commit | 728974ebb4228daad0e80cd58765d50245eeec55 | [log] [tgz] |
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author | Jonathan O'Donnell <joncodo@meri.co> | Thu Oct 14 13:19:41 2021 -0300 |
committer | GitHub <noreply@github.com> | Thu Oct 14 13:19:41 2021 -0300 |
tree | 3e093c61fcbabf90aeccb8e5aff788aaba897987 | |
parent | 3cb87aa8e72929dcc0d876e7d8991dfc6e6d8559 [diff] | |
parent | 99c75977b587bce4898d967c56fd2e04e8f85e2d [diff] |
Merge pull request #509 from merico-dev/fix-production-config-build config-ui: Fix prod build and add route controls
English | 中文 |
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Dev Lake is the one-stop solution that integrates, analyzes, and visualizes software development data throughout the software development life cycle (SDLC) for engineering teams.
Section | Description | Documentation Link |
---|---|---|
Data Sources | Links to specific plugin usage & details | View Section |
User Setup | Steps to run the project as a user | View Section |
Developer Setup | How to setup dev environment | View Section |
Tests | Commands for running tests | View Section |
Grafana | How to visualize the data | View Section |
Build a Plugin | Details on how to make your own | Link |
Add Plugin Metrics | Guide to adding plugin metrics | Link |
Contributing | How to contribute to this repo | Link |
Below is a list of data source plugins used to collect & enrich data from specific sources. Each have a README.md
file with basic setup, troubleshooting and metrics info.
For more information on building a new data source plugin see Build a Plugin.
Section | Section Info | Docs |
---|---|---|
Jira | Metrics, Generating API Token, Find Board ID | Link |
Gitlab | Metrics, Generating API Token, Find Project ID | Link |
Jenkins | Metrics, Generating API Token | Link |
NOTE: If you only plan to run the product, this is the only section you should need NOTE: Commands written like this
are to be run in your terminal
NOTE: After installing docker, you may need to run the docker application and restart your terminal
Clone repository
git clone https://github.com/merico-dev/lake.git devlake cd devlake cp .env.example .env
Start Docker on your machine and then you can run docker-compose up -d config-ui
to start up the configuration interface
For more info on how to configure plugins, please refer to the data source plugins section
Visit localhost:4000
to setup configuration files
- Finish the configuration on the main configuration page (
localhost:4000
)- Navigate to desired plugins pages on the sidebar under “Plugins”, e.g. Jira, Gitlab, Jenkins etc. Enter in required information for those plugins
- Submit the form to update the values by clicking on the Save Config button on each form page
Run docker-compose up -d
to start up the other services
Visit localhost:4000/triggers
to trigger data collection
Please replace your gitlab projectId and jira boardId in the request body. Click the Trigger Collection button. This can take up to 20 minutes for large projects. (gitlab 10k+ commits or jira 5k+ issues)
Click Go to grafana button when done (username: admin
, password: admin
). The button will be shown on the Trigger Collection page when data collection has finished.
Commonly, we have requirement to synchorize data periodly. We providered a tool called lake-cli
to meet that requirement. Check lake-cli
usage at here.
Otherwise, if you just want to use the cron job, please check docker-compose
version at here
sudo apt-get install build-essential
Navigate to where you would like to install this project and clone the repository
git clone https://github.com/merico-dev/lake.git cd lake
Install go packages
make install
Copy sample config files to new local file
cp .env.example .env
Start the docker containers
Make sure the docker application is running before this step
make compose
Run the project
make dev
You can now post to /task to create a jira task. This will collect data from Jira
curl -XPOST 'localhost:8080/task' \ -H 'Content-Type: application/json' \ -d '[[{ "plugin": "jira", "options": { "boardId": 8 } }]]'
Visualize the data in the Grafana Dashboard
From here you can see existing data visualized from collected & enriched data
admin
, password: admin
)lake
To run the tests: make test
We use Grafana as a visualization tool to build charts for the data stored in our database. Using SQL queries we can add panels to build, save, and edit customized dashboards.
All the details on provisioning, and customizing a dashboard can be found in the Grafana Doc
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