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The following commit(s) were added to refs/heads/master by this push:
     new 0a316a8ed3 chore(docs): feature flags setting is misleading in docs 
(#20622)
0a316a8ed3 is described below

commit 0a316a8ed324ecc46372a03a47cb5f2474e7b349
Author: wiktor2200 <[email protected]>
AuthorDate: Mon Jul 11 13:43:13 2022 +0200

    chore(docs): feature flags setting is misleading in docs (#20622)
---
 docs/docs/creating-charts-dashboards/creating-your-first-dashboard.mdx | 2 +-
 docs/docs/installation/alerts-reports.mdx                              | 2 +-
 docs/docs/installation/cache.mdx                                       | 2 +-
 docs/docs/installation/sql-templating.mdx                              | 2 +-
 4 files changed, 4 insertions(+), 4 deletions(-)

diff --git 
a/docs/docs/creating-charts-dashboards/creating-your-first-dashboard.mdx 
b/docs/docs/creating-charts-dashboards/creating-your-first-dashboard.mdx
index ecabf896f8..48792e3199 100644
--- a/docs/docs/creating-charts-dashboards/creating-your-first-dashboard.mdx
+++ b/docs/docs/creating-charts-dashboards/creating-your-first-dashboard.mdx
@@ -183,7 +183,7 @@ Access to dashboards is managed via owners (users that have 
edit permissions to
 Non-owner users access can be managed two different ways:
 
 1. Dataset permissions - if you add to the relevant role permissions to 
datasets it automatically grants implicit access to all dashboards that uses 
those permitted datasets
-2. Dashboard roles - if you enable **DASHBOARD_RBAC** feature flag  then you 
be able to manage which roles can access the dashboard
+2. Dashboard roles - if you enable **DASHBOARD_RBAC** [feature 
flag](https://superset.apache.org/docs/installation/configuring-superset#feature-flags)
 then you be able to manage which roles can access the dashboard
 - Having dashboard access implicitly grants read access to the associated 
datasets, therefore
 all charts will load their data even if feature flag is turned on and no roles 
assigned
 to roles the access will fallback to **Dataset permissions**
diff --git a/docs/docs/installation/alerts-reports.mdx 
b/docs/docs/installation/alerts-reports.mdx
index 6e71682dc7..d382b95f8e 100644
--- a/docs/docs/installation/alerts-reports.mdx
+++ b/docs/docs/installation/alerts-reports.mdx
@@ -22,7 +22,7 @@ Alerts and reports are disabled by default. To turn them on, 
you need to do some
 
 ##### In your `superset_config.py`
 
-- `"ALERT_REPORTS"` feature flag must be turned to True.
+- `"ALERT_REPORTS"` [feature 
flag](https://superset.apache.org/docs/installation/configuring-superset#feature-flags)
 must be turned to True.
 - `CELERYBEAT_SCHEDULE` in CeleryConfig must contain schedule for 
`reports.scheduler`.
 - At least one of those must be configured, depending on what you want to use:
   - emails: `SMTP_*` settings
diff --git a/docs/docs/installation/cache.mdx b/docs/docs/installation/cache.mdx
index aaa8327451..84d8556c1e 100644
--- a/docs/docs/installation/cache.mdx
+++ b/docs/docs/installation/cache.mdx
@@ -44,7 +44,7 @@ defined in `DATA_CACHE_CONFIG`.
 
 ### Caching Thumbnails
 
-This is an optional feature that can be turned on by activating it’s feature 
flag on config:
+This is an optional feature that can be turned on by activating it’s [feature 
flag](https://superset.apache.org/docs/installation/configuring-superset#feature-flags)
 on config:
 
 ```
 FEATURE_FLAGS = {
diff --git a/docs/docs/installation/sql-templating.mdx 
b/docs/docs/installation/sql-templating.mdx
index 09373d8999..8a093e643a 100644
--- a/docs/docs/installation/sql-templating.mdx
+++ b/docs/docs/installation/sql-templating.mdx
@@ -10,7 +10,7 @@ version: 1
 ### Jinja Templates
 
 SQL Lab and Explore supports [Jinja 
templating](https://jinja.palletsprojects.com/en/2.11.x/) in queries.
-To enable templating, the `ENABLE_TEMPLATE_PROCESSING` feature flag needs to 
be enabled in
+To enable templating, the `ENABLE_TEMPLATE_PROCESSING` [feature 
flag](https://superset.apache.org/docs/installation/configuring-superset#feature-flags)
 needs to be enabled in
 `superset_config.py`. When templating is enabled, python code can be embedded 
in virtual datasets and
 in Custom SQL in the filter and metric controls in Explore. By default, the 
following variables are
 made available in the Jinja context:

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