diff --git a/README.md b/README.md
index 60bd5ce8..bf52a1ce 100644
--- a/README.md
+++ b/README.md
@@ -14,12 +14,6 @@ You can install optuna-dashboard via [PyPI](https://pypi.org/project/optuna-dash
 $ pip install optuna-dashboard
 ```
 
-Also, you can install following optional dependencies to make optuna-dashboard faster.
-
-```console
-$ pip install optuna-fast-fanova gunicorn
-```
-
 ## Getting Started
 
 First, please specify the storage URL to persistent your study using the [RDB backend](https://optuna.readthedocs.io/en/stable/tutorial/20_recipes/001_rdb.html).
@@ -49,56 +43,7 @@ Listening on http://localhost:8080/
 Hit Ctrl-C to quit.
 ```
 
-<details>
-
-<summary>More command line options</summary>
-
-```console
-$ optuna-dashboard -h
-usage: optuna-dashboard [-h] [--port PORT] [--host HOST] [--version] [--quiet] storage
-
-Real-time dashboard for Optuna.
-
-positional arguments:
-  storage        DB URL (e.g. sqlite:///example.db)
-
-optional arguments:
-  -h, --help            show this help message and exit
-  --port PORT           port number (default: 8080)
-  --host HOST           hostname (default: 127.0.0.1)
-  --server {wsgiref,gunicorn}
-                        server (default: auto)
-  --artifact-dir ARTIFACT_DIR
-                        directory to store artifact files
-  --version, -v         show program's version number and exit
-  --quiet, -q           quiet
-```
-
-</details>
-
-<details>
-
-<summary>Python Interface</summary>
-
-**`run_server(storage: Union[str, BaseStorage], host: str = 'localhost', port: int = 8080) -> None`**
-
-Start running optuna-dashboard and blocks until the server terminates.
-This function uses wsgiref module which is not intended for the production use.
-
-**`wsgi(storage: Union[str, BaseStorage]) -> WSGIApplication`**
-
-This function exposes WSGI interface for people who want to run on the
-production-class WSGI servers like Gunicorn or uWSGI.
-
-**`save_note(study_or_trial: Union[Study, Trial], body: str) -> None`**
-
-Save the note (Markdown format) to the Study or the Trial.
-
-**`set_objective_names(study: Study, names: list[str]) -> None`**
-
-Set the names of objectives.
-
-</details>
+Please check out [our documentation](https://optuna-dashboard.readthedocs.io) for more details.
 
 ## Using an official Docker image
 
diff --git a/docs/getting-started.rst b/docs/getting-started.rst
new file mode 100644
index 00000000..324f0b35
--- /dev/null
+++ b/docs/getting-started.rst
@@ -0,0 +1,204 @@
+Getting Started
+===============
+
+Installation
+------------
+
+Prerequisite
+~~~~~~~~~~~~
+
+Optuna Dashboard supports Python 3.7 or newer.
+
+
+Installing from PyPi
+~~~~~~~~~~~~~~~~~~~~
+
+You can install optuna-dashboard via `PyPI <https://pypi.org/project/optuna-dashboard/>`_ or `Anaconda Cloud <https://anaconda.org/conda-forge/optuna-dashboard>`_.
+
+.. code-block:: console
+
+    $ pip install optuna-dashboard
+
+Also, you can install following optional dependencies to make optuna-dashboard faster.
+
+.. code-block:: console
+
+   $ pip install optuna-fast-fanova gunicorn
+
+Installing from the source code
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+Since it requires to build TypeScript files, ``pip install git+https://.../optuna-dashboard.git`` does not actually work.
+Please clone the git repository and execute following commands to build sdist package:
+
+.. code-block:: console
+
+   $ git clone git@github.com:optuna/optuna.git
+   $ cd optuna
+
+.. code-block:: console
+
+   # Node.js v16 is required to compile TypeScript files.
+   $ npm install
+   $ npm run build:prd
+   $ python setup.py sdist
+
+Then you can install it like:
+
+.. code-block:: console
+
+   $ pip install dist/optuna-dashboard-x.y.z.tar.gz
+
+See `CONTRIBUTING.md <https://github.com/optuna/optuna/blob/master/CONTRIBUTING.md>`_ for more details.
+
+
+Command-line Interface
+----------------------
+
+The most common usage of Optuna Dashboard is using the command-line interface.
+Assuming that Optuna's optimization history is persisted using ``RDBStorage``,
+you can use the command line interface like ``optuna-dashboard <STORAGE_URL>``.
+
+.. code-block:: python
+
+    import optuna
+
+    def objective(trial):
+        x = trial.suggest_float("x", -100, 100)
+        y = trial.suggest_categorical("y", [-1, 0, 1])
+        return x**2 + y
+
+    study = optuna.create_study(
+        storage="sqlite:///db.sqlite3",  # Specify the storage URL here.
+        study_name="quadratic-simple"
+    )
+    study.optimize(objective, n_trials=100)
+    print(f"Best value: {study.best_value} (params: {study.best_params})")
+
+
+.. code-block:: console
+
+   $ optuna-dashboard sqlite:///db.sqlite3
+   Listening on http://localhost:8080/
+   Hit Ctrl-C to quit.
+
+If you are using JournalStorage classes introduced in Optuna v3.1, you can use them like below:
+
+.. code-block:: console
+
+   # JournalFileStorage
+   $ optuna-dashboard ./path/to/journal.log
+
+   # JournalRedisStorage
+   $ optuna-dashboard redis://localhost:6379
+
+
+Using an official Docker image
+------------------------------
+
+You can also use `an official Docker image <https://github.com/optuna/optuna-dashboard/pkgs/container/optuna-dashboard>`_ instead of setting up your Python environment.
+The Docker image only supports SQLite3, MySQL(PyMySQL), and PostgreSQL(Psycopg2).
+
+**SQLite3**
+
+.. code-block:: console
+
+   $ docker run -it --rm -p 8080:8080 -v `pwd`:/app -w /app ghcr.io/optuna/optuna-dashboard sqlite:///db.sqlite3
+
+
+**MySQL (PyMySQL)**
+
+.. code-block:: console
+
+   $ docker run -it --rm -p 8080:8080 ghcr.io/optuna/optuna-dashboard mysql+pymysql://username:password@hostname:3306/dbname
+
+**PostgreSQL (Psycopg2)**
+
+.. code-block:: console
+
+   $ docker run -it --rm -p 8080:8080 ghcr.io/optuna/optuna-dashboard postgresql+psycopg2://username:password@hostname:5432/dbname
+
+Python Interface
+----------------
+
+Python interfaces are also provided for users who want to use other storage implementations (e.g. ``InMemoryStorage``).
+You can use :func:`~optuna_dashboard.run_server` function like below:
+
+.. code-block:: python
+
+    import optuna
+    from optuna_dashboard import run_server
+
+    def objective(trial):
+        x = trial.suggest_float("x", -100, 100)
+        y = trial.suggest_categorical("y", [-1, 0, 1])
+        return x**2 + y
+
+    storage = optuna.storages.InMemoryStorage()
+    study = optuna.create_study(storage=storage)
+    study.optimize(objective, n_trials=100)
+
+    run_server(storage)
+
+
+Using Gunicorn or uWSGI server
+------------------------------
+
+Optuna Dashboard uses `wsgiref <https://docs.python.org/3/library/wsgiref.html>`_ module, which is in the Python's standard libraries, by default.
+However, as described `here <https://github.com/python/cpython/blob/v3.11.0/Lib/wsgiref/simple_server.py#L3-L7>`_, ``wsgiref`` is implemented for testing or debugging purpose.
+You can switch to other WSGI server implementations by using :func:`~optuna_dashboard.wsgi` function.
+
+.. code-block:: python
+
+   :caption: wsgi.py
+
+   from optuna.storages import RDBStorage
+   from optuna_dashboard import wsgi
+
+   storage = RDBStorage("sqlite:///db.sqlite3")
+   application = wsgi(storage)
+
+Then please execute following commands to start.
+
+.. code-block:: console
+
+   $ pip install gunicorn
+   $ gunicorn --workers 4 wsgi:application
+
+or
+
+.. code-block:: console
+
+   $ pip install uwsgi
+   $ uwsgi --http :8080 --workeers 4 --wsgi-file wsgi.py
+
+
+Google Colaboratory
+-------------------
+
+When you want to check the optimization history on Google Colaboratory,
+you can use ``google.colab.output()`` function as follows:
+
+.. code-block:: python
+
+   import optuna
+   import threading
+   from google.colab import output
+   from optuna_dashboard import run_server
+
+   def objective(trial):
+       x = trial.suggest_float("x", -100, 100)
+       return (x - 2) ** 2
+
+   # Run optimization
+   storage = optuna.storages.InMemoryStorage()
+   study = optuna.create_study(storage=storage)
+   study.optimize(objective, n_trials=100)
+
+   # Start Optuna Dashboard
+   port = 8081
+   thread = threading.Thread(target=run_server, args=(storage,), kwargs={"port": port})
+   thread.start()
+   output.serve_kernel_port_as_window(port, path='/dashboard/')
+
+Then please open http://localhost:8081/dashboard to browse.
diff --git a/docs/index.rst b/docs/index.rst
index c12e83c4..71a0a66e 100644
--- a/docs/index.rst
+++ b/docs/index.rst
@@ -12,7 +12,7 @@ Real-time dashboard for `Optuna <https://github.com/optuna/optuna>`_.
    :maxdepth: 3
    :caption: Contents:
 
-   installation
+   getting-started
    api
    errors
 
diff --git a/docs/installation.rst b/docs/installation.rst
deleted file mode 100644
index c8fb2ac1..00000000
--- a/docs/installation.rst
+++ /dev/null
@@ -1,17 +0,0 @@
-Installation
-============
-
-Optuna Dashboard supports Python 3.7 or newer.
-
-We recommend to install Optuna via pip:
-You can install optuna-dashboard via `PyPI <https://pypi.org/project/optuna-dashboard/>`_ or `Anaconda Cloud <https://anaconda.org/conda-forge/optuna-dashboard>`_.
-
-.. code-block:: console
-
-    $ pip install optuna-dashboard
-
-Also, you can install following optional dependencies to make optuna-dashboard faster.
-
-.. code-block:: console
-
-   $ pip install optuna-fast-fanova gunicorn