machine restart, kubernets pod killing, podcpu load, high pod memory occupation and the like.
HaTechVulFault includes the following basic information
| metadata | Self-based information, tags, etc. |
| permissions | Defining the permissions required to perform the failure |
| image | Docker mirror executing the failure |
| command | The command line executing the fault |
| args | Parameters to carry out the fault |
| env | The environment variable executing the fault |
The HaTechVulEngine is used for defining a self-defined resource object of the k8s vulnerability test; the method comprises the steps of containing faults needing to be executed and authority and environment variables needed for executing the faults;
the HaTechVulEnginesesrault is used for defining a self-defined resource object of the k8s vulnerability test result; the vulnerability testing system comprises a vulnerability testing object and execution state information of the vulnerability testing;
the HaTechVulWorkFlow is used for defining a self-defined resource object of the k8s vulnerability testing automation workflow; including all the vulnerability tests that need to be performed and the order of execution of the individual vulnerability tests.
In this embodiment, the custom controller includes a fault definition controller, a vulnerability testing result controller, and a testing automation workflow controller, all of which operate in the manner of Deployment in kubernets.
The fault definition controller is used for managing a fault library for testing, and the fault definition controller is used for managing a mirror Image, a fault starting Command and parameters Args of fault execution, an environment variable Env of fault execution and authority required by fault execution; the fault definition controller defaults to provide basic faults for a fault library, wherein the basic faults comprise downtime aiming at basic resources, node network abnormity, high node CPU load and full disk, and Pod termination, Container termination and Pod network abnormity aiming at a K8s cluster; the fault definition controller supports user-defined extension faults and supports adding, modifying, checking and deleting faults in a fault library through a Kubectl command or by calling a RESTMaper interface.
The vulnerability test controller is used for managing fault tests, and contains a fault and an environment variable Env for executing the fault in real time; the fault testing method can receive a testing request from the testing automation workflow controller aiming at the fault, execute fault testing according to the request and send a testing result to the vulnerability testing result controller.
The test automation workflow controller comprises a plurality of vulnerability tests and a pre-action and an environment recovery action for executing the corresponding vulnerability tests; multiple vulnerability tests may be performed in parallel or sequentially; the test automation workflow controller supports immediate execution at a time and repeated execution at regular intervals; such as a day, a week, a time of a month.
By adopting the technical scheme disclosed by the invention, the following beneficial effects are obtained:
the invention provides an automatic testing method for cloud native environment vulnerability, which uses a workflow engine and a chaotic engineering testing thought to simulate various fault scenes in the real world which may be encountered by a system, finds out bug of the system or the vulnerability of the system to the maximum extent in advance, and can effectively improve the reliability and toughness of the cloud native environment through reinforcement and optimization in advance. The method simulates the characteristics of real-world faults, supports complex scenes, enables a plurality of faults to occur in parallel or in sequence, enables the time point of the fault occurrence to be any time point which can be completely defined by user, and can support one or more repeated occurrences, such as restarting of a simulation node at an indefinite time and deleting of Pod at an indefinite time, so as to observe whether a Kubernetes cluster can be normally scheduled or not and whether application can be normally accessed or not, thereby finding out the weakness of the system in advance, optimizing the reinforcement system in advance, and enhancing the toughness of the system.
The foregoing is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, various modifications and improvements can be made without departing from the principle of the present invention, and such modifications and improvements should also be considered within the scope of the present invention.
Claims (5)
1. An automatic test method for cloud native environment vulnerability is characterized in that: comprises the following steps of (a) carrying out,
s1, initializing the system to an application cluster, and creating related custom resources and a custom controller for managing the custom resources by adopting an Operator expansion mode, wherein the custom controller comprises a fault definition controller, a vulnerability test result controller and a test automation workflow controller which are operated in K8S in a Deployment mode;
s2, the test automation workflow controller monitors whether a test task needs to be executed at the current time point through a K8S Api Server, if yes, the test automation workflow controller enters S3; if not, continuing monitoring;
s3, the Step of the test task is decomposed by the test automation workflow controller, the Step is decomposed into a plurality of independent tasks, and a first task Step is randomly acquired;
s4, the test automation workflow controller calls K8S Api to create a vulnerability test object according to the template definition of the task Step;
s5, when the vulnerability test controller monitors that a vulnerability test object is created, starting to execute the vulnerability test;
s6, the vulnerability test result controller acquires the test result of the task Step and feeds the test result back to the test automation working flow controller;
s7, the test automation workflow controller judges whether the task Step is executed in parallel or in sequence, if the task Step is executed in parallel, the test automation workflow controller directly returns to S3 to obtain the next task Step; if the task is executed sequentially, the execution of the task Step is waited to be completed, and then the Step is returned to S3 to obtain the next task Step;
s8, returning to S2 to continue monitoring until the plurality of independent tasks are executed completely;
the vulnerability test controller performs the vulnerability test including the following processes,
a1, starting initialization Init Container, creating k8s Job according to the vulnerability test definition to execute the initialization phase, and starting Watch Container to wait for the task execution to be completed;
a2, acquiring an actual fault definition from the fault controller according to the vulnerability test definition, and starting a Main Container to execute the fault test;
a3, starting a reverse Container execution environment recovery action according to the vulnerability test definition;
a4, the Watch Container obtains the test result and sends the test result to the K8s Api Server, namely, the vulnerability test result object is created.
2. The automated testing method of cloud-native environment vulnerability of claim 1, characterized by: the custom resources may include, for example,
the HaTechVulFault is used for defining a self-defined resource object of the K8s fault; the authority required for executing the corresponding fault, the mirror image for executing the corresponding fault, a command line for executing the corresponding fault, a parameter for executing the corresponding fault and an environment variable for executing the corresponding fault can be defined;
the HaTechVulEngine is used for defining a self-defined resource object of the k8s vulnerability test; the method comprises the steps of containing faults needing to be executed and authority and environment variables needed for executing the faults;
the HaTechVulEnginesesrault is used for defining a self-defined resource object of the k8s vulnerability test result; the vulnerability testing system comprises a vulnerability testing object and execution state information of the vulnerability testing;
the HaTechVulWorkFlow is used for defining a self-defined resource object of the k8s vulnerability testing automation workflow; including all the vulnerability tests that need to be performed and the order of execution of the individual vulnerability tests.
3. The automated testing method of cloud-native environment vulnerability of claim 1, characterized by: the fault definition controller is used for managing a fault library of the test, and the fault definition controller is used for managing a mirror image of fault execution, a fault starting command and parameter, an environment variable of fault execution and authority required by fault execution; the fault definition controller defaults to provide basic faults for a fault library, wherein the basic faults comprise downtime aiming at basic resources, node network abnormity, high node CPU load and full disk, and Pod termination, Container termination and Pod network abnormity aiming at a K8s cluster; the fault definition controller supports user-defined extension faults and supports adding, modifying, checking and deleting faults in a fault library through a Kubectl command or by calling a RESTMaper interface.
4. The automated testing method of cloud-native environment vulnerability of claim 1, characterized by: the vulnerability test controller is used for managing fault tests, and contains a fault and an environment variable for executing the fault in real time; the fault testing method can receive a testing request from the testing automation workflow controller aiming at the fault, execute fault testing according to the request and send a testing result to the vulnerability testing result controller.
5. The automated testing method of cloud-native environment vulnerability of claim 1, characterized by: the test automation workflow controller comprises a plurality of vulnerability tests and a pre-action and an environment recovery action for executing the corresponding vulnerability tests; multiple vulnerability tests may be performed in parallel or sequentially; the test automation workflow controller supports immediate execution at a time and repeated execution at regular intervals.
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