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new 422da1cbe2 docs: update scope and connection definition (#559)
422da1cbe2 is described below
commit 422da1cbe2e84c3f7ea17ad378a2d9f2e37cb332
Author: Louis.z <[email protected]>
AuthorDate: Thu Jun 15 10:50:21 2023 +0800
docs: update scope and connection definition (#559)
* docs: update scope and connection definition
* docs: update data scope definition
---------
Co-authored-by: Startrekzky <[email protected]>
---
docs/Overview/KeyConcepts.md | 20 ++++++++------------
versioned_docs/version-v0.17/Overview/KeyConcepts.md | 18 +++++++-----------
2 files changed, 15 insertions(+), 23 deletions(-)
diff --git a/docs/Overview/KeyConcepts.md b/docs/Overview/KeyConcepts.md
index b33dc16c9a..dcd4739760 100644
--- a/docs/Overview/KeyConcepts.md
+++ b/docs/Overview/KeyConcepts.md
@@ -1,12 +1,12 @@
---
sidebar_position: 4
title: "Key Concepts"
-linkTitle: "KeyConepts"
+linkTitle: "KeyConcepts"
description: >
DevLake Key Concepts
---
-*Last updated: May 16 2022*
+*Last updated: June 13, 2023*
## In Configuration UI (Regular Mode)
@@ -27,30 +27,26 @@ For example, when a user associates 'Jenkins Job A' and
'Jira board B' with pro
3. **Adding [Transformation Rules](#transformation-rules) (optional)**: You
can optionally apply transformation for the data scope you have just selected,
in order to view more advanced metrics.
3. **Setting the Sync Frequency**: You can specify the sync frequency for your
blueprint to achieve recurring data syncs and transformation. Alternatively,
you can set the frequency to manual if you wish to run the tasks in the
blueprint manually.
-The relationship among Blueprint, Data Connections, Data Scope and
Transformation Rules is explained as follows:
+The relationship between Blueprint, Data Connections, Data Scope and
Transformation Rules is explained as follows:
- Each blueprint can have multiple data connections.
-- Each data connection can have multiple sets of data scope.
+- Each data connection can have multiple data scopes.
- Each set of data scope only consists of one GitHub/GitLab project or Jira
board, along with their corresponding data entities.
- Each set of data scope can only have one set of transformation rules.
### Data Sources
**A data source is a specific DevOps tool from which you wish to sync your
data, such as GitHub, GitLab, Jira and Jenkins.**
-DevLake normally uses one [data plugin](#data-plugins) to pull data for a
single data source. However, in some cases, DevLake uses multiple data plugins
for one data source for the purpose of improved sync speed, among many other
advantages. For instance, when you pull data from GitHub or GitLab, aside from
the GitHub or GitLab plugin, Git Extractor is also used to pull data from the
repositories. In this case, DevLake still refers GitHub or GitLab as a single
data source.
+DevLake normally uses one [data plugin](#data-plugins) to pull data for a
single data source. However, in some cases, DevLake uses multiple data plugins
for one data source for a better sync speed, among many other advantages. For
instance, when you pull data from GitHub or GitLab, aside from the GitHub or
GitLab plugin, Git Extractor is also used to pull data from the repositories.
In this case, DevLake still recognizes GitHub or GitLab as a single data source.
### Data Connections
**A data connection is a specific instance of a data source that stores
information such as `endpoint` and `auth`.** A single data source can have one
or more data connections (e.g. two Jira instances). Currently, DevLake supports
one data connection for GitHub, GitLab and Jenkins, and multiple connections
for Jira.
-You can set up a new data connection either during the first step of creating
a blueprint, or in the Connections page that can be accessed from the
navigation bar. Because one single data connection can be reused in multiple
blueprints, you can update the information of a particular data connection in
Connections, to ensure all its associated blueprints will run properly. For
example, you may want to update your GitHub token in a data connection if it
goes expired.
+The recommended way to set up a new data connection is via the Data
Connections page. You can then add the data connection to a DevLake project to
measure metrics later. A data connection can be used in multiple projects.
-### Data Scope
-**In a blueprint, each data connection can have multiple sets of data scope
configurations, including GitHub or GitLab projects, Jira boards and their
corresponding [data entities](#data-entities).** The fields for data scope
configuration vary according to different data sources.
-
-Each set of data scope refers to one GitHub or GitLab project, or one Jira
board and the data entities you would like to sync for them, for the
convenience of applying transformation in the next step. For instance, if you
wish to sync 5 GitHub projects, you will have 5 sets of data scope for GitHub.
-
-To learn more about the default data scope of all data sources and data
plugins, please refer to [Supported Data Sources](./SupportedDataSources.md).
+### Data Scope(s)
+**A data scope is the top-level "container" in a data source**. For example, a
data scope for Jira is a Jira board, for TAPD is a TAPD workspace, for
GitHub/GitLab/BitBucket is a repo, for Jenkins is a Jenkins job, etc. You can
add multiple data scopes to a data connection to determine which data to
collect. Data scopes vary for different data sources.
### Data Entities
**Data entities refer to the data fields from one of the five data domains:
Issue Tracking, Source Code Management, Code Review, CI/CD and Cross-Domain.**
diff --git a/versioned_docs/version-v0.17/Overview/KeyConcepts.md
b/versioned_docs/version-v0.17/Overview/KeyConcepts.md
index b33dc16c9a..63ddd72b63 100644
--- a/versioned_docs/version-v0.17/Overview/KeyConcepts.md
+++ b/versioned_docs/version-v0.17/Overview/KeyConcepts.md
@@ -6,7 +6,7 @@ description: >
DevLake Key Concepts
---
-*Last updated: May 16 2022*
+*Last updated: June 13, 2023*
## In Configuration UI (Regular Mode)
@@ -27,30 +27,26 @@ For example, when a user associates 'Jenkins Job A' and
'Jira board B' with pro
3. **Adding [Transformation Rules](#transformation-rules) (optional)**: You
can optionally apply transformation for the data scope you have just selected,
in order to view more advanced metrics.
3. **Setting the Sync Frequency**: You can specify the sync frequency for your
blueprint to achieve recurring data syncs and transformation. Alternatively,
you can set the frequency to manual if you wish to run the tasks in the
blueprint manually.
-The relationship among Blueprint, Data Connections, Data Scope and
Transformation Rules is explained as follows:
+The relationship between Blueprint, Data Connections, Data Scope and
Transformation Rules is explained as follows:
- Each blueprint can have multiple data connections.
-- Each data connection can have multiple sets of data scope.
+- Each data connection can have multiple data scopes.
- Each set of data scope only consists of one GitHub/GitLab project or Jira
board, along with their corresponding data entities.
- Each set of data scope can only have one set of transformation rules.
### Data Sources
**A data source is a specific DevOps tool from which you wish to sync your
data, such as GitHub, GitLab, Jira and Jenkins.**
-DevLake normally uses one [data plugin](#data-plugins) to pull data for a
single data source. However, in some cases, DevLake uses multiple data plugins
for one data source for the purpose of improved sync speed, among many other
advantages. For instance, when you pull data from GitHub or GitLab, aside from
the GitHub or GitLab plugin, Git Extractor is also used to pull data from the
repositories. In this case, DevLake still refers GitHub or GitLab as a single
data source.
+DevLake normally uses one [data plugin](#data-plugins) to pull data for a
single data source. However, in some cases, DevLake uses multiple data plugins
for one data source for a better sync speed, among many other advantages. For
instance, when you pull data from GitHub or GitLab, aside from the GitHub or
GitLab plugin, Git Extractor is also used to pull data from the repositories.
In this case, DevLake still recognizes GitHub or GitLab as a single data source.
### Data Connections
**A data connection is a specific instance of a data source that stores
information such as `endpoint` and `auth`.** A single data source can have one
or more data connections (e.g. two Jira instances). Currently, DevLake supports
one data connection for GitHub, GitLab and Jenkins, and multiple connections
for Jira.
-You can set up a new data connection either during the first step of creating
a blueprint, or in the Connections page that can be accessed from the
navigation bar. Because one single data connection can be reused in multiple
blueprints, you can update the information of a particular data connection in
Connections, to ensure all its associated blueprints will run properly. For
example, you may want to update your GitHub token in a data connection if it
goes expired.
+The recommended way to set up a new data connection is via the Data
Connections page. You can then add the data connection to a DevLake project to
measure metrics later. A data connection can be used in multiple projects.
-### Data Scope
-**In a blueprint, each data connection can have multiple sets of data scope
configurations, including GitHub or GitLab projects, Jira boards and their
corresponding [data entities](#data-entities).** The fields for data scope
configuration vary according to different data sources.
-
-Each set of data scope refers to one GitHub or GitLab project, or one Jira
board and the data entities you would like to sync for them, for the
convenience of applying transformation in the next step. For instance, if you
wish to sync 5 GitHub projects, you will have 5 sets of data scope for GitHub.
-
-To learn more about the default data scope of all data sources and data
plugins, please refer to [Supported Data Sources](./SupportedDataSources.md).
+### Data Scope(s)
+**A data scope is the top-level "container" in a data source**. For example, a
data scope for Jira is a Jira board, for TAPD is a TAPD workspace, for
GitHub/GitLab/BitBucket is a repo, for Jenkins is a Jenkins job, etc. You can
add multiple data scopes to a data connection to determine which data to
collect. Data scopes vary for different data sources.
### Data Entities
**Data entities refer to the data fields from one of the five data domains:
Issue Tracking, Source Code Management, Code Review, CI/CD and Cross-Domain.**
