endly

End to end functional test and automation framework

Programming language: Go

License: Apache License 2.0

Tags: Testing     Testing Frameworks    

Latest version: v0.55

README

Declarative end to end functional testing (endly)

This library is compatible with Go 1.12+

Please refer to [CHANGELOG.md](CHANGELOG.md) if you encounter breaking changes.

• Motivation
• Introduction
• Getting Started
• Documentation

• License

• Credits and Acknowledgements

Motivation

An end to end testing is a methodology which comprehensively tests an application in the environment closely imitating production system with all network communication, user, datastore and other dependencies interaction.

It takes great length to manually prepare an application and its data for testing. And it can be serious bottleneck if this process is manual or relies on the 3rd party. Complex regression test plan execution and data organization can be yet additional challenge with hundreds business use cases to test.

While there are many great frameworks selection helping with an integration testing:

web UI integration testing:

• Selenium
• Cypress.io
• Protractor

or database integration testing:

• dbunit
• dsunit

or application build and deployment:

• Docker

None of these tools on its own have a comprehensive end to end testing and automation capabilities. What is worst some of these tools are coupled with a particular frameworks or specific language.

Endly takes declarative approach to test an application written in any language. The testing weight moves towards input and desired application output definition. This framework provides an ability to maintain and operate on hundreds of use cases effectively and cohesively, on top of that it can also automate system, data and application preparation related tasks. Endly can easily orchestrate e2e testing process of n-tier distributed application where backend, middleware and front-end each uses different stack.

Some typical e2e testing tasks supported by endly:

• Local or remote system preparation including all services required by the application (with or without docker).
• Checking out the application code
• Building and deploying the application (with or without docker).
• Database and data preparation
• Setting application state
• Regression test execution (HTTP, REST, Selenium)
• Data and application output verification (UI changes, transaction logs, database changes)

Introduction

Endly uses a generic workflow system to automate development and testing processes. Each process defines a sequence of task and actions. While a task act like a grouping element, an action does the actual job. For instance a regression test task; it may involve many small activities like sending HTTP request and checking response, validating database state, validating log records produced by the application, etc.

Various endly services expose a set of actions that can be directly invoked by a user-defined workflow.

Imagine an application build task, which may involve the following

• code checkout
• setting up SDK
• setting build tools
• setting environment
• build an app

An endly workflow accomplishing this task may look like the following:

init:
  xxCredentials: ${env.HOME}/.secret/secret.json
  appPath: $WorkingDirectory(../)
  target:
    URL: ssh://127.0.0.1/
    credentials: localhost
pipeline:
  build-app:
    checkout:
      action: version/control:checkout
      origin:
        URL: https://github.com/some_repo/app
      dest:
        URL: $appPath
    set_sdk:
      set_jdk:
        action: sdk:set
        sdk: jdk:1.8
      set_build_runner:
        action: deployment:deploy
        appName: maven
        version: 3.5
      set_env:
        action: exec:run
        target: $target
        commands:
          - export XXX_CREDENTIALS=$xxCredentials
    get-schema:
      action: storage:copy
      source:
        URL: https://raw.githubusercontent.com/some_repo/db/schema.sql
      dest:
        URL: $appPath/schema.sql
    build:
      action: exec:run
      request: '@build.yaml'

@build.yaml

target: $target
commands:
  - echo 'building app'
  - cd $appPath
  - mvn clean test

In the following inline workflow, I have used

• version/control service with checkout operation
• sdk service with set operation
• deployment service with deploy operation
• storage service with copy operation
• exec service with run operation

Endly exposes services in the RESTful manner, where each service provides a list of supported operation alongside with corresponding contracts. Any service request can be defined either directly within workflow or delegated to external request file using YAML or JSON format.

For instance to find out what request/response contract is supported by exec:run (which uses SSH session) you can simply run

endly -s=exec -a=run

The following command provide list of currently supported endly services

endly -s='*'

While the above build task example was a trivial workflow usage, the power of endly comes with

• flexible workflow definition
• workflow reusability
• full stateful workflow execution control (i.e., defer task, on error task, loops, switch/case, concurrent action execution etc)
• ability to organize regression workflow with thousands of use cases in a cohesive manner
• ability to comprehensively control testing application state
• flexible service architecture

Getting Started

Installation

• [Install/Download](doc/installation)
• [Endly docker image](docker/)

Project generator

Good workflow and data organization is the key for success, e2e project generator is the great place to start.

• [Create test project for your app](doc/generator). [test project generator](project_generator.png)

Examples:

a) System preparation

For instance: the following define inline workflow to prepare app system services:

@system.yaml

tasks: $tasks
defaults:
  target: $serviceTarget
pipeline:
  destroy:
    stop-images:
      action: docker:stop
      images:
        - mysql
        - aerospike
  init:
    services:
      mysql:
        workflow: "service/mysql:start"
        name: mydb3
        version: $mysqlVersion
        credentials: $mysqlCredentials
        config: config/my.cnf
      aerospike:
        workflow: "service/aerospike:start"
        name: mydb4
        config: config/aerospike.conf

b) Application build and deployment

For instance: the following define inline workflow to build and deploy a test app: (you can easily build an app for standalone mode or in and for docker container)

With Dockerfile build file and docker compose

@app.yaml

tasks: $tasks
init:
- buildPath = /tmp/build/myapp/
- version = 0.1.0
defaults:
  app: myapp
  version: 0.1.0
  useRegistry: false
pipeline:
  build:
    init:
      action: exec:run
      target: $target
      commands:
      - if [ -e $buildPath ]; then rm -rf $buildPath; fi
      - mkdir -p $buildPath
    checkout:
      action: version/control:checkout
      origin:
        URL: https://github.com/adrianwit/dstransfer
      dest:
        URL: scp://${targetHost}:22/$buildPath
        credentials: localhost
    download:
      action: storage:copy
      source:
        URL: config/Dockerfile
      dest:
        URL: $buildPath
        credentials: localhost
    build-img:
      action: docker:build
      target: $target
      path: $buildPath
      '@tag':
        image: dstransfer
        username: adrianwit
        version: 0.1.0
  stop:
    target: $appTarget
    action: docker/ssh:composeDown
    source:
      URL: config/docker-compose.yaml
  deploy:
    target: $appTarget
    action: docker/ssh:composeUp
    runInBackground: true
    source:
      URL: config/docker-compose.yaml

As Standalone app (with predefined shared workflow)

@app.yaml

init:
  buildTarget:
    URL: scp://127.0.0.1/tmp/build/myApp/
    credentials: localhost
  appTarget:
    URL: scp://127.0.0.1/opt/myApp/
    credentials: localhost
  target:
    URL: scp://127.0.0.1/
    credentials: localhost
defaults:
  target: $target

pipeline:

  build:
    checkout:
      action: version/control:checkout
      origin:
        URL: ./../ 
        #or https://github.com/myRepo/myApp
      dest: $buildTarget
    set-sdk:
      action: sdk:set
      sdk: go:1.11
    build-app:
      action: exec:run
      commands:
        - cd /tmp/build/myApp/app
        - export GO111MODULE=on
        - go build myApp.go
        - chmod +x myApp
    deploy:
      mkdir:
        action: exec:run
        commands:
          - sudo rm -rf /opt/myApp/
          - sudo mkdir -p /opt/myApp
          - sudo chown -R ${os.user} /opt/myApp

      install:
        action: storage:copy
        source: $buildTarget
        dest: $appTarget
        expand: true
        assets:
          app/myApp: myApp
          config/config.json: config.json

  stop:
    action: process:stop
    input: myApp

  start:
    action: process:start
    directory: /opt/myApp
    immuneToHangups: true
    command: ./myApp
    arguments:
      - "-config"
      - "config.json"

c) Datastore/database creation

For instance: the following define inline workflow to create/populare mysql and aerospike database/dataset:

@datastore.yaml

pipeline:
  create-db:
    db3:
      action: dsunit:init
      scripts:
        - URL: datastore/db3/schema.ddl
      datastore: db3
      recreate: true
      config:
        driverName: mysql
        descriptor: "[username]:[password]@tcp(127.0.0.1:3306)/[dbname]?parseTime=true"
        credentials: $mysqlCredentials
      admin:
        datastore: mysql
        config:
          driverName: mysql
          descriptor: "[username]:[password]@tcp(127.0.0.1:3306)/[dbname]?parseTime=true"
          credentials: $mysqlCredentials
    db4:
      action: dsunit:init
      datastore: db4
      recreate: true
      config:
        driverName: aerospike
        descriptor: "tcp([host]:3000)/[namespace]"
        parameters:
          dbname: db4
          namespace: db4
          host: $serviceHost
          port: 3000
  populate:
    db3:
      action: dsunit:prepare
      datastore: db3
      URL: datastore/db3/dictionary
    db4:
      action: dsunit:prepare
      datastore: db4
      URL: datastore/db4/data

endly -r=datastore

d) Creating setup / verification dataset from existing datastore

For instance: the following define inline workflow to create setup dataset SQL based from on existing database

@freeze.yaml

pipeline:
  db1:
    register:
      action: dsunit:register
      datastore: db1
      config:
        driverName: bigquery
        credentials: bq
        parameters:
          datasetId: adlogs

    reverse:
      takeSchemaSnapshot:
        action: dsunit:dump
        datastore: db1
        # leave empty for all tables
        tables:
          - raw_logs
        #optionally target for target vendor if different that source  
        target: mysql 
        destURL: schema.sql

      takeDataSnapshot:
        action: dsunit:freeze
        datastore: db1
        destURL: db1/prepare/raw_logs.json
        omitEmpty: true
        ignore:
          - request.postBody
        replace:
          request.timestamp: $$ts
        sql:  SELECT request, meta, fee
                FROM raw_logs 
                WHERE requests.sessionID IN(x, y, z)

endly -r=freeze

e) Comparing SQL based data sets

endly -r=compare

@compare.yaml

pipeline:
  register:
    verticadb:
      action: dsunit:register
      datastore: db1
      config:
        driverName: odbc
        descriptor: driver=Vertica;Database=[database];ServerName=[server];port=5433;user=[username];password=[password]
        credentials: db1
        parameters:
          database: db1
          server: x.y.z.a
          TIMEZONE: UTC
    bigquerydb:
      action: dsunit:register
      datastore: db2
      config:
        driverName: bigquery
        credentials: db2
        parameters:
          datasetId: db2
  compare:
    action: dsunit:compare
    maxRowDiscrepancy: 10
    ignore:
      - field10
      - fieldN
    directives:
      "@numericPrecisionPoint@": 7
      "@coalesceWithZero@": true
      "@caseSensitive@": false

    source1:
      datastore: db1
      SQL: SELECT * 
           FROM db1.mytable 
           WHERE DATE(ts) BETWEEN '2018-12-01' AND '2018-12-02' 
           ORDER BY 1

    source2:
      datastore: db2
      SQL: SELECT *
           FROM db2.mytable
           WHERE DATE(ts) BETWEEN '2018-12-01' AND '2018-12-02'
           ORDER BY 1

f) Testing

For instance: the following define inline workflow to run test with selenium runner:

@test.yaml

defaults:
  target:
     URL: ssh://127.0.0.1/
     credentials: localhost
pipeline:
  init:
    action: selenium:start
    version: 3.4.0
    port: 8085
    sdk: jdk
    sdkVersion: 1.8
  test:
    action: selenium:run
    browser: firefox
    remoteSelenium:
      URL: http://127.0.0.1:8085
    commands:
      - get(http://play.golang.org/?simple=1)
      - (#code).clear
      - (#code).sendKeys(package main

          import "fmt"

          func main() {
              fmt.Println("Hello Endly!")
          }
        )
      - (#run).click
      - command: output = (#output).text
        exit: $output.Text:/Endly/
        sleepTimeMs: 1000
        repeat: 10
      - close
    expect:
      output:
        Text: /Hello Endly!/

endly -r=test

g) Stress testing:

The following define inline workflow that loads request and desired responses from data folder for stress testing.

@load.yaml

init:
  testEndpoint: z.myendoint.com
pipeline:
  test:
    tag: StressTest
    data:
      []Requests: '@data/*request.json'
      []Responses: '@data/*response.json'
    range: '1..1'
    template:
      info:
        action: print
        message: starting load testing 
      load:
        action: 'http/runner:load'
        threadCount: 3
        '@repeat': 100
        requests: $data.Requests
        expect:
          Responses: $data.Responses
      load-info:
        action: print
        message: 'QPS: $load.QPS: Response: min: $load.MinResponseTimeInMs ms, avg: $load.AvgResponseTimeInMs ms max: $load.MaxResponseTimeInMs ms'

Where data folder contains http request and desired responses i.e

@data/XXX_request.json

{
  "Method":"get",
  "URL":"http://${testEndpoint}/bg/?pixid=123"
}

@data/XXX_response.json

{
  "Code":200,
  "Body":"/some expected fragement/"
}

endly -r=load

h) Serverless e2e testing with cloud function

@test.yaml

defaults:
  credentials: am
pipeline:
  deploy:
    action: gcp/cloudfunctions:deploy
    '@name': HelloWorld
    entryPoint: HelloWorldFn
    runtime: go111
    source:
      URL: test/
  test:
    action: gcp/cloudfunctions:call
    logging: false
    '@name': HelloWorld
    data:
      from: Endly
  info:
    action: print
    message: $test.Result
  assert:
    action: validator:assert
    expect: /Endly/
    actual: $test.Result
  undeploy:
    action: gcp/cloudfunctions:delete
    '@name': HelloWorld

i) Serverless e2e testing with lambda function

@test.yaml

init:
  functionRole: lambda-loginfo-executor
  functionName: LoginfoFn
  codeZip: ${appPath}/loginfo/app/loginfo.zip
  privilegePolicy: ${parent.path}/privilege-policy.json
pipeline:
  deploy:
    build:
      action: exec:run
      target: $target
      errors:
        - ERROR
      commands:
        - cd ${appPath}loginfo/app
        - unset GOPATH
        - export GOOS=linux
        - export GOARCH=amd64
        - go build -o loginfo
        - zip -j loginfo.zip loginfo

    setupFunction:
      action: aws/lambda:deploy
      credentials: $awsCredentials
      functionname: $functionName
      runtime:  go1.x
      handler: loginfo
      code:
        zipfile: $LoadBinary(${codeZip})
      rolename: lambda-loginfo-executor
      define:
        - policyname: s3-mye2e-bucket-role
          policydocument: $Cat('${privilegePolicy}')
      attach:
        - policyarn: arn:aws:iam::aws:policy/service-role/AWSLambdaBasicExecutionRole

    setupAPI:
      action: aws/apigateway:deployAPI
      credentials: aws
      '@name': loginfoAPI
      resources:
        - path: /{proxy+}
          methods:
            - httpMethod: ANY
              functionname: $functionName
    sleepTimeMs: 10000

  test:
    action: rest/runner:send
    URL: ${setupAPI.EndpointURL}oginfo
    method: post
     '@request':
      region: ${awsSecrets.Region}
      URL: s3://mye2e-bucket/folder1/
    expect:
      Status: ok
      FileCount: 2
      LinesCount: 52

To see Endly in action,

End to end testing examples

In addition a few examples of fully functioning applications are included. You can build, deploy and test them end to end all with endly.

1) Web Service

• [Reporter](example/ws/reporter) - a pivot table report builder. - Test with Rest Runner - Data Preparation and Validation (mysql)

2) User Interface

• [SSO](example/ui/sso) - user registration and login application. - Test with Selenium Runner - Test with HTTP Runner - Data Preparation and Validation (aersopike) - Web Content validation - Mocking 3rd party REST API with [http/endpoint service](testing/endpoint/http)

3) Extract, Transform and Load (ETL)

• [Transformer](example/etl/myApp) - datastore to datastore myApp (i.e. aerospike to mysql)
  • Test with Rest Runner
  • Data Preparation and Validation (aersopike, mysql)

4) Runtime - simple http request event logger

• [Logger](example/rt/elogger)
  • Test with HTTP Runner
  • Log Validation

5) Serverless - serverless (lambda/cloud function/dataflow)

• Serverless

Documentation

• [Installation](doc/installation)
• [Secret/Credential](doc/secrets)
• [Inline Workflow](doc/inline)
• [Workflow](doc/workflow)
• [Service](doc/service)
• [Usage](doc/usage)
• [User Defined Function](doc/udf)
• [Data store testing](testing/dsunit)

@run.yaml

target:
  URL: "ssh://127.0.0.1/"
  credentials: localhost
systemPaths:
  - /usr/local/go/bin
commands:
  - go version
  - echo $GOPATH

External resources

• Endly introduction
• Software Developement Automation - Part I
• Software Developement Automation - Part II
• ETL end to end testing with docker, NoSQL, RDBMS and Big Query
• Data testing strategy reinvented
• Go lang e2e testing
• Endly UI e2e testing demo

License

The source code is made available under the terms of the Apache License, Version 2, as stated in the file LICENSE.

Individual files may be made available under their own specific license, all compatible with Apache License, Version 2. Please see individual files for details.

TODO

• [ ] documentation improvements
• [ ] command executor with os/exec.Command
• [ ] gcp/containers integration
• [ ] gcp/cloudfunctions viant/afs integration
• [ ] ufd self describing meta data
• [ ] viant/afs docker connector

Contributing to endly

endly is an open source project and contributors are welcome!

Credits and Acknowledgements

Library Author: Adrian Witas