[DATALAB-2402]: Add Sphinx doc

.asf.yaml

@@ -0,0 +1,6 @@
+github:
+  ghp_branch:  gh-pages
+  labels:
+    - datalab
+publish:
+  whoami: gh-pages

RELEASE_NOTES.md

@@ -1,60 +1,69 @@
+#
 # DLab is Self-service, Fail-safe Exploratory Environment for Collaborative Data Science Workflow
 
-## New features in v2.2
+## New features in v2.3
+
 **All Cloud platforms:**
-- added concept of Projects into DLab. Now users can unite under Projects and collaborate
-- for ease of use we've added web terminal for all DLab Notebooks
-- updated versions of installed software:
-	* angular 8.2.7
+- Added support for multi-Cloud orchestration for AWS, Azure and GCP. Now, a single DLab instance can connect to the above Clouds, by means of respective set of API's, deployed on cloud endpoints;
+- Added JupyterLab v.0.35.6 template
+- Updated versions of installed software:
+  - Jupyter notebook v.6.0.2;
+  - Apache Zeppelin v.0.8.2;
+  - RStudio v.1.2.5033;
+  - Apache Spark v.2.4.4 for standalone cluster;
+
+**AWS:**
+- Added support of new version of Data Engine Service (EMR) v.5.28.0;
 
 **GCP:**
-- added billing report to monitor Cloud resources usage into DLab, including ability to manage billing quotas
-- updated versions of installed software:
-	* Dataproc 1.3
+- Added support of new version of Data Engine Service (Dataproc) v.1.4;
+- Added new template Superset v.0.35.1;
 
-## Improvements in v2.2
+## Improvements in v2.3
 **All Cloud platforms:**
-- implemented login via KeyCloak to support integration with multiple SAML and OAUTH2 identity providers
-- added DLab version into WebUI
-- augmented ‘Environment management’ page
-- added possibility to tag Notebook from UI
-- added possibility to terminate computational resources via scheduler
+- Grouped project management actions in single Edit project menu for ease of use;
+- Introduced new "project admin" role;
+- SSO now also works for Notebooks;
+- Implemented ability to filter installed libraries;
+- Added possibility to sort by project/user/charges in 'Billing report' page;
+- Added test option for remote endpoint;
 
-**GCP:**
-- added possibility to create Notebook/Data Engine from an AMI image
+## Bug fixes in v2.3
+**All Cloud platforms:**
+- Fixed a bug when Notebook name should be unique per project for different users, since it was impossible to operate Notebook with the same name after the first instance creation;
+- Fixed a bug when administrator could not stop/terminate Notebook/computational resources created by another user;
+- Fixed a bug when shell interpreter was not showing up for Apache Zeppelin;
+- Fixed a bug when scheduler by start time was not triggered for Data Engine;
+- Fixed a bug when it was possible to start Notebook if project quota was exceeded;
+- Fixed a bug when scheduler for stopping was not triggered after total quota depletion;
 
-**AWS and GCP:**
-- UnGit tool now allows working with remote repositories over ssh
-- implemented possibility to view Data Engine Service version on UI after creation
+**AWS:**
+- Fixed a bug when Notebook image/snapshot were still available after SSN termination;
 
-## Bug fixes in v2.2
-**All Cloud platforms:**
-- fixed  sparklyr library (r package) installation on RStudio, RStudio with TensorFlow notebooks
+**Microsoft Azure:**
+- Fixed a bug when custom image creation from Notebook failed and deleted the existing Notebook of another user;
+- Fixed a bug when detailed billing was not available;
+- Fixed a bug when spark reconfiguration failed on Data Engine;
+- Fixed a bug when billing data was not available after calendar filter usage;
 
+## Known issues in v2.3
 **GCP:**
-- fixed a bug when Data Engine creation fails for DeepLearning template
-- fixed a bug when Jupyter does not start successfully after Data Engine Service creation (create Jupyter -> create Data Engine -> stop Jupyter -> Jupyter fails)
-- fixed a bug when DeepLearning creation was failing
-
-## Known issues in v2.2
-**All Cloud platforms:**
-- Notebook name should be unique per project for different users in another case it is impossible to operate Notebook with the same name after the first instance creation
+- SSO is not available for Superset;
 
 **Microsoft Azure:**
-- DLab deployment  is unavailable if Data Lake is enabled
-- custom image creation from Notebook fails and deletes existed Notebook
+- Notebook creation fails on RedHat;
+- Web terminal is not working for Notebooks only for remote endpoint;
 
-**Refer to the following link in order to view the other major/minor issues in v2.2:**
+Refer to the following link in order to view the other major/minor issues in v2.3:
 
-[Apache DLab: known issues](https://issues.apache.org/jira/issues/?filter=12347602 "Apache DLab: known issues")
+[Apache DLab: known issues](https://issues.apache.org/jira/issues/?filter=12348876#](https://issues.apache.org/jira/issues/?filter=12348876 "Apache DLab: known issues")
 
-## Known issues caused by cloud provider limitations in v2.2
+## Known issues caused by cloud provider limitations in v2.3
 **Microsoft Azure:**
-- resource name length should not exceed 80 chars
-- TensorFlow templates are not supported for Red Hat Enterprise Linux
-- low priority Virtual Machines are not supported yet
+- Resource name length should not exceed 80 chars;
+- TensorFlow templates are not supported for RedHat Enterprise Linux;
+- Low priority Virtual Machines are not supported yet;
 
 **GCP:**
-- resource name length should not exceed 64 chars
-- billing data is not available
-- **NOTE:** DLab has not been tested on GCP for Red Hat Enterprise Linux
+- Resource name length should not exceed 64 chars;
+- NOTE: DLab has not been tested on GCP for RedHat Enterprise Linux;