Commit 77eabfba authored by Marcin Sedlak-Jakubowski's avatar Marcin Sedlak-Jakubowski

Merge branch 'docs-value-analytics-update' into 'master'

Update Value Stream Analytics page

See merge request gitlab-org/gitlab!62611
parents 1943fa5a e9d96459
......@@ -7,7 +7,7 @@ info: To determine the technical writer assigned to the Stage/Group associated w
# Value Stream Analytics **(FREE)**
> - Introduced as Cycle Analytics prior to GitLab 12.3 at the project level.
> - [Introduced](https://gitlab.com/gitlab-org/gitlab/-/issues/12077) in [GitLab Premium](https://about.gitlab.com/pricing/) 12.3 at the group level.
> - [Introduced](https://gitlab.com/gitlab-org/gitlab/-/issues/12077) in GitLab Premium 12.3 at the group level.
> - [Renamed](https://gitlab.com/gitlab-org/gitlab/-/merge_requests/23427) from Cycle Analytics to Value Stream Analytics in GitLab 12.8.
Value Stream Analytics measures the time spent to go from an
......@@ -15,20 +15,20 @@ Value Stream Analytics measures the time spent to go from an
(also known as cycle time) for each of your projects or groups. Value Stream Analytics displays the median time
spent in each stage defined in the process.
Value Stream Analytics is useful in order to quickly determine the velocity of a given
You can use Value Stream Analytics to determine the velocity of a given
project. It points to bottlenecks in the development process, enabling management
to uncover, triage, and identify the root cause of slowdowns in the software development life cycle.
For information on how to contribute to the development of Value Stream Analytics, see our [contributor documentation](../../development/value_stream_analytics.md).
For information about how to contribute to the development of Value Stream Analytics, see our [contributor documentation](../../development/value_stream_analytics.md).
Project-level Value Stream Analytics is available via **Project > Analytics > Value Stream**.
Project-level Value Stream Analytics is available by using **Project > Analytics > Value Stream**.
NOTE:
[Group-level Value Stream Analytics](../group/value_stream_analytics) is also available.
## Default stages
The stages tracked by Value Stream Analytics by default represent the [GitLab flow](../../topics/gitlab_flow.md). These stages can be customized in Group Level Value Stream Analytics.
The stages tracked by Value Stream Analytics by default represent the [GitLab flow](../../topics/gitlab_flow.md). You can customize these stages in group-level Value Stream Analytics.
- **Issue** (Tracker)
- Time to schedule an issue (by milestone or by adding it to an issue board)
......@@ -38,38 +38,34 @@ The stages tracked by Value Stream Analytics by default represent the [GitLab fl
- Time to create a merge request
- **Test** (CI)
- Time it takes GitLab CI/CD to test your code
- **Review** (Merge Request/MR)
- **Review** (Merge request)
- Time spent on code review
- **Staging** (Continuous Deployment)
- Time between merging and deploying to production
### Date ranges
> [Introduced](https://gitlab.com/gitlab-org/gitlab-foss/-/issues/36300) in GitLab 10.0.
To filter analytics results based on a date range, select one of these options:
GitLab provides the ability to filter analytics based on a date range. To filter results, select one of these options:
1. Last 7 days
1. Last 30 days (default)
1. Last 90 days
- **Last 7 days**
- **Last 30 days** (default)
- **Last 90 days**
## How Time metrics are measured
The "Time" metrics near the top of the page are measured as follows:
The **Time** metrics near the top of the page are measured as follows:
- **Lead time**: median time from issue created to issue closed.
- **Cycle time**: median time from first commit to issue closed. (You can associate a commit with an issue by [crosslinking in the commit message](../project/issues/crosslinking_issues.md#from-commit-messages).)
- **Lead time**: Median time from issue created to issue closed.
- **Cycle time**: Median time from first commit to issue closed. (You can associate a commit with an issue by [crosslinking in the commit message](../project/issues/crosslinking_issues.md#from-commit-messages).)
## How the stages are measured
Value Stream Analytics uses start events and stop events to measure the time that an Issue or MR spends in each stage.
For example, a stage might start when one label is added to an issue, and end when another label is added.
Items are not included in the stage time calculation if they have not reached the stop event.
Each stage of Value Stream Analytics is further described in the table below.
Value Stream Analytics uses start events and stop events to measure the time that an issue or merge request spends in each stage.
For example, a stage might start when one label is added to an issue and end when another label is added.
Items aren't included in the stage time calculation if they have not reached the stop event.
| **Stage** | **Description** |
| --------- | --------------- |
| Stage | Description |
|---------|---------------|
| Issue | Measures the median time between creating an issue and taking action to solve it, by either labeling it or adding it to a milestone, whichever comes first. The label is tracked only if it already includes an [Issue Board list](../project/issue_board.md) created for it. |
| Plan | Measures the median time between the action you took for the previous stage, and pushing the first commit to the branch. That first branch commit triggers the separation between **Plan** and **Code**, and at least one of the commits in the branch must include the related issue number (such as `#42`). If the issue number is *not* included in a commit, that data is not included in the measurement time of the stage. |
| Code | Measures the median time between pushing a first commit (previous stage) and creating a merge request (MR). The process is tracked with the [issue closing pattern](../project/issues/managing_issues.md#closing-issues-automatically) in the description of the merge request. For example, if the issue is closed with `Closes #xxx`, it's assumed that `xxx` is issue number for the merge request). If there is no closing pattern, the start time is set to the create time of the first commit. |
......@@ -77,16 +73,16 @@ Each stage of Value Stream Analytics is further described in the table below.
| Review | Measures the median time taken to review merge requests with a closing issue pattern, from creation to merge. |
| Staging | Measures the median time between merging the merge request (with a closing issue pattern) to the first deployment to a [production environment](#how-the-production-environment-is-identified). Data not collected without a production environment. |
How this works, behind the scenes:
How this works:
1. Issues and merge requests are grouped in pairs, where the merge request has the
[closing pattern](../project/issues/managing_issues.md#closing-issues-automatically)
for the corresponding issue. Issue/merge request pairs without closing patterns are
**not** included.
1. Issue/merge request pairs are filtered by the last XX days, specified through the UI
(default = 90 days). Pairs outside the filtered range are not included.
for the corresponding issue. Issue and merge request pairs without closing patterns are
not included.
1. Issue and merge request pairs are filtered by the last XX days, specified through the UI
(default is `90` days). Pairs outside the filtered range are not included.
1. For the remaining pairs, review information needed for stages, including
issue creation date, merge request merge time, and so on.
issue creation date and merge request merge time.
In short, the Value Stream Analytics dashboard tracks data related to [GitLab flow](../../topics/gitlab_flow.md). It does not include data for:
......@@ -97,67 +93,69 @@ In short, the Value Stream Analytics dashboard tracks data related to [GitLab fl
## How the production environment is identified
Value Stream Analytics identifies production environments based on
[the deployment tier of environments](../../ci/environments/index.md#deployment-tier-of-environments).
Value Stream Analytics identifies production environments based on the
[deployment tier of environments](../../ci/environments/index.md#deployment-tier-of-environments).
## Example workflow
Below is a simple fictional workflow of a single cycle that happens in a
single day passing through all seven stages. Note that if a stage does not have
a start and a stop mark, it is not measured and hence not calculated in the median
time. It is assumed that milestones are created and CI for testing and setting
Here's a fictional workflow of a single cycle that happens in a
single day, passing through all seven stages. If a stage doesn't have
a start and a stop mark, it isn't measured and hence isn't calculated in the median
time. It's assumed that milestones are created, and CI for testing and setting
environments is configured.
1. Issue is created at 09:00 (start of **Issue** stage).
1. Issue is added to a milestone at 11:00 (stop of **Issue** stage / start of
1. Issue is added to a milestone at 11:00 (stop of **Issue** stage and start of
**Plan** stage).
1. Start working on the issue, create a branch locally and make one commit at
1. Start working on the issue, create a branch locally, and make one commit at
12:00.
1. Make a second commit to the branch which mentions the issue number at 12.30
(stop of **Plan** stage / start of **Code** stage).
1. Push branch and create a merge request that contains the [issue closing pattern](../project/issues/managing_issues.md#closing-issues-automatically)
in its description at 14:00 (stop of **Code** stage / start of **Test** and
1. Make a second commit to the branch that mentions the issue number at 12:30
(stop of **Plan** stage and start of **Code** stage).
1. Push branch, and create a merge request that contains the [issue closing pattern](../project/issues/managing_issues.md#closing-issues-automatically)
in its description at 14:00 (stop of **Code** stage and start of **Test** and
**Review** stages).
1. The CI starts running your scripts defined in [`.gitlab-ci.yml`](../../ci/yaml/README.md) and
takes 5min (stop of **Test** stage).
1. Review merge request, ensure that everything is OK and merge the merge
request at 19:00. (stop of **Review** stage / start of **Staging** stage).
1. Now that the merge request is merged, a deployment to the `production`
takes 5 minutes (stop of **Test** stage).
1. Review merge request, ensure that everything is okay, and then merge the merge
request at 19:00 (stop of **Review** stage and start of **Staging** stage).
1. The merge request is merged, and a deployment to the `production`
environment starts and finishes at 19:30 (stop of **Staging** stage).
From the above example we see the time used for each stage:
From the previous example we see the time used for each stage:
- **Issue**: 2h (11:00 - 09:00)
- **Plan**: 1h (12:00 - 11:00)
- **Code**: 2h (14:00 - 12:00)
- **Test**: 5min
- **Review**: 5h (19:00 - 14:00)
- **Staging**: 30min (19:30 - 19:00)
- **Issue**: 2 hrs (09:00 to 11:00)
- **Plan**: 1 hr (11:00 to 12:00)
- **Code**: 2 hrs (12:00 to 14:00)
- **Test**: 5 mins
- **Review**: 5 hrs (14:00 to 19:00)
- **Staging**: 30 mins (19:00 to 19:30)
More information:
- The above example specifies the issue number in a latter commit. The process
still collects analytics data for that issue.
- The time required in the **Test** stage is not included in the overall time of
the cycle. It is included in the **Review** process, as every MR should be
- Although the previous example specifies the issue number in a later commit, the process
still collects analytics data for the issue.
- The time required in the **Test** stage isn't included in the overall time of
the cycle. The time is included in the **Review** process, as every merge request should be
tested.
- The example above illustrates only **one cycle** of the multiple stages. Value
- The previous example illustrates only one cycle of the multiple stages. Value
Stream Analytics, on its dashboard, shows the calculated median elapsed time
for these issues.
## Permissions
The current permissions on the Project-level Value Stream Analytics dashboard are:
The permissions for the project-level Value Stream Analytics dashboard include:
- Public projects - anyone can access.
- Internal projects - any authenticated user can access.
- Private projects - any member Guest and above can access.
| Project type | Permissions |
|--------------|---------------------------------------|
| Public | Anyone can access |
| Internal | Any authenticated user can access |
| Private | Any member Guest and above can access |
You can [read more about permissions](../../user/permissions.md) in general.
## More resources
Learn more about Value Stream Analytics in the following resources:
Learn more about Value Stream Analytics with the following resources:
- [Value Stream Analytics feature page](https://about.gitlab.com/stages-devops-lifecycle/value-stream-analytics/).
- [Value Stream Analytics feature preview](https://about.gitlab.com/blog/2016/09/16/feature-preview-introducing-cycle-analytics/).
......
Markdown is supported
0%
or
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment