Team Configuration
What is 'Team Configuration' and how it works?
To organize and display metrics by team
, Apache DevLake needs to know about the team configuration in an organization, specifically:
- What are the teams?
- Who are the users(unified identities)?
- Which users belong to a team?
- Which accounts(identities in specific tools) belong to the same user?
Each of the questions above corresponds to a table in DevLake's schema, illustrated below:
teams
table stores all the teams in the organization.users
table stores the organization's roster. An entry in theusers
table corresponds to a person in the org.team_users
table stores which users belong to a team.user_accounts
table stores which accounts belong to a user. Anaccount
refers to an identiy in a DevOps tool and is automatically created when importing data from that tool. For example, auser
may have a GitHubaccount
as well as a Jiraaccount
.
Apache DevLake uses a simple heuristic algorithm based on emails and names to automatically map accounts to users and populate the user_accounts
table.
When Apache DevLake cannot confidently map an account
to a user
due to insufficient information, it allows DevLake users to manually configure the mapping to ensure accuracy and integrity.
A step-by-step guide
In the following sections, we'll walk through how to configure teams and create the five aforementioned tables (teams
, users
, team_users
, accounts
, and user_accounts
).
The overall workflow is:
- Create the
teams
table - Create the
users
andteam_users
table - Populate the
accounts
table via data collection - Run a heuristic algorithm to populate
user_accounts
table - Manually update
user_accounts
when the algorithm can't catch everything
- Please replace
/path/to/*.csv
with the absolute path of the CSV file you'd like to upload. - Please replace
http://127.0.0.1:4000
with your actual Config UI service IP and port number. If you have enabled HTTPS, please replace it accordingly. - Please create your API key on the
API Keys
page instead of using the automatically generated key from the webhook creation.
Step 1 - Create the teams
table
You can create the teams
table by sending a PUT request to /plugins/org/teams.csv
with a teams.csv
file. To jumpstart the process, you can download a template teams.csv
from /plugins/org/teams.csv?fake_data=true
. Below are the detailed instructions:
Download the template
teams.csv
file. You can do it bya. Pasting the URL into your browser to download the template.
http://127.0.0.1:4000/api/plugins/org/teams.csv?fake_data=true
b. Or using CURL:
curl 'http://127.0.0.1:4000/api/rest/plugins/org/teams.csv?fake_data=true' -X 'GET' -H 'Authorization: Bearer {API_key}'
Fill out
teams.csv
file and upload it to DevLake (If you are using Excel to modify the CSV file, please save it with UTF-8 encoding. See how)a. Fill out
teams.csv
with your org data. Please don't modify the column headers or the file suffix.b. Upload
teams.csv
to DevLake with the following curl commandcurl 'http://127.0.0.1:4000/api/rest/plugins/org/teams.csv' -X 'PUT' -H 'Authorization: Bearer {API_key}' --form 'file=@"/path/to/teams.csv"'
c. The PUT request would populate the
teams
table with data fromteams.csv
file. You can connect to the database and verify the data in theteams
table. See 'Appendix A' for how to connect to the database.
Step 2 - Create the users
and team_users
table
You can create the users
and team_users
table by sending a single PUT request to /plugins/org/users.csv
with a users.csv
file. To jumpstart the process, you can download a template users.csv
from /plugins/org/users.csv?fake_data=true
. Below are the detailed instructions:
Download the template
users.csv
file. You can do it bya. Pasting the URL into your browser to download the template.
http://127.0.0.1:4000/api/plugins/org/users.csv?fake_data=true
b. Or using CURL:
curl 'http://127.0.0.1:4000/api/rest/plugins/org/users.csv?fake_data=true' -X 'GET' -H 'Authorization: Bearer {API_key}'
Fill out
users.csv
and upload it to DevLake (If you are using Excel to modify the CSV file, please save it with UTF-8 encoding. See how)a. Fill out
users.csv
with your org data. Please do not modify the column headers or the file suffix.b. Upload
users.csv
to DevLake with the following curl command:curl 'http://127.0.0.1:4000/api/rest/plugins/org/users.csv' -X 'PUT' -H 'Authorization: Bearer {API_key}' --form 'file=@"/path/to/users.csv"'
c. The PUT request would populate the
users
table along with theteam_users
table with data fromusers.csv
file. You can connect to the database and verify these two tables.If you want to update
team_users
orusers
table, simply upload the updatedusers.csv
to DevLake again following the previous step.
Step 3 - Populate the accounts
table via data collection
The accounts
table is automatically populated when you collect data from data sources like GitHub and Jira through DevLake.
For example, the GitHub plugin would create one entry in the accounts
table for each GitHub user involved in your repository. For demo purposes, we will insert some mock data into the accounts
table using SQL:
INSERT INTO `accounts` (`id`, `created_at`, `updated_at`, `_raw_data_params`, `_raw_data_table`, `_raw_data_id`, `_raw_data_remark`, `email`, `full_name`, `user_name`, `avatar_url`, `organization`, `created_date`, `status`)
VALUES
('github:GithubAccount:1:1234', '2022-07-12 10:54:09.632', '2022-07-12 10:54:09.632', '{\"ConnectionId\":1,\"Owner\":\"apache\",\"Repo\":\"incubator-devlake\"}', '_raw_github_api_pull_request_reviews', 28, '', 'TyroneKCummings@teleworm.us', '', 'Tyrone K. Cummings', 'https://avatars.githubusercontent.com/u/101256042?u=a6e460fbaffce7514cbd65ac739a985f5158dabc&v=4', '', NULL, 0),
('jira:JiraAccount:1:629cdf', '2022-07-12 10:54:09.632', '2022-07-12 10:54:09.632', '{\"ConnectionId\":1,\"BoardId\":\"76\"}', '_raw_jira_api_users', 5, '', 'DorothyRUpdegraff@dayrep.com', '', 'Dorothy R. Updegraff', 'https://avatars.jiraxxxx158dabc&v=4', '', NULL, 0);
Step 4 - Run a heuristic algorithm to populate user_accounts
table
Now that we have data in both the users
and accounts
table, we can tell DevLake to infer the mappings between users
and accounts
with a simple heuristic algorithm based on names and emails.
Send an API request to DevLake to run the mapping algorithm
curl --location --request POST '127.0.0.1:4000/api/pipelines' \
--header 'Content-Type: application/json' \
--data-raw '{
"name": "test",
"plan":[
[
{
"plugin": "org",
"subtasks":["connectUserAccountsExact"]
}
]
]
}'After successful execution, you can verify the data in
user_accounts
in the database.
Step 5 - Manually update user_accounts
when the algorithm can't catch everything
It is recommended to examine the generated user_accounts
table after running the algorithm. We will demonstrate how to manually update user_accounts
when the mapping is inaccurate or incomplete in this section.
To make manual verification easier, DevLake provides an API for users to download user_accounts
as a CSV file. Alternatively, you can verify and modify user_accounts
all by SQL, see Appendix for more info.
Download the template by pasting the following URL to your browser:
http://127.0.0.1:4000/api/plugins/org/user_account_mapping.csv
b. Or using CURL:
curl 'http://127.0.0.1:4000/api/rest/plugins/org/user_account_mapping.csv' -X 'GET' -H 'Authorization: Bearer {API_key}'
If you find the mapping inaccurate or incomplete, you can modify the
user_account_mapping.csv
file and then upload it to DevLake. For example, here we change theUserId
of row 'Id=github:GithubAccount:1:1234' in theuser_account_mapping.csv
file to 2.Save and upload the updated
user_account_mapping.csv
file with the following curl command (If you are using Excel to modify the CSV file, please save it with UTF-8 encoding. See how):curl 'http://127.0.0.1:4000/api/rest/plugins/org/user_account_mapping.csv' -X 'PUT' -H 'Authorization: Bearer {API_key}' --form 'file=@"/path/to/user_account_mapping.csv"'
You can verify the data in the
user_accounts
table has been updated.
Appendix A: how to connect to the database
There are many ways to connect to the database:
- Through Grafana. Go to Grafana's Explore page. Switch the SQL editor to the code mode. Then, you can write SQL to describe database and query data.
- Through database management tools such as Navicat, phyMyAdmin, DataGrip, MySQLWorkbench, etc. Type in your host, port, username and password to connect to the DB. The username and password can be fount in the image or .env file.
- Through the command line. Take MySQL as an example:
mysql -h <ip> -u <username> -p -P <port>
Appendix B: how to examine user_accounts
via SQL
SELECT a.id as account_id, a.email, a.user_name as account_user_name, u.id as user_id, u.name as real_name
FROM accounts a
join user_accounts ua on a.id = ua.account_id
join users u on ua.user_id = u.id
Troubleshooting
If you run into any problem, please check the Troubleshooting or create an issue