Remove notebook/compose mentions from docs

docker-compose.yaml

@@ -1,16 +1,5 @@
 # compose config on latest release builds
 services:
-  jupyter:
-    container_name: qs-jupyter
-    image: icr.io/quantum-public/quantum-serverless-notebook:${VERSION:-0.8.2}-py39
-    profiles: ["jupyter", "full"]
-    ports:
-      - 8888:8888
-    environment:
-      - JUPYTER_TOKEN=123
-      - GATEWAY_HOST=http://gateway:8000
-    networks:
-      - safe-tier
   ray-head:
     container_name: ray-head
     image: icr.io/quantum-public/quantum-serverless-ray-node:${VERSION:-0.8.2}-py39

docs/deployment/cloud.rst

@@ -55,20 +55,17 @@ If you have ``docker compose`` available you can run the next command in your te
 .. code-block::
    :caption: run the command from the root of the project
 
-        $ docker compose --profile jupyter up
+        $ docker compose up
 
 Once the execution of the command has finished, if everything went well you should be able to open the browser
-and have access to:
-
-* Jupyter notebook: http://localhost:8888
-* Ray dashboard: http://localhost:8265
+and have access to the Ray dashboard at: http://localhost:8265
 
 In case you want to use the ``main`` branch you can use the configuration for development running the next command:
 
 .. code-block::
    :caption: run the command from the root of the project
 
-        $ docker compose -f docker-compose-dev.yaml --profile jupyter up
+        $ docker compose -f docker-compose-dev.yaml up
 
 .. _helm-deployment:
 

docs/deployment/local.rst

@@ -46,15 +46,13 @@ Once you have Docker and docker compose installed, you can run the following com
 
         $ docker compose [--profile <PROFILE>] up
 
-The available profiles are `full`, `jupyter`, and `repo`.
+The available profiles are `full` and `repo`.
 The repo profile installs core services and the program repository;
-the jupyter profile installs core services and Jupyter Notebook;
 and the full profile installs all core services, including logging and
-monitorying systems and jupyter.
+monitorying systems.
 
 Step 4: Run a program in the test environment
 
 Once the containers are running, you can simulate a remote cluster with the resources on your
-local machine. To create and run programs in this simulated cluster, visit the Jupyter Lab
-environment at `localhost:8888` via a web browser. Refer to the :ref:`getting_started` guides
+local machine. To create and run programs in this simulated cluster, we recommend using [Jupyter Lab](https://jupyter.org/install). Refer to the :ref:`getting_started` guides
 for details about running your program remotely.