actions/importer-labs
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

Merge pull request #64 from valet-customers/jenkins-review

Browse Source 
Jenkins review
This commit is contained in:
Matisse Hack
2022-09-19 11:29:49 -07:00
committed by GitHub
parent 96acceb6bc 230c4e2f57
commit d019e23f3f
22 changed files with 367 additions and 540 deletions
Download Patch File Download Diff File Expand all files Collapse all files
.gitignore
+3 -356
View File
@@ -1,356 +1,3 @@
## Ignore Visual Studio temporary files, build results, and
## files generated by popular Visual Studio add-ons.
##
## Get latest from https://github.com/github/gitignore/blob/master/VisualStudio.gitignore
# User-specific files
*.rsuser
*.suo
*.user
*.userosscache
*.sln.docstates
# User-specific files (MonoDevelop/Xamarin Studio)
*.userprefs
# Mono auto generated files
mono_crash.*
# Build results
[Dd]ebug/
[Dd]ebugPublic/
[Rr]elease/
[Rr]eleases/
x64/
x86/
[Aa][Rr][Mm]/
[Aa][Rr][Mm]64/
bld/
[Bb]in/
[Oo]bj/
[Ll]og/
[Ll]ogs/
# Visual Studio 2015/2017 cache/options directory
.vs/
# Uncomment if you have tasks that create the project's static files in wwwroot
#wwwroot/
# Visual Studio 2017 auto generated files
Generated\ Files/
# MSTest test Results
[Tt]est[Rr]esult*/
[Bb]uild[Ll]og.*
# NUnit
*.VisualState.xml
TestResult.xml
nunit-*.xml
# Build Results of an ATL Project
[Dd]ebugPS/
[Rr]eleasePS/
dlldata.c
# Benchmark Results
BenchmarkDotNet.Artifacts/
# .NET Core
project.lock.json
project.fragment.lock.json
artifacts/
# StyleCop
StyleCopReport.xml
# Files built by Visual Studio
*_i.c
*_p.c
*_h.h
*.ilk
*.meta
*.obj
*.iobj
*.pch
*.pdb
*.ipdb
*.pgc
*.pgd
*.rsp
*.sbr
*.tlb
*.tli
*.tlh
*.tmp
*.tmp_proj
*_wpftmp.csproj
*.log
*.vspscc
*.vssscc
.builds
*.pidb
*.svclog
*.scc
# Chutzpah Test files
_Chutzpah*
# Visual C++ cache files
ipch/
*.aps
*.ncb
*.opendb
*.opensdf
*.sdf
*.cachefile
*.VC.db
*.VC.VC.opendb
# Visual Studio profiler
*.psess
*.vsp
*.vspx
*.sap
# Visual Studio Trace Files
*.e2e
# TFS 2012 Local Workspace
$tf/
# Guidance Automation Toolkit
*.gpState
# ReSharper is a .NET coding add-in
_ReSharper*/
*.[Rr]e[Ss]harper
*.DotSettings.user
# TeamCity is a build add-in
_TeamCity*
# DotCover is a Code Coverage Tool
*.dotCover
# AxoCover is a Code Coverage Tool
.axoCover/*
!.axoCover/settings.json
# Visual Studio code coverage results
*.coverage
*.coveragexml
# NCrunch
_NCrunch_*
.*crunch*.local.xml
nCrunchTemp_*
# MightyMoose
*.mm.*
AutoTest.Net/
# Web workbench (sass)
.sass-cache/
# Installshield output folder
[Ee]xpress/
# DocProject is a documentation generator add-in
DocProject/buildhelp/
DocProject/Help/*.HxT
DocProject/Help/*.HxC
DocProject/Help/*.hhc
DocProject/Help/*.hhk
DocProject/Help/*.hhp
DocProject/Help/Html2
DocProject/Help/html
# Click-Once directory
publish/
# Publish Web Output
*.[Pp]ublish.xml
*.azurePubxml
# Note: Comment the next line if you want to checkin your web deploy settings,
# but database connection strings (with potential passwords) will be unencrypted
*.pubxml
*.publishproj
# Microsoft Azure Web App publish settings. Comment the next line if you want to
# checkin your Azure Web App publish settings, but sensitive information contained
# in these scripts will be unencrypted
PublishScripts/
# NuGet Packages
*.nupkg
# NuGet Symbol Packages
*.snupkg
# The packages folder can be ignored because of Package Restore
**/[Pp]ackages/*
# except build/, which is used as an MSBuild target.
!**/[Pp]ackages/build/
# Uncomment if necessary however generally it will be regenerated when needed
#!**/[Pp]ackages/repositories.config
# NuGet v3's project.json files produces more ignorable files
*.nuget.props
*.nuget.targets
# Microsoft Azure Build Output
csx/
*.build.csdef
# Microsoft Azure Emulator
ecf/
rcf/
# Windows Store app package directories and files
AppPackages/
BundleArtifacts/
Package.StoreAssociation.xml
_pkginfo.txt
*.appx
*.appxbundle
*.appxupload
# Visual Studio cache files
# files ending in .cache can be ignored
*.[Cc]ache
# but keep track of directories ending in .cache
!?*.[Cc]ache/
# Others
ClientBin/
~$*
*~
*.dbmdl
*.dbproj.schemaview
*.jfm
*.pfx
*.publishsettings
orleans.codegen.cs
# Including strong name files can present a security risk
# (https://github.com/github/gitignore/pull/2483#issue-259490424)
#*.snk
# Since there are multiple workflows, uncomment next line to ignore bower_components
# (https://github.com/github/gitignore/pull/1529#issuecomment-104372622)
#bower_components/
# RIA/Silverlight projects
Generated_Code/
# Backup & report files from converting an old project file
# to a newer Visual Studio version. Backup files are not needed,
# because we have git ;-)
_UpgradeReport_Files/
Backup*/
UpgradeLog*.XML
UpgradeLog*.htm
ServiceFabricBackup/
*.rptproj.bak
# SQL Server files
*.mdf
*.ldf
*.ndf
# Business Intelligence projects
*.rdl.data
*.bim.layout
*.bim_*.settings
*.rptproj.rsuser
*- [Bb]ackup.rdl
*- [Bb]ackup ([0-9]).rdl
*- [Bb]ackup ([0-9][0-9]).rdl
# Microsoft Fakes
FakesAssemblies/
# GhostDoc plugin setting file
*.GhostDoc.xml
# Node.js Tools for Visual Studio
.ntvs_analysis.dat
node_modules/
# Visual Studio 6 build log
*.plg
# Visual Studio 6 workspace options file
*.opt
# Visual Studio 6 auto-generated workspace file (contains which files were open etc.)
*.vbw
# Visual Studio LightSwitch build output
**/*.HTMLClient/GeneratedArtifacts
**/*.DesktopClient/GeneratedArtifacts
**/*.DesktopClient/ModelManifest.xml
**/*.Server/GeneratedArtifacts
**/*.Server/ModelManifest.xml
_Pvt_Extensions
# Paket dependency manager
.paket/paket.exe
paket-files/
# FAKE - F# Make
.fake/
# CodeRush personal settings
.cr/personal
# Python Tools for Visual Studio (PTVS)
__pycache__/
*.pyc
# Cake - Uncomment if you are using it
# tools/**
# !tools/packages.config
# Tabs Studio
*.tss
# Telerik's JustMock configuration file
*.jmconfig
# BizTalk build output
*.btp.cs
*.btm.cs
*.odx.cs
*.xsd.cs
# OpenCover UI analysis results
OpenCover/
# Azure Stream Analytics local run output
ASALocalRun/
# MSBuild Binary and Structured Log
*.binlog
# NVidia Nsight GPU debugger configuration file
*.nvuser
# MFractors (Xamarin productivity tool) working folder
.mfractor/
# Local History for Visual Studio
.localhistory/
# BeatPulse healthcheck temp database
healthchecksdb
# Backup folder for Package Reference Convert tool in Visual Studio 2017
MigrationBackup/
# Ionide (cross platform F# VS Code tools) working folder
.ionide/
# valet files
.env*local
credentials_file.yaml
.vscode
.env.local
.cache/
tmp/
azure_devops/1-configure.md
+3 -2
View File
@@ -7,7 +7,7 @@ You will need to complete all of the setup instructions [here](./readme.md#confi
## Configuring credentials
1. Create an Azure DevOps personal access token (PAT).
__Note__: you can skip this step if you still have the PAT created during the setup steps [here](./readme.md#bootstrap-your-azure-devops-organization).
- Navigate to your existing organization (<https://dev.azure.com/:organization>) in your browser.
- In the top right corner of your screen, click `User settings`.
@@ -62,7 +62,8 @@ To verify our environment is configured correctly, run the `update` CLI command.
2. You should see a confirmation that you were logged into the GitHub Container Registry and Valet was updated to the latest version.
```bash
```console
$ gh valet update
Login Succeeded
latest: Pulling from valet-customers/valet-cli
Digest: sha256:a7d00dee8a37e25da59daeed44b1543f476b00fa2c41c47f48deeaf34a215bbb
azure_devops/2-audit.md
+1 -1
View File
@@ -20,7 +20,7 @@ You will now perform an audit against the bootstrapped Azure DevOps project. Ans
- __:project__. This should be the same project name used in the setup steps [here](./readme.md#bootstrap-your-azure-devops-organization)
3. Where do you want to store the result?
- __./tmp/audit__. This can be any path within the working directory from which Valet commands are executed.
- __tmp/audit__. This can be any path within the working directory from which Valet commands are executed.
### Steps
azure_devops/3-forecast.md
+5 -5
View File
@@ -5,7 +5,7 @@ In this lab you will use the `forecast` command to forecast potential GitHub Act
## Prerequisites
1. Followed the steps [here](./readme.md#configure-your-codespace) to set up your GitHub Codespaces environment and bootstrap an Azure DevOps project.
2. Completed the [configure lab](./1-configure-lab.md#configuring-credentials).
2. Completed the [configure lab](./1-configure.md#configuring-credentials).
## Perform a forecast
@@ -18,7 +18,7 @@ Answer the following questions before running the `forecast` command:
- __:project__. This should be the same project name used in the setup steps [here](./readme.md#bootstrap-your-azure-devops-organization)
3. Where do you want to store the results?
- `./tmp/forecast_reports`
- `tmp/forecast`
### Steps
@@ -26,7 +26,7 @@ Answer the following questions before running the `forecast` command:
2. Run the following command from the root directory:
```bash
gh valet forecast azure-devops --output-dir ./tmp/forecast_reports
gh valet forecast azure-devops --output-dir tmp/forecast
```
__Note__: The Azure DevOps organization and project name can be omitted from the `forecast` command because they were persisted in the `.env.local` file in the [configure lab](./1-configure.md). You can optionally provide these arguments on the command line with the `--azure-devops-organization` and `--azure-devops-project` CLI options.
@@ -42,7 +42,7 @@ Answer the following questions before running the `forecast` command:
5. Run the following `forecast` command while specifying the path to the sample json files:
```bash
gh valet forecast azure-devops --output-dir ./tmp/forecast_reports --source-file-path azure_devops/bootstrap/jobs.json
gh valet forecast azure-devops --output-dir tmp/forecast --source-file-path azure_devops/bootstrap/jobs.json
```
6. The command will list all the files written to disk when the command succeeds.
@@ -51,7 +51,7 @@ Answer the following questions before running the `forecast` command:
## Review the forecast report
The forecast report, logs, and completed job data will be located within the `tmp/forecast_reports` folder.
The forecast report, logs, and completed job data will be located within the `tmp/forecast` folder.
1. Find the `forecast_report.md` file in the file explorer.
2. Right-click the `forecast_report.md` file and select `Open Preview`.
azure_devops/4-dry-run.md
+6 -6
View File
@@ -5,7 +5,7 @@ In this lab you will use the `dry-run` command to convert an Azure DevOps pipeli
## Prerequisites
1. Followed the steps [here](./readme.md#configure-your-codespace) to set up your GitHub Codespaces environment and bootstrap an Azure DevOps project.
2. Completed the [configure lab](./1-configure-lab.md#configuring-credentials).
2. Completed the [configure lab](./1-configure.md#configuring-credentials).
3. Completed the [audit lab](./2-audit.md).
## Perform a dry run
@@ -19,7 +19,7 @@ You will perform a dry run for a pipeline in the bootstrapped Azure DevOps proje
- Inspecting the URL to locate the pipeline id <https://dev.azure.com/:organization/:project/_build?definitionId=:pipeline_id>
2. Where do you want to store the result?
- __./tmp/dry-run-lab__. This can be any path within the working directory from which Valet commands are executed.
- __tmp/dry-run__. This can be any path within the working directory from which Valet commands are executed.
### Steps
@@ -27,14 +27,14 @@ You will perform a dry run for a pipeline in the bootstrapped Azure DevOps proje
2. Run the following command from the root directory:
```bash
gh valet dry-run azure-devops pipeline --pipeline-id :pipeline_id --output-dir tmp/dry-run-lab
gh valet dry-run azure-devops pipeline --pipeline-id :pipeline_id --output-dir tmp/dry-run
```
3. The command will list all the files written to disk when the command succeeds.
4. View the converted workflow:
- Find `./tmp/dry-run-lab` in the file explorer pane in your codespace.
- Find `tmp/dry-run` in the file explorer pane in your codespace.
- Click `valet-pipeline1.yml` to open.
## Inspect the output files
The files generated from the `dry-run` command represent the equivalent Actions workflow for the given Azure DevOps pipeline. The Azure DevOps pipeline and converted workflow can be seen below:
@@ -63,7 +63,7 @@ steps:
<details>
<summary><em>Converted workflow 👇</em></summary>
```yaml
name: valet-bootstrap/pipelines/valet-pipeline1
on:
azure_devops/5-custom-transformers.md
+7 -7
View File
@@ -10,9 +10,9 @@ In this lab we will build upon the `dry-run` command to override Valet's default
## Prerequisites
1. Followed the steps [here](./readme.md#configure-your-codespace) to set up your GitHub Codespaces environment and bootstrap an Azure DevOps project.
2. Completed the [configure lab](./1-configure-lab.md#configuring-credentials).
2. Completed the [configure lab](./1-configure.md#configuring-credentials).
3. Completed the [audit lab](./2-audit.md).
4. Completed the [dry-run lab](./3-dry-run.md).
4. Completed the [dry-run lab](./4-dry-run.md).
## Perform a dry run
@@ -25,7 +25,7 @@ You will perform a dry-run for a pipeline in the bootstrapped Azure DevOps proje
- Inspecting the URL to locate the pipeline id <https://dev.azure.com/:organization/:project/_build?definitionId=:pipeline_id>
2. Where do you want to store the result?
- __./tmp/dry-run-lab__. This can be any path within the working directory from which Valet commands are executed.
- __tmp/dry-run__. This can be any path within the working directory from which Valet commands are executed.
### Steps
@@ -33,12 +33,12 @@ You will perform a dry-run for a pipeline in the bootstrapped Azure DevOps proje
2. Run the following command from the root directory:
```bash
gh valet dry-run azure-devops pipeline --pipeline-id :pipeline_id --output-dir tmp/dry-run-lab
gh valet dry-run azure-devops pipeline --pipeline-id :pipeline_id --output-dir tmp/dry-run
```
3. The command will list all the files written to disk when the command succeeds.
4. View the converted workflow:
- Find `./tmp/dry-run-lab` in the file explorer pane in your codespace.
- Find `tmp/dry-run` in the file explorer pane in your codespace.
- Click `valet-custom-transformer-example.yml` to open.
The converted workflow that is generated can be seen below:
@@ -77,7 +77,7 @@ jobs:
</details>
_Note_: You can refer to the previous [lab](./3-dry-run.md) to learn about the fundamentals of the `dry-run` command.
_Note_: You can refer to the previous [lab](./4-dry-run.md) to learn about the fundamentals of the `dry-run` command.
## Custom transformers for build steps
@@ -127,7 +127,7 @@ This method can use any valid ruby syntax and should return a `Hash` that repres
Now you can perform another `dry-run` command and use the `--custom-transformers` CLI option to provide this custom transformer. Run the following command within your codespace terminal:
```bash
gh valet dry-run azure-devops pipeline --pipeline-id :pipeline_id --output-dir tmp/dry-run-lab --custom-transformers transformers.rb
gh valet dry-run azure-devops pipeline --pipeline-id :pipeline_id --output-dir tmp/dry-run --custom-transformers transformers.rb
```
Open the workflow that is generated and inspect the contents. Now the `DotnetCoreCLI@2` steps are converted using the customized behavior!
azure_devops/6-migrate.md
+8 -8
View File
@@ -5,9 +5,9 @@ In this lab, you will use the `migrate` command to convert an Azure DevOps pipel
## Prerequisites
1. Followed the steps [here](./readme.md#configure-your-codespace) to set up your GitHub Codespaces environment and bootstrap an Azure DevOps project.
2. Completed the [configure lab](./1-configure-lab.md#configuring-credentials).
3. Completed the [dry-run lab](./3-dry-run.md).
4. Completed the [custom transformers lab](./4-custom-transformers.md).
2. Completed the [configure lab](./1-configure.md#configuring-credentials).
3. Completed the [dry-run lab](./4-dry-run.md).
4. Completed the [custom transformers lab](./5-custom-transformers.md).
## Performing a migration
@@ -19,7 +19,7 @@ Answer the following questions before running a `migrate` command:
- Selecting the pipeline with the name "valet-pipeline2"
- Inspecting the URL to locate the pipeline id <https://dev.azure.com/:organization/:project/_build?definitionId=:pipeline_id>
2. Where do you want to store the logs?
- __./tmp/migrate__
- __tmp/migrate__
3. What is the URL for the GitHub repository to add the workflow to?
- __this repository__. The URL should follow the pattern <https://github.com/:owner/:repo> with `:owner` and `:repo` replaced with your values.
@@ -28,14 +28,14 @@ Answer the following questions before running a `migrate` command:
1. Run the following `migrate` command in the codespace terminal:
```bash
gh valet migrate azure-devops pipeline --pipeline-id :pipeline_id --target-url https://github.com/:owner/:repo --output-dir ./tmp/migrate
gh valet migrate azure-devops pipeline --pipeline-id :pipeline_id --target-url https://github.com/:owner/:repo --output-dir tmp/migrate
```
2. The command will write the URL to the pull request that was created when the command succeeds.
```bash
➜ gh valet migrate azure-devops pipeline --pipeline-id 8 --target-url https://github.com/ethanis/labs --output-dir ./tmp/migrate
[2022-09-07 20:25:08] Logs: 'tmp/dry-run-lab/log/valet-20220907-202508.log'
```console
$ gh valet migrate azure-devops pipeline --pipeline-id 8 --target-url https://github.com/ethanis/labs --output-dir tmp/migrate
[2022-09-07 20:25:08] Logs: 'tmp/dry-run/log/valet-20220907-202508.log'
[2022-09-07 20:25:13] Pull request: 'https://github.com/ethanis/labs/pull/42'
```
azure_devops/readme.md
+23 -21
View File
@@ -12,28 +12,29 @@ These steps **must** be completed prior to starting other labs.
1. Start a new codespace.
- Click the `Code` button on your repository's landing page.
- Click the `Codespaces` tab.
- Click `Create codespaces on main` to create the codespace.
- After the codespace has initialized there will be a terminal present.
- Click the `Code` button on your repository's landing page.
- Click the `Codespaces` tab.
- Click `Create codespaces on main` to create the codespace.
- After the codespace has initialized there will be a terminal present.
2. Verify the Valet CLI is installed and working. More information on the Valet extension for the official GitHub CLI can be found [here](https://github.com/github/gh-valet).
- Run the following command in the codespace terminal:
- Run the following command in the codespace terminal:
```bash
gh valet version
```
```bash
gh valet version
```
- Verify the output is similar to below.
```bash
gh version 2.14.3 (2022-07-26)
gh valet github/gh-valet v0.1.12
valet-cli unknown
```
- Verify the output is similar to below.
- If `gh valet version` did not produce similar output, please refer to the troubleshooting [guide](#troubleshoot-the-valet-cli).
```console
$ gh valet version
gh version 2.14.3 (2022-07-26)
gh valet github/gh-valet v0.1.12
valet-cli unknown
```
- If `gh valet version` did not produce similar output, please refer to the troubleshooting [guide](#troubleshoot-the-valet-cli).
## Bootstrap your Azure DevOps organization
@@ -77,10 +78,10 @@ Perform the following labs to learn how to migrate Azure DevOps pipelines to Git
1. [Configure credentials for Valet](1-configure.md)
2. [Perform an audit of an Azure DevOps project](2-audit.md)
3. [Perform a dry-run migration of an Azure DevOps pipeline](3-dry-run.md)
4. [Use custom transformers to customize Valet's behavior](4-custom-transformers.md)
5. [Perform a production migration of a Azure DevOps pipeline](5-migrate.md)
6. [Forecast potential build runner usage](6-forecast.md)
3. [Forecast potential build runner usage](3-forecast.md)
4. [Perform a dry-run migration of an Azure DevOps pipeline](4-dry-run.md)
5. [Use custom transformers to customize Valet's behavior](5-custom-transformers.md)
6. [Perform a production migration of a Azure DevOps pipeline](6-migrate.md)
## Troubleshoot the Valet CLI
@@ -95,7 +96,8 @@ The CLI extension for Valet can be manually installed by following these steps:
- Verify the result of the install contains:
```bash
```console
$ gh extension install github/gh-valet
✓ Installed extension github/gh-valet
```
gitlab/1-configure.md
+3 -1
View File
@@ -7,6 +7,7 @@ You will need to complete all of the setup instructions [here](./readme.md#confi
## Configuring credentials
1. Run the setup script in the codespace terminal to ensure the GitLab server is ready:
```bash
./gitlab/bootstrap/setup.sh
```
@@ -59,7 +60,8 @@ To verify your environment is configured correctly, run the `update` CLI command
2. You should see a confirmation that you were logged into the GitHub Container Registry and Valet was updated to the latest version.
```bash
```console
$ gh valet update
Login Succeeded
latest: Pulling from valet-customers/valet-cli
Digest: sha256:a7d00dee8a37e25da59daeed44b1543f476b00fa2c41c47f48deeaf34a215bbb
gitlab/2-audit.md
+1 -1
View File
@@ -17,7 +17,7 @@ You will be performing an audit against your preconfigured GitLab server. Answer
- __valet__. In this example you will be auditing the `valet` group. In the future, you could add additional groups and subgroups to the audit command.
2. Where do you want to store the result?
- __./tmp/audit__. This can be any path within the working directory from which Valet commands are executed.
- __tmp/audit__. This can be any path within the working directory from which Valet commands are executed.
### Steps
gitlab/3-forecast.md
+5 -5
View File
@@ -5,7 +5,7 @@ In this lab you will use the `forecast` command to forecast potential GitHub Act
## Prerequisites
1. Followed the steps [here](./readme.md#configure-your-codespace) to set up your GitHub Codespaces environment and start a GitLab server.
2. Completed the [configure lab](./1-configure-lab.md#configuring-credentials).
2. Completed the [configure lab](./1-configure.md#configuring-credentials).
## Perform a forecast
@@ -16,7 +16,7 @@ Answer the following questions before running the `forecast` command:
2. What is the date you want to start forecasting from?
- **2022-08-02**. This date is needed as it is prior to when the data was seeded in GitLab for these labs. This value defaults to the date one week ago, however, you should use a start date that will show a representative view of typical usage.
3. Where do you want to store the results?
- **./tmp/forecast_reports**
- **tmp/forecast**
### Steps
@@ -24,7 +24,7 @@ Answer the following questions before running the `forecast` command:
2. Run the following command from the root directory:
```bash
gh valet forecast gitlab --output-dir ./tmp/forecast_reports --namespace valet --start-date 2022-08-02
gh valet forecast gitlab --output-dir tmp/forecast --namespace valet --start-date 2022-08-02
```
3. The command will list all the files written to disk when the command succeeds.
@@ -33,7 +33,7 @@ Answer the following questions before running the `forecast` command:
## Review the forecast report
The forecast report, logs, and completed job data will be located within the `tmp/forecast_reports` folder.
The forecast report, logs, and completed job data will be located within the `tmp/forecast` folder.
1. Find the `forecast_report.md` file in the file explorer.
2. Right-click the `forecast_report.md` file and select `Open Preview`.
@@ -92,7 +92,7 @@ You can use the `--source-file-path` CLI option to combine data from multiple re
Run the following command from within the codespace terminal:
```bash
gh valet forecast --source-file-path tmp/**/jobs/*.json --output-dir tmp/combined-forecast
gh valet forecast --source-file-path tmp/**/jobs/*.json --output-dir tmp/forecast-combined
```
You can now inspect the output of the command to see a forecast report using all of the files matching the `tmp/**/jobs/*.json` pattern.
gitlab/4-dry-run.md
+7 -6
View File
@@ -5,7 +5,7 @@ In this lab you will use the `dry-run` command to convert a GitLab pipeline to i
## Prerequisites
1. Followed the steps [here](./readme.md#configure-your-codespace) to set up your Codespace environment and start a GitLab server.
2. Completed the [configure lab](./1-configure-lab.md#configuring-credentials).
2. Completed the [configure lab](./1-configure.md#configuring-credentials).
3. Completed the [audit lab](./2-audit.md).
## Perform a dry run
@@ -19,7 +19,7 @@ You will be performing a dry run against a pipeline in your preconfigured GitLab
- __Valet__
3. Where do you want to store the result?
- __./tmp/dry-run-lab__. This can be any path within the working directory from which Valet commands are executed.
- __tmp/dry-run__. This can be any path within the working directory from which Valet commands are executed.
### Steps
@@ -27,7 +27,7 @@ You will be performing a dry run against a pipeline in your preconfigured GitLab
2. Run the following command from the root directory:
```bash
gh valet dry-run gitlab --output-dir ./tmp/dry-run-lab --namespace valet --project basic-pipeline-example
gh valet dry-run gitlab --output-dir tmp/dry-run --namespace valet --project basic-pipeline-example
```
3. The command will list all the files written to disk when the command succeeds.
@@ -35,9 +35,9 @@ You will be performing a dry run against a pipeline in your preconfigured GitLab
![img](https://user-images.githubusercontent.com/18723510/184173635-aec28d1c-8c61-4dcf-a743-f86cbdc836c5.png)
4. View the converted workflow:
- Find `./tmp/dry-run/valet` in the file explorer pane in your codespace.
- Find `tmp/dry-run/valet` in the file explorer pane in your codespace.
- Click `basic-pipeline-example.yml` to open.
## Inspect the output files
The files generated from the `dry-run` command represent the equivalent Actions workflow for the given GitLab pipeline. The GitLab pipeline and converted workflow can be seen below:
@@ -98,7 +98,7 @@ deploy_b:
<details>
<summary><em>Converted workflow 👇</em></summary>
```yaml
name: valet/basic-pipeline-example
on:
@@ -196,6 +196,7 @@ jobs:
- run: echo "test stage complete. It will start at about the same time as deploy_a."
- run: sleep 400
```
</details>
Despite these two pipelines using different syntax they will function equivalently.
gitlab/5-custom-transformers.md
+3 -3
View File
@@ -10,8 +10,8 @@ In this lab you will build upon the `dry-run` command to override Valet's defaul
## Prerequisites
1. Followed the steps [here](./readme.md#configure-your-codespace) to set up your GitHub Codespaces environment and start you GitLab server.
2. Completed the [configure lab](./1-configure-lab.md#configuring-credentials).
3. Completed the [dry-run lab](./3-dry-run.md).
2. Completed the [configure lab](./1-configure.md#configuring-credentials).
3. Completed the [dry-run lab](./4-dry-run.md).
## Perform a dry-run
@@ -53,7 +53,7 @@ jobs:
</details>
_Note_: You can refer to the previous [lab](./3-dry-run.md) to learn about the fundamentals of the `dry-run` command.
_Note_: You can refer to the previous [lab](./4-dry-run.md) to learn about the fundamentals of the `dry-run` command.
## Custom transformers for an unknown step
gitlab/6-migrate.md
+6 -6
View File
@@ -5,9 +5,9 @@ In this lab, you will use the `migrate` command to convert a GitLab pipeline and
## Prerequisites
1. Followed the steps [here](./readme.md#configure-your-codespace) to set up your GitHub Codespaces environment and start a GitLab server.
2. Completed the [configure lab](./1-configure-lab.md#configuring-credentials).
3. Completed the [dry-run lab](./3-dry-run.md).
4. Completed the [custom transformers lab](./4-custom-transformers.md).
2. Completed the [configure lab](./1-configure.md#configuring-credentials).
3. Completed the [dry-run lab](./4-dry-run.md).
4. Completed the [custom transformers lab](./5-custom-transformers.md).
## Performing a migration
@@ -18,7 +18,7 @@ Answer the following questions before running a `migrate` command:
2. What is the namespace for that project?
- __Valet__
3. Where do you want to store the logs?
- __./tmp/migrate__
- __tmp/migrate__
4. What is the URL for the GitHub repository to add the workflow to?
- __this repository__. The URL should should follow the pattern <https://github.com/:owner/:repo> with `:owner` and `:repo` replaced with your values.
@@ -27,7 +27,7 @@ Answer the following questions before running a `migrate` command:
1. Run the following `migrate` command in the codespace terminal:
```bash
gh valet migrate gitlab --target-url https://github.com/:owner/:repo --output-dir ./tmp/migrate --namespace valet --project rails-example
gh valet migrate gitlab --target-url https://github.com/:owner/:repo --output-dir tmp/migrate --namespace valet --project rails-example
```
2. The command will write the URL to the pull request that was created when the command succeeds.
@@ -43,7 +43,7 @@ The first thing to notice about the pull request is that there is a list of manu
Next, you can inspect the "Files changed" in this pull request and see the converted workflow that is being added. Any additional changes or code reviews that were needed should be done in this pull request.
Finally, you can merge the pull request once your review has completed. You can then view the workflow running by selecting the "Actions" menu in the top navigation bar in GitHub.
![img](https://user-images.githubusercontent.com/18723510/184960870-590b1a28-422f-4350-9ec0-0423bf7ad445.png)
At this point, the migration has completed and you have successfully migrated a GitLab pipeline to Actions!
gitlab/readme.md
+34 -31
View File
@@ -12,48 +12,50 @@ These steps **must** be completed prior to starting other labs.
1. Start a new codespace
- Click the `Code` button on your repository's landing page.
- Click the `Codespaces` tab.
- Click `Create codespaces on main` to create the codespace.
- After the codespace has initialized there will be a terminal present.
- Click the `Code` button on your repository's landing page.
- Click the `Codespaces` tab.
- Click `Create codespaces on main` to create the codespace.
- After the codespace has initialized there will be a terminal present.
2. Verify the Valet CLI is installed and working. More information on the Valet extension for the official GitHub CLI can be found [here](https://github.com/github/gh-valet).
- Run the following command in the codespace terminal:
- Run the following command in the codespace terminal:
```bash
gh valet version
```
```bash
gh valet version
```
- Verify the output is similar to below.
```bash
gh version 2.14.3 (2022-07-26)
gh valet github/gh-valet v0.1.12
valet-cli unknown
```
- Verify the output is similar to below.
- If `gh valet version` did not produce similar output, please refer to the troubleshooting [guide](#troubleshoot-the-valet-cli).
```console
$ gh valet version
gh version 2.14.3 (2022-07-26)
gh valet github/gh-valet v0.1.12
valet-cli unknown
```
- If `gh valet version` did not produce similar output, please refer to the troubleshooting [guide](#troubleshoot-the-valet-cli).
## Bootstrap a GitLab server
1. Execute the GitLab setup script that will start a container with GitLab running inside of it. The script should be executed when starting a new codespace or restarting an existing one.
- Run the following command from the codespace terminal:
```bash
./gitlab/bootstrap/setup.sh
```
- Run the following command from the codespace terminal:
- After some time, a pop-up box should appear with a link to the URL for your GitLab server.
- You can also access the URL by going to the `Ports` tab in your terminal. Right-click the URL listed under the `Local Address` and click the `Open in Browser` tab.
```bash
./gitlab/bootstrap/setup.sh
```
- After some time, a pop-up box should appear with a link to the URL for your GitLab server.
- You can also access the URL by going to the `Ports` tab in your terminal. Right-click the URL listed under the `Local Address` and click the `Open in Browser` tab.
2. Open the GitLab server in your browser and use the following credentials to authenticate:
- Username: `root`
- Password: `valet-labs!`
- Username: `root`
- Password: `valet-labs!`
- Once authenticated, you should see a GitLab server with a few predefined pipelines in the `valet` group.
3. Once authenticated, you should see a GitLab server with a few predefined pipelines in the `valet` group.
## Labs for GitLab
@@ -61,10 +63,10 @@ Perform the following labs to learn more about Actions migrations with Valet:
1. [Configure credentials for Valet](1-configure.md)
2. [Perform an audit on GitLab pipelines](2-audit.md)
3. [Perform a dry-run migration of a GitLab pipeline](3-dry-run.md)
4. [Use custom transformers to customize Valet's behavior](4-custom-transformers.md)
5. [Perform a production migration of a GitLab pipeline](5-migrate.md)
6. [Forecast potential build runner usage](6-forecast.md)
3. [Forecast potential build runner usage](3-forecast.md)
4. [Perform a dry-run migration of a GitLab pipeline](4-dry-run.md)
5. [Use custom transformers to customize Valet's behavior](5-custom-transformers.md)
6. [Perform a production migration of a GitLab pipeline](6-migrate.md)
## Troubleshoot the Valet CLI
@@ -79,7 +81,8 @@ The CLI extension for Valet can be manually installed by following these steps:
- Verify the result of the install contains:
```bash
```console
$ gh extension install github/gh-valet
✓ Installed extension github/gh-valet
```
jenkins/1-configure.md
+2 -1
View File
@@ -54,7 +54,8 @@ To verify your environment is configured correctly, run the `update` CLI command
2. You should see a confirmation that you were logged into the GitHub Container Registry and Valet was updated to the latest version.
```bash
```console
$ gh valet update
Login Succeeded
latest: Pulling from valet-customers/valet-cli
Digest: sha256:a7d00dee8a37e25da59daeed44b1543f476b00fa2c41c47f48deeaf34a215bbb
jenkins/2-audit.md
+135 -6
View File
@@ -17,7 +17,7 @@ You will be performing an audit against your preconfigured Jenkins server. Answe
- In this example you will audit the entire Jenkins instance, but in the future if you wanted to configure a specific folder to be audited add the `-f <folder_path>` flag to the `audit` command.
2. Where do you want to store the result?
- __./tmp/audit__. This can be any path within the working directory from which Valet commands are executed.
- __tmp/audit__. This can be any path within the working directory from which Valet commands are executed.
### Steps
@@ -30,7 +30,30 @@ You will be performing an audit against your preconfigured Jenkins server. Answe
3. The command will list all the files written to disk in green when the command succeeds.
![img](https://user-images.githubusercontent.com/19557880/184682347-b19760fa-36a6-423e-a445-bb30eda5ac59.png)
```console
$ gh valet audit jenkins --output-dir tmp/audit
[2022-08-20 22:08:20] Logs: 'tmp/audit/log/valet-20220916-015817.log'
[2022-08-20 22:08:20] Auditing 'http://localhost:8080/'
[2022-08-20 22:08:20] Output file(s):==========================================|
[2022-08-20 22:08:20] tmp/audit/demo_pipeline.yml
[2022-08-20 22:08:20] tmp/audit/demo_pipeline.config.json
[2022-08-20 22:08:20] tmp/audit/demo_pipeline.jenkinsfile
[2022-08-20 22:08:20] tmp/audit/groovy_script.error.txt
[2022-08-20 22:08:20] tmp/audit/groovy_script.config.json
[2022-08-20 22:08:20] tmp/audit/monas_dev_work/monas_freestyle.yml
[2022-08-20 22:08:20] tmp/audit/monas_dev_work/monas_freestyle.config.json
[2022-08-20 22:08:20] tmp/audit/monas_dev_work/monas_pipeline.yml
[2022-08-20 22:08:20] tmp/audit/monas_dev_work/monas_pipeline.config.json
[2022-08-20 22:08:20] tmp/audit/monas_dev_work/monas_pipeline.jenkinsfile
[2022-08-20 22:08:20] tmp/audit/test_freestyle_project.yml
[2022-08-20 22:08:20] tmp/audit/test_freestyle_project.config.json
[2022-08-20 22:08:20] tmp/audit/test_mutlibranch_pipeline.config.json
[2022-08-20 22:08:20] tmp/audit/test_pipeline.yml
[2022-08-20 22:08:20] tmp/audit/test_pipeline.config.json
[2022-08-20 22:08:20] tmp/audit/test_pipeline.jenkinsfile
[2022-08-20 22:08:20] tmp/audit/workflow_usage.csv
[2022-08-20 22:08:20] tmp/audit/audit_summary.md
```
## Inspect the output files
@@ -46,7 +69,28 @@ The audit summary, logs, config files, jenkinsfiles, and transformed workflows w
The pipeline summary section contains high level statistics regarding the conversion rate done by Valet:
![img](https://user-images.githubusercontent.com/19557880/184683664-81985baf-5c03-4765-a067-f4023416e3ea.png)
```md
## Pipelines
Total: **7**
- Successful: **3 (42%)**
- Partially successful: **3 (42%)**
- Unsupported: **1 (14%)**
- Failed: **0 (0%)**
### Job types
Supported: **6 (85%)**
- flow-definition: **3**
- project: **2**
- org.jenkinsci.plugins.workflow.multibranch.WorkflowMultiBranchProject: **1**
Unsupported: **1 (14%)**
- scripted: **1**
```
Here are some key terms in the “Pipelines” section in the above example:
@@ -67,7 +111,35 @@ The "Job types" section will summarize which types of pipelines are being used a
The build steps summary section presents an overview of the individual build steps that are used across all pipelines and how many were automatically converted by Valet.
![img](https://user-images.githubusercontent.com/19557880/184684062-69ab0bde-5e32-45f8-a7dd-ed4655872975.png)
```md
### Build steps
Total: **17**
Known: **13 (76%)**
- echo: **6**
- hudson.tasks.Shell: **3**
- junit: **2**
- archiveArtifacts: **1**
- sh: **1**
Unknown: **3 (17%)**
- sleep: **2**
- hudson.plugins.git.GitPublisher: **1**
Unsupported: **1 (5%)**
- hudson.tasks.Mailer: **1**
Actions: **22**
- run: **10**
- actions/checkout@v2: **9**
- EnricoMi/publish-unit-test-result-action@v1.7: **2**
- actions/upload-artifact@v2: **1**
```
Here are some key terms in the "Build steps" section in the above example:
@@ -86,7 +158,21 @@ There is an equivalent breakdown of build triggers, environment variables, and o
The manual tasks summary section presents an overview of the manual tasks that you will need to perform that Valet is not able to complete automatically.
![img](https://user-images.githubusercontent.com/19557880/184684249-9accfd94-c2df-4891-af56-dcff66beb557.png)
```md
### Manual tasks
Total: **9**
Secrets: **2**
- `${{ secrets.SECRET_TEST_EXPRESSION_VAR }}`: **1**
- `${{ secrets.EXPRESSION_FIRST_VAR }}`: **1**
Self hosted runners: **7**
- `TeamARunner`: **6**
- `DemoRunner`: **1**
```
Here are some key terms in the “Manual tasks” section in the above example:
@@ -97,7 +183,50 @@ Here are some key terms in the “Manual tasks” section in the above example:
The final section of the audit report provides a manifest of all of the files that are written to disk during the audit. These files include:
![img](https://user-images.githubusercontent.com/19557880/184684416-b3db774e-4ab8-46e0-91ad-e503632df5cb.png)
```md
### Successful
#### demo_pipeline
- [demo_pipeline.yml](demo_pipeline.yml)
- [demo_pipeline.config.json](demo_pipeline.config.json)
- [demo_pipeline.jenkinsfile](demo_pipeline.jenkinsfile)
#### monas_dev_work/monas_freestyle
- [monas_dev_work/monas_freestyle.yml](monas_dev_work/monas_freestyle.yml)
- [monas_dev_work/monas_freestyle.config.json](monas_dev_work/monas_freestyle.config.json)
#### test_mutlibranch_pipeline
- [test_mutlibranch_pipeline.config.json](test_mutlibranch_pipeline.config.json)
### Partially successful
#### monas_dev_work/monas_pipeline
- [monas_dev_work/monas_pipeline.yml](monas_dev_work/monas_pipeline.yml)
- [monas_dev_work/monas_pipeline.config.json](monas_dev_work/monas_pipeline.config.json)
- [monas_dev_work/monas_pipeline.jenkinsfile](monas_dev_work/monas_pipeline.jenkinsfile)
#### test_freestyle_project
- [test_freestyle_project.yml](test_freestyle_project.yml)
- [test_freestyle_project.config.json](test_freestyle_project.config.json)
#### test_pipeline
- [test_pipeline.yml](test_pipeline.yml)
- [test_pipeline.config.json](test_pipeline.config.json)
- [test_pipeline.jenkinsfile](test_pipeline.jenkinsfile)
### Failed
#### groovy_script
- [groovy_script.error.txt](groovy_script.error.txt)
- [groovy_script.config.json](groovy_script.config.json)
```
Each pipeline will have a variety of files written that include:
jenkins/3-forecast.md
+46 -23
View File
@@ -5,7 +5,7 @@ In this lab you will use the `forecast` command to forecast potential GitHub Act
## Prerequisites
1. Followed the steps [here](./readme.md#configure-your-codespace) to set up your GitHub Codespaces environment and start a Jenkins server.
2. Completed the [configure lab](./1-configure-lab.md#configuring-credentials).
2. Completed the [configure lab](./1-configure.md#configuring-credentials).
## Perform a forecast
@@ -18,7 +18,7 @@ Answer the following questions before running the `forecast` command:
- __2022-08-02__. This date is needed as it is prior to when the data was seeded in Jenkins for these labs. This value defaults to the date one week ago, however, you should use a start date that will show a representative view of typical usage.
3. Where do you want to store the results?
- `./tmp/forecast_reports`
- `tmp/forecast`
### Steps
@@ -26,16 +26,23 @@ Answer the following questions before running the `forecast` command:
2. Run the following command from the root directory:
```bash
gh valet forecast jenkins --output-dir ./tmp/forecast_reports --start-date 2022-08-02
gh valet forecast jenkins --output-dir tmp/forecast --start-date 2022-08-02
```
3. The command will list all the files written to disk when the command succeeds.
![img](https://user-images.githubusercontent.com/19557880/186223037-18556c82-5a29-4434-bc17-4b906d704967.png)
```console
$ gh valet forecast jenkins --output-dir tmp/forecast --start-date 2022-08-02
[2022-08-20 22:08:20] Logs: 'tmp/forecast/log/valet-20220916-021004.log'
[2022-08-20 22:08:20] Forecasting 'http://localhost:8080/'
[2022-08-20 22:08:20] Output file(s):
[2022-08-20 22:08:20] tmp/forecast/jobs/09-16-2022-02-10_jobs_0.json
[2022-08-20 22:08:20] tmp/forecast/forecast_report.md
```
## Review the forecast report
The forecast report, logs, and completed job data will be located within the `tmp/forecast_reports` folder.
The forecast report, logs, and completed job data will be located within the `tmp/forecast` folder.
1. Find the `forecast_report.md` file in the file explorer.
2. Right-click the `forecast_report.md` file and select `Open Preview`.
@@ -46,30 +53,30 @@ The forecast report, logs, and completed job data will be located within the `tm
The "Total" section of the forecast report contains high level statistics related to all the jobs completed after the `--start-date` CLI option:
```md
- Job count: __73__
- Pipeline count: __6__
- Job count: **73**
- Pipeline count: **6**
- Execution time
- Total: __27,057 minutes__
- Median: __2 minutes__
- P90: __19 minutes__
- Min: __0 minutes__
- Max: __15,625 minutes__
- Total: **27,057 minutes**
- Median: **2 minutes**
- P90: **19 minutes**
- Min: **0 minutes**
- Max: **15,625 minutes**
- Queue time
- Median: __0 minutes__
- P90: __0 minutes__
- Min: __0 minutes__
- Max: __0 minutes__
- Median: **0 minutes**
- P90: **0 minutes**
- Min: **0 minutes**
- Max: **0 minutes**
- Concurrent jobs
- Median: __1__
- P90: __3__
- Min: __0__
- Max: __29__
- Median: **1**
- P90: **3**
- Min: **0**
- Max: **29**
```
Here are some key terms of items defined in the forecast report:
@@ -85,16 +92,32 @@ Additionally, these metrics are defined for each queue of runners defined in Jen
## Forecasting multiple providers
You can examine the available options for the `forecast` command by running `gh valet forecast --help`. When you do this you will see the `--source-file-path` option:
You can examine the available options for the `forecast` command by running `gh valet forecast jenkins --help`. When you do this you will see the `--source-file-path` option:
![img](https://user-images.githubusercontent.com/19557880/186263140-f02c6cab-7979-417c-bdfe-b9590e9c5597.png)
```console
$ gh valet forecast jenkins --help
Options:
-u, --jenkins-instance-url <jenkins-instance-url> The URL of the Jenkins CI instance.
-n, --jenkins-username <jenkins-username> Username for the Jenkins instance.
-t, --jenkins-access-token <jenkins-access-token> Access token for the Jenkins instance.
-f, --folders <folders> Folders to forecast in the instance
--source-file-path <source-file-path> The file path(s) to existing jobs data.
-o, --output-dir <output-dir> (REQUIRED) The location for any output files.
--start-date <start-date> The start date of the forecast analysis in YYYY-MM-DD format. [default: 9/9/2022 2:14:15 AM]
--time-slice <time-slice> The time slice in seconds to use for computing concurrency metrics. [default: 60]
--credentials-file <credentials-file> The file containing the credentials to use.
--no-telemetry Boolean value to disallow telemetry.
--no-ssl-verify Disable ssl certificate verification.
--no-http-cache Disable caching of http responses.
-?, -h, --help Show help and usage information
```
You can use the `--source-file-path` CLI option to combine data from multiple reports into a single report. This becomes useful if you use multiple CI/CD providers and wanted to get a holistic view of the runner usage. This works by using the `.json` files generated by `forecast` commands as space-delimited values for the `--source-file-path` CLI option. Optionally, this value could be a glob pattern to dynamically specify the list of files (e.g. `**/*.json`).
Run the following command from within the codespace terminal:
```bash
gh valet forecast --source-file-path tmp/**/jobs/*.json --output-dir tmp/combined-forecast
gh valet forecast --source-file-path tmp/**/jobs/*.json --output-dir tmp/forecast-combined
```
You can now inspect the output of the command to see a forecast report using all of the files matching the `tmp/**/jobs/*.json` pattern.
jenkins/4-dry-run.md
+11 -6
View File
@@ -5,7 +5,7 @@ In this lab you will use the `dry-run` command to convert a Jenkins pipeline to
## Prerequisites
1. Followed the steps [here](./readme.md#configure-your-codespace) to set up your GitHub Codespaces environment and start a Jenkins server.
2. Completed the [configure lab](./1-configure-lab.md#configuring-credentials).
2. Completed the [configure lab](./1-configure.md#configuring-credentials).
3. Completed the [audit lab](./2-audit.md).
## Perform a dry run
@@ -19,7 +19,7 @@ You will be performing a dry run against a pipeline in your preconfigured Jenkin
- __<http://localhost:8080/job/test_pipeline>__
3. Where do you want to store the result?
- __./tmp/dry-run-lab__. This can be any path within the working directory from which Valet commands are executed.
- __tmp/dry-run__. This can be any path within the working directory from which Valet commands are executed.
### Steps
@@ -27,15 +27,20 @@ You will be performing a dry run against a pipeline in your preconfigured Jenkin
2. Run the following command from the root directory:
```bash
gh valet dry-run jenkins --source-url http://localhost:8080/job/test_pipeline --output-dir .tmp/jenkins/dry-run
gh valet dry-run jenkins --source-url http://localhost:8080/job/test_pipeline --output-dir tmp/dry-run
```
3. The command will list all the files written to disk when the command succeeds.
![img](https://user-images.githubusercontent.com/19557880/184935603-5c2d4dfe-66ef-4cb1-9398-e96954ca72e3.png)
```console
$ gh valet dry-run jenkins --source-url http://localhost:8080/job/test_pipeline --output-dir tmp/dry-run
[2022-08-20 22:08:20] Logs: 'tmp/dry-run/log/valet-20220916-022338.log'
[2022-08-20 22:08:20] Output file(s):
[2022-08-20 22:08:20] tmp/dry-run/test_pipeline.yml
```
4. View the converted workflow:
- Find `./tmp/dry-run` in the file explorer pane in your codespace.
- Find `tmp/dry-run` in the file explorer pane in your codespace.
- Click `test_pipeline.yml` to open
## Inspect the output files
@@ -66,7 +71,7 @@ pipeline {
}
stage('test') {
steps{
junit '**/target/*.xml'
junit '**/target/*.xml'
}
}
}
jenkins/5-custom-transformers.md
+14 -8
View File
@@ -10,15 +10,15 @@ In this lab you will build upon the `dry-run` command to override Valet's defaul
## Prerequisites
1. Followed the steps [here](./readme.md#configure-your-codespace) to set up your GitHub Codespaces environment and start a Jenkins server.
2. Completed the [configure lab](./1-configure-lab.md#configuring-credentials).
3. Completed the [dry-run lab](./3-dry-run.md).
2. Completed the [configure lab](./1-configure.md#configuring-credentials).
3. Completed the [dry-run lab](./4-dry-run.md).
## Perform a dry-run
You will be performing a `dry-run` command to inspect the workflow that is converted by default. Run the following command within the codespace terminal:
```bash
gh valet dry-run jenkins --source-url http://localhost:8080/job/test_pipeline --output-dir tmp/jenkins/dry-run
gh valet dry-run jenkins --source-url http://localhost:8080/job/test_pipeline --output-dir tmp/dry-run
```
The converted workflow that is generated by the above command can be seen below:
@@ -71,7 +71,7 @@ jobs:
</details>
_Note_: You can refer to the previous [lab](./3-dry-run.md) to learn about the fundamentals of the `dry-run` command.
_Note_: You can refer to the previous [lab](./4-dry-run.md) to learn about the fundamentals of the `dry-run` command.
## Custom transformers for an unknown step
@@ -114,7 +114,7 @@ This method can use any valid ruby syntax and should return a `Hash` that repres
Now you can perform another `dry-run` command and use the `--custom-transformers` CLI option to provide this custom transformer. Run the following command within your codespace terminal:
```bash
gh valet dry-run jenkins --source-url http://localhost:8080/job/test_pipeline --output-dir tmp/jenkins/dry-run --custom-transformers transformers.rb
gh valet dry-run jenkins --source-url http://localhost:8080/job/test_pipeline --output-dir tmp/dry-run --custom-transformers transformers.rb
```
Open the workflow that is generated and inspect the contents. Now the `sleep` step is converted and uses the customized behavior!
@@ -160,7 +160,13 @@ end
Now, we can perform another `dry-run` command with the `--custom-transformers` CLI option. The output of the `dry-run` command should look similar to this:
![img](https://user-images.githubusercontent.com/19557880/186782050-65ece0c4-52a3-4f88-818f-0f860c50c2b7.png)
```console
$ gh valet dry-run jenkins --source-url http://localhost:8080/job/test_pipeline --output-dir tmp/dry-run --custom-transformers transformers.rb
[2022-08-20 22:08:20] Logs: 'tmp/dry-run/log/valet-20220916-022628.log'
This is the item: {"name"=>"junit", "arguments"=>[{"key"=>"testResults", "value"=>{"isLiteral"=>true, "value"=>"**/target/*.xml"}}]}
[2022-08-20 22:08:20] Output file(s):
[2022-08-20 22:08:20] tmp/dry-run/test_pipeline.yml
```
Now that you know the data structure of `item`, you can access the file path programmatically by editing the custom transformer to the following:
@@ -207,7 +213,7 @@ env "DB_ENGINE", "mongodb"
In this example, the first parameter to the `env` method is the environment variable name and the second is the updated value.
Now you can perform another `dry-run` command with the `--custom-transformers` CLI option. When you open the converted workflow the `DB_ENGINE` environment variable will be set to `mongodb`:
Now you can perform another `dry-run` command with the `--custom-transformers` CLI option. When you open the converted workflow the `DB_ENGINE` environment variable will be set to `mongodb`:
```diff
env:
@@ -234,7 +240,7 @@ runner "TeamARunner", "ubuntu-latest"
In this example, the first parameter to the `runner` method is the Jenkins label and the second is the Actions runner label.
Now you can perform another `dry-run` command with the `--custom-transformers` CLI option. When you open the converted workflow the `runs-on` statement will use the customized runner label:
Now you can perform another `dry-run` command with the `--custom-transformers` CLI option. When you open the converted workflow the `runs-on` statement will use the customized runner label:
```diff
runs-on:
jenkins/6-migrate.md
+10 -6
View File
@@ -5,9 +5,9 @@ In this lab, you will use the `migrate` command to convert a Jenkins pipeline an
## Prerequisites
1. Followed the steps [here](./readme.md#configure-your-codespace) to set up your GitHub Codespaces environment and start a Jenkins server.
2. Completed the [configure lab](./1-configure-lab.md#configuring-credentials).
3. Completed the [dry-run lab](./3-dry-run.md).
4. Completed the [custom transformers lab](./4-custom-transformers.md).
2. Completed the [configure lab](./1-configure.md#configuring-credentials).
3. Completed the [dry-run lab](./4-dry-run.md).
4. Completed the [custom transformers lab](./5-custom-transformers.md).
## Performing a migration
@@ -16,7 +16,7 @@ Answer the following questions before running a `migrate` command:
1. What is the source URL of the pipeline you want to convert?
- __<http://localhost:8080/monas_dev_work/job/monas_freestyle>__
2. Where do you want to store the logs?
- __./tmp/migrate__
- __tmp/migrate__
3. What is the URL for the GitHub repository to add the workflow to?
- __this repository__. The URL should follow the pattern <https://github.com/:owner/:repo> with `:owner` and `:repo` replaced with your values.
@@ -25,12 +25,16 @@ Answer the following questions before running a `migrate` command:
1. Run the following `migrate` command in your codespace terminal:
```bash
gh valet migrate jenkins --target-url https://github.com/:owner/:repo --output-dir ./tmp/migrate --source-url http://localhost:8080/job/monas_dev_work/job/monas_freestyle
gh valet migrate jenkins --target-url https://github.com/:owner/:repo --output-dir tmp/migrate --source-url http://localhost:8080/job/monas_dev_work/job/monas_freestyle
```
2. The command will write the URL to the pull request that was created when the command succeeds.
![img](https://user-images.githubusercontent.com/19557880/185509412-ab64d92d-2a56-4d5a-bbb4-35a41a2ca48c.png)
```console
$ gh valet migrate jenkins --target-url https://github.com/:owner/:repo --output-dir tmp/migrate --source-url http://localhost:8080/job/monas_dev_work/job/monas_freestyle
[2022-08-20 22:08:20] Logs: 'tmp/migrate/log/valet-20220916-014033.log'
[2022-08-20 22:08:20] Pull request: 'https://github.com/:owner/:repo/pull/1'
```
3. Open the generated pull request in a new browser tab.
jenkins/readme.md
+34 -31
View File
@@ -12,48 +12,50 @@ These steps **must** be completed prior to starting other labs.
1. Start a new codespace.
- Click the `Code` button on your repository's landing page.
- Click the `Codespaces` tab.
- Click `Create codespaces on main` to create the codespace.
- After the codespace has initialized there will be a terminal present.
- Click the `Code` button on your repository's landing page.
- Click the `Codespaces` tab.
- Click `Create codespaces on main` to create the codespace.
- After the codespace has initialized there will be a terminal present.
2. Verify the Valet CLI is installed and working. More information on the Valet extension for the official GitHub CLI can be found [here](https://github.com/github/gh-valet).
- Run the following command in the codespace's terminal:
- Run the following command in the codespace's terminal:
```bash
gh valet version
```
```bash
gh valet version
```
- Verify the output is similar to below.
```bash
gh version 2.14.3 (2022-07-26)
gh valet github/gh-valet v0.1.12
valet-cli unknown
```
- Verify the output is similar to below.
- If `gh valet version` did not produce similar output, refer to the troubleshooting [guide](#troubleshoot-the-valet-cli).
```console
$ gh valet version
gh version 2.14.3 (2022-07-26)
gh valet github/gh-valet v0.1.12
valet-cli unknown
```
- If `gh valet version` did not produce similar output, refer to the troubleshooting [guide](#troubleshoot-the-valet-cli).
## Bootstrap a Jenkins server
1. Execute the Jenkins setup script that will start a container with a Jenkins server running inside of it. This script should be executed when starting a new codespace or restarting an existing one.
1. Execute the Jenkins setup script that will start a container with a Jenkins server running inside of it. This script should be executed when starting a new codespace or restarting an existing one.
- Run the following command from the codespace's terminal to start a Jenkins server:
- Run the following command from the codespace's terminal to start a Jenkins server:
```bash
./jenkins/bootstrap/setup.sh
```
```bash
./jenkins/bootstrap/setup.sh
```
- After some time, a pop-up box should appear with a link to the URL for your Jenkins server.
- You can also access the URL by going to the `Ports` tab in your terminal. Right-click the URL listed under the `Local Address` and click the `Open in Browser` tab.
- After some time, a pop-up box should appear with a link to the URL for your Jenkins server.
- You can also access the URL by going to the `Ports` tab in your terminal. Right-click the URL listed under the `Local Address` and click the `Open in Browser` tab.
2. Open the Jenkins server in your browser and use the following credentials to authenticate:
- Username: `admin`
- Password: `password`
- Username: `admin`
- Password: `password`
- Once authenticated, you should see a Jenkins server with a few predefined pipelines.
3. Once authenticated, you should see a Jenkins server with a few predefined pipelines.
## Labs for Jenkins
@@ -61,10 +63,10 @@ Perform the following labs to learn more about Actions migrations with Valet:
1. [Configure credentials for Valet](1-configure.md)
2. [Perform an audit of a Jenkins server](2-audit.md)
3. [Perform a dry-run migration of a Jenkins pipeline](3-dry-run.md)
4. [Use custom transformers to customize Valet's behavior](4-custom-transformers.md)
5. [Perform a production migration of a Jenkins pipeline](5-migrate.md)
6. [Forecast potential build runner usage](6-forecast.md)
3. [Forecast potential build runner usage](3-forecast.md)
4. [Perform a dry-run migration of a Jenkins pipeline](4-dry-run.md)
5. [Use custom transformers to customize Valet's behavior](5-custom-transformers.md)
6. [Perform a production migration of a Jenkins pipeline](6-migrate.md)
## Troubleshoot the Valet CLI
@@ -79,7 +81,8 @@ The CLI extension for Valet can be manually installed by following these steps:
- Verify the result of the install contains:
```bash
```console
$ gh extension install github/gh-valet
✓ Installed extension github/gh-valet
```