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This article introduces you how to use KubeSphere DevOps to build an automated testing system, the content is very detailed, interested friends can refer to, hope to be helpful to you.

Test layering

The purpose of the test is to verify the expected function and find potential defects. Testing increases confidence in delivering qualified products and makes agile iterations possible. It can be said that testing determines the progress of product development.

The network model has seven layers of OSI and four layers of TCP, while the development modes include MTV, MVC, MVP, MVVM and so on. High cohesion, low coupling, divided into responsibilities, modules, layering. Then structured, standardized, and the technology gradually matured.

Testing is also divided into UI testing, API testing, and unit testing. Testing is not a new technology, but a balance between output and cost.

The following is mainly about how to run automated tests using the KubeSphere DevOps system on the KubeSphere platform.

What is KubeSphere DevOps?

For container and Kubernetes application scenarios, KubeSphere provides an one-stop DevOps system based on Jenkins, including rich CI/CD pipeline construction and plug-in management features, as well as Binary-to-Image (B2I), Source-to-Image (S2I), code dependent cache support for pipeline, S2I, B2I, code quality management and pipeline logging.

KubeSphere's built-in DevOps system combines application development and automatic release with the container platform, and supports docking with third-party private image repositories and code repositories to form a complete CI/CD in private scenarios, providing an end-to-end user experience.

However, few users know that KubeSphere DevOps can also be used to build automated testing systems, which brings great convenience to automated unit testing, API testing and UI testing, and improves the work efficiency of testers.

Unit testing

Unit tests are run so frequently that they should be triggered every time the code is submitted. Unit testing is less dependent and usually requires only one container runtime environment.

The following is an example of running a unit test using golang:latest.

Pipeline {

Agent {

Node {

Label 'go'

}

}

Stages {

Stage ('testing') {

Steps {

Container ('go') {

Sh''

Git clone https://github.com/etcd-io/etcd.git

Cd etcd

Make test

''

}

}

}

}

}

Log of execution pipeline:

For other languages and frameworks, unit testing can also be easily run on Kubernetes by installing some packages and Mock-related services. You can explore more techniques for writing unit tests than runtime and unit test scenarios.

API test

If the team's automated testing is just getting started, API automated testing is a very good starting point.

Unit tests are mainly written by R & D. In the process of rapid iteration, experienced R & D will not forget to write unit tests. The faster the refactoring and change, the more important testing will become rather than a burden. Without writing a unit test, it can only be said that it is not taken seriously. It is very difficult to promote something that is ignored by the executor and it is difficult for managers to see the benefits.

UI automated testing is often replaced by manual testing. At the same time, the cost of maintaining UI automated testing is high, so UI automated testing should not be carried out too much in the process of rapid iteration.

The advantage of API testing is that under the framework of separation of front and rear ends, the documents and materials related to API are relatively perfect, and team members are relatively familiar with API, which is convenient for testing.

Here is an example of using Postman to automate API testing:

Pipeline {

Agent {

Kubernetes {

Label 'apitest'

Yaml''apiVersion: v1

Kind: Pod

Spec:

Containers:

-name: newman

Image: postman/newman_alpine33

Command: [\ 'cat\']

Tty: true

VolumeMounts:

-name: dockersock

MountPath: / var/run/docker.sock

-name: dockerbin

MountPath: / usr/bin/docker

Volumes:

-name: dockersock

HostPath:

Path: / var/run/docker.sock

-name: dockerbin

HostPath:

Path: / usr/bin/docker

''

DefaultContainer 'newman'

}

}

Parameters {

String (name: 'HOST', defaultValue:' 10.10.10.10, description:'')

String (name: 'PORT', defaultValue:' 8000yuan, description:'')

String (name: 'USERNAME', defaultValue:' admin', description:'')

String (name: 'PASSWORD', defaultValue:' password', description:'')

}

Stages {

Stage ('testing') {

Steps {

Sh''

Apk add-no-cache bash git openssh

Git clone https://yourdomain.com/ns/ks-api-test.git

Cd ks-api-test

Sed-I "s/__HOST__/$HOST/g" postman_environment.json

Sed-I "s/__PORT__/$PORT/g" postman_environment.json

Sed-I "s/__USERNAME__/$USERNAME/g" postman_environment.json

Sed-I "s/__PASSWORD__/$PASSWORD/g" postman_environment.json

Npm install-g newman-reporter-htmlextra

Newman run iam/postman_collection.json-e postman_environment.json-r htmlextra

''

}

}

}

Post {

Always {

ArchiveArtifacts' ks-api-test/newman/*'

}

}

}

Archive after execution:

Download the Artifact of Archive, decompress it and view the test report:

The framework for API automated testing is easy to implement, with just a few functions:

Interface request response assertion request orchestration to generate report

But be sure to choose the right solution according to the team's API testing and delivery habits. You can develop it yourself, or you can use existing tools. The above option is Postman + Newman because teams generally use Postman for API testing.

The rest is how to organize testing, you can submit files to a common warehouse, or you can use a paid version of Postman to share dataset testing.

UI test

The cost of UI automated testing is high in several ways:

Test cases are difficult to maintain. Front-end style change, product logic change. It is difficult to provide a stable operating environment. All kinds of timeout and dirty data will lead to a high failure rate.

The UI automated testing here uses the Robotframework framework that I am familiar with and uses keywords for automated testing.

Here is an example of using Robotframework to automate UI testing:

Pipeline {

Agent {

Kubernetes {

Label 'robotframework'

Yaml''apiVersion: v1

Kind: Pod

Spec:

Containers:

-name: robotframework

Image: shaowenchen/docker-robotframework:latest

Tty: true

VolumeMounts:

-name: dockersock

MountPath: / var/run/docker.sock

-name: dockerbin

MountPath: / usr/bin/docker

Volumes:

-name: dockersock

HostPath:

Path: / var/run/docker.sock

-name: dockerbin

HostPath:

Path: / usr/bin/docker

''

DefaultContainer 'robotframework'

}

}

Parameters {

String (name: 'HOST', defaultValue:' 10.10.10.10, description:'')

String (name: 'PORT', defaultValue:' 80808, description:'')

String (name: 'USERNAME', defaultValue:' admin', description:'')

String (name: 'PASSWORD', defaultValue:' password', description:'')

}

Stages {

Stage ('testing') {

Steps {

Sh''

Curl-s-L https://raw.githubusercontent.com/shaowenchen/scripts/master/kubesphere/preinstall.sh | bash

Git clone https://yourdomain.com/ns/ks-ui-test.git

Cd ks-ui-test

Sed-I "s/__USERNAME__/$USERNAME/g" tests/common.robot

Sed-I "s/__PASSWORD__/$PASSWORD/g" tests/common.robot

Echo "\ nTestEnv http://$HOST:$PORT" > > tests/api.robot

Echo "\ nTestEnv http://$HOST:$PORT" > > tests/devops.robot

. / start.sh'''

}

}

}

Post {

Always {

Sh 'tar cvf report-$BUILD_NUMBER.tar ks-ui-test/tests/report'

ArchiveArtifacts'* .tar'

}

}

}

Pipeline log after execution:

Download the Artifact of pipelined Archive, decompress it and view the test report:

KubeSphere (https://kubesphere.io) is an application-centric multi-tenant container platform built on Kubernetes, which provides full-stack IT automation operation and maintenance capabilities and simplifies the DevOps workflow of enterprises. KubeSphere provides a friendly and guided operation interface to help enterprises quickly build a powerful and feature-rich container cloud platform.

On how to use KubeSphere DevOps to build automated testing system to share here, I hope that the above content can be of some help to you, can learn more knowledge. If you think the article is good, you can share it for more people to see.

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