DevLake

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What is DevLake?

DevLake brings all your DevOps data into one practical, personalized, extensible view. Ingest, analyze, and visualize data from an ever-growing list of developer tools, with our free and open source product.

DevLake is most exciting for developer teams looking to make better sense of their development process and to bring a more data-driven approach to their own practices. With DevLake you can ask your process any question, just connect and query.

Get started with just a few clicks

Run Locally

See the Guide

Dashboard Screenshot

User Flow

Why DevLake?

1. Comprehensive understanding of software development lifecycle, digging workflow bottlenecks
2. Timely review of team iteration performance, rapid feedback, agile adjustment
3. Quickly build scenario-based data dashboards and drill down to analyze the root cause of problems

What can be accomplished with DevLake?

1. Collect DevOps performance data for the whole process
2. Share abstraction layer with similar tools to output standardized performance data
3. Built-in 20+ performance metrics and drill-down analysis capability
4. Support custom SQL analysis and drag and drop to build scenario-based data views
5. Flexible architecture and plug-in design to support fast access to new data sources

See Demo

Click here to see demo. The demo is based on data from this repo.
Username/Password: test/test

Contents

Section	Sub-section	Description	Documentation Link
Data Sources	Supported Data Sources	Links to specific plugin usage & details	View Section
Setup Guide	User Setup	Set up Dev Lake locally as a user	View Section
	Developer Setup	Set up development environment locally	View Section
	Cloud Setup	Set up DevLake in the cloud with Tin	View Section
Tests	Tests	Commands for running tests	View Section
Make Contribution	Understand the architecture of DevLake	See the architecture diagram	View Section
	Build a Plugin	Details on how to make your own plugin	View Section
	Add Plugin Metrics	Guide to add metrics	View Section
	Contribution specs	How to contribute to this repo	View Section
User Guide, Help, and more	Grafana	How to visualize the data	View Section
	Need Help	Message us on Discord	View Section
	FAQ	Frequently asked questions by users	View Section
	License	The project license	View Section

Data Sources We Currently Support

Below is a list of data source plugins used to collect & enrich data from specific sources. Each has 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	Summary, Data & Metrics, Configuration, Plugin API	Link
GitLab	Summary, Data & Metrics, Configuration, Plugin API	Link
Jenkins	Summary, Data & Metrics, Configuration, Plugin API	Link
GitHub	Summary, Data & Metrics, Configuration, Plugin API	Link

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Setup Guide

There're 3 ways to set up DevLake: user setup, developer setup and cloud setup.

User setup

• If you only plan to run the product locally, this is the ONLY section you should need.
• Commands written like this are to be run in your terminal.

Required Packages to Install

• Docker
• docker-compose

NOTE: After installing docker, you may need to run the docker application and restart your terminal

Commands to run in your terminal

1. Clone repository:

   git clone https://github.com/merico-dev/lake.git devlake
   cd devlake
   cp .env.example .env

2. Start Docker on your machine, then run docker-compose up -d to start the services.

3. Visit localhost:4000 to setup configuration files.

   • Navigate to desired plugins pages on the Integrations page
   • You will need to enter the required information for the plugins you intend to use.
   • Please reference the following for more details on how to configure each one: -> Jira -> GitLab -> Jenkins -> GitHub

   • Submit the form to update the values by clicking on the Save Connection button on each form page

   • devlake takes a while to fully boot up. if config-ui complaining about api being unreachable, please wait a few seconds and try refreshing the page.
   • To collect this repo for a quick preview, please provide a Github personal token on Data Integrations / Github page.

4. Visit localhost:4000/triggers to trigger data collection.

   • Please refer to this wiki How to trigger data collection. Data collection can take a while depending on the amount of data you'd like to collect.
   • To collect this repo for a quick preview, you can use the following JSON

     [
       [
         {
           "Plugin": "github",
           "Options": {
             "repositoryName": "lake",
             "owner": "merico-dev"
           }
         }
       ]
     ]

5. Click View Dashboards button when done (username: admin, password: admin). The button will be shown on the Trigger Collection page when data collection has finished.

Setup cron job

To synchronize data periodically, we provide lake-cli for easily sending data collection requests along with a cron job to periodically trigger the cli tool.

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Developer Setup

Requirements

• Docker
• Golang
• Make
  • Mac (Already installed)
  • Windows: Download
  • Ubuntu: sudo apt-get install build-essential

How to setup dev environment

1. 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

2. Install Go packages:

   make install

3. Copy the sample config file to new local file:

   cp .env.example .env

   Find the line start with DB_URL in the file .env and replace mysql:3306 with 127.0.0.1:3306

4. Start the MySQL and Grafana containers:

   Make sure the Docker daemon is running before this step.

   docker-compose up mysql grafana

5. Run lake and config UI in dev mode in two seperate terminals:

   # run lake
   make dev
   # run config UI
   make configure-dev

6. Visit config UI at localhost:4000 to configure data sources.

   • Navigate to desired plugins pages on the Integrations page
   • You will need to enter the required information for the plugins you intend to use.
   • Please reference the following for more details on how to configure each one: -> Jira -> GitLab, -> Jenkins -> GitHub

   • Submit the form to update the values by clicking on the Save Connection button on each form page

7. Visit localhost:4000/triggers to trigger data collection.

   • Please refer to this wiki How to trigger data collection. Data collection can take up to 20 minutes for large projects. (GitLab 10k+ commits or Jira 5k+ issues)

8. Click View Dashboards button when done (username: admin, password: admin). The button is shown in the top left.

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Cloud setup

If you want to run DevLake in a clound environment, you can set up DevLake with Tin. See detailed setup guide

Disclaimer:

To protect your information, it is critical for users of the Tin hosting to set passwords to protect DevLake applications. We built DevLake as a self-hosted product, in part to ensure users have total protection and ownership of their data, while the same remains true for the Tin hosting, this risk point can only be eliminated by the end-user.

Tests

To run the tests:

make test

Make Contribution

This section list all the documents to help you contribute to the repo.

Understand the Architecture of DevLake

Architecture Diagram

Add a Plugin

plugins/README.md

Add Plugin Metrics

plugins/HOW-TO-ADD-METRICS.md

Contributing Spec

CONTRIBUTING.md

User Guide, Help and more

Grafana

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.

Need help?

Message us on Discord

FAQ

Q: When I run docker-compose up -d I get this error: "qemu: uncaught target signal 11 (Segmentation fault) - core dumped". How do I fix this?

A: M1 Mac users need to download a specific version of docker on their machine. You can find it here.

License

This project is licensed under Apache License 2.0 - see the LICENSE file for details.