doc: Update Backend.AI production installation guide doc (#1796)

changes/1796.doc.md

@@ -0,0 +1 @@
+Update Backend.AI production installation guide doc

docs/dev/development-setup.rst

@@ -239,7 +239,7 @@ Open yet another terminal for client and run:
 .. code-block:: console
 
    $ source ./env-local-admin-api.sh  # Use the generated local endpoint and credential config.
-   $ # source ./env-local-user-api.sh  # Yo may choose an alternative credential config.
+   $ # source ./env-local-user-api.sh  # You may choose an alternative credential config.
    $ ./backend.ai config
    $ ./backend.ai run python --rm -c 'print("hello world")'
    ∙ Session token prefix: fb05c73953

docs/install/install-from-package/install-agent.rst

@@ -87,7 +87,7 @@ would be:
    scratch-size = "1G"
 
    [watcher]
-   service-addr = { host = "bai-m1", port = 6009 }
+   service-addr = { host = "bai-a01"", port = 6009 }
    ssl-enabled = false
    target-service = "backendai-agent.service"
    soft-reset-available = false
@@ -189,6 +189,9 @@ First, create a runner script at ``${HOME}/bin/run-agent.sh``:
       export HOME="/home/bai"
    fi
 
+   # -- If you have installed using static python --
+   source .venv/bin/activate
+
    # -- If you have installed using pyenv --
    if [ -z "$PYENV_ROOT" ]; then
       export PYENV_ROOT="$HOME/.pyenv"

docs/install/install-from-package/install-manager.rst

@@ -264,6 +264,9 @@ First, create a runner script at ``${HOME}/bin/run-manager.sh``:
       export HOME="/home/bai"
    fi
 
+   # -- If you have installed using static python --
+   source .venv/bin/activate
+
    # -- If you have installed using pyenv --
    if [ -z "$PYENV_ROOT" ]; then
       export PYENV_ROOT="$HOME/.pyenv"

docs/install/install-from-package/install-storage-proxy.rst

@@ -148,6 +148,9 @@ First, create a runner script at ``${HOME}/bin/run-storage-proxy.sh``:
       export HOME="/home/bai"
    fi
 
+   # -- If you have installed using static python --
+   source .venv/bin/activate
+
    # -- If you have installed using pyenv --
    if [ -z "$PYENV_ROOT" ]; then
       export PYENV_ROOT="$HOME/.pyenv"

docs/install/install-from-package/install-webserver.rst

@@ -67,8 +67,7 @@ would be:
 
    [ui]
    brand = "Backend.AI"
-   default_environment = "cr.backend.ai/stable/python"
-   default_import_environment = "cr.backend.ai/filebrowser:21.02-ubuntu20.04"
+   menu_blocklist = "pipeline"
 
    [api]
    domain = "default"
@@ -89,6 +88,65 @@ would be:
 
    [license]
 
+   [webserver]
+
+   [logging]
+   # One of: "NOTSET", "DEBUG", "INFO", "WARNING", "ERROR", "CRITICAL"
+   # Set the global logging level.
+   level = "INFO"
+
+   # Multi-choice of: "console", "logstash", "file"
+   # For each choice, there must be a "logging.<driver>" section
+   # in this config file as exemplified below.
+   drivers = ["console", "file"]
+
+   [logging.console]
+   # If set true, use ANSI colors if the console is a terminal.
+   # If set false, always disable the colored output in console logs.
+   colored = true
+
+   # One of: "simple", "verbose"
+   format = "verbose"
+
+   [logging.file]
+   # The log file path and filename pattern.
+   # All messages are wrapped in single-line JSON objects.
+   # Rotated logs may have additional suffixes.
+   # For production, "/var/log/backend.ai" is recommended.
+   path = "./logs"
+   filename = "webserver.log"
+
+   # Set the maximum number of recent container coredumps in the coredump directory.
+   # Oldest coredumps are deleted if there is more than this number of coredumps.
+   backup-count = 10
+
+   # The log file size to begin rotation.
+   rotation-size = "10M"
+
+   [logging.logstash]
+   # The endpoint to publish logstash records.
+   endpoint = { host = "localhost", port = 9300 }
+
+   # One of: "zmq.push", "zmq.pub", "tcp", "udp"
+   protocol = "tcp"
+
+   # SSL configs when protocol = "tcp"
+   ssl-enabled = true
+   ssl-verify = true
+
+   # Specify additional package namespaces to include in the logs
+   # and their individual log levels.
+   # Note that the actual logging level applied is the conjunction of the global logging level and the
+   # logging levels specified here for each namespace.
+   [logging.pkg-ns]
+   "" = "WARNING"
+   "aiotools" = "INFO"
+   "aiohttp" = "INFO"
+   "ai.backend" = "INFO"
+
+   [debug]
+   enabled = false
+
    [plugin]
 
    [pipeline]
@@ -127,6 +185,9 @@ First, create a runner script at ``${HOME}/bin/run-webserver.sh``:
       export HOME="/home/bai"
    fi
 
+   # -- If you have installed using static python --
+   source .venv/bin/activate
+
    # -- If you have installed using pyenv --
    if [ -z "$PYENV_ROOT" ]; then
       export PYENV_ROOT="$HOME/.pyenv"

docs/install/install-from-package/os-preparation.rst

@@ -113,11 +113,51 @@ information on the Python version compatibility can be found at
 `here <https://github.com/lablup/backend.ai#package-installation-guide#python-version-compatibility>`_.
 
 There can be several ways to prepare a specific Python version. Here, we will be
-using pyenv and pyenv-virtualenv.
+using a standalone static built Python.
 
+Use a standalone static built Python (Recommended)
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+Obtain distribution of `a standalone static built Python <https://github.com/indygreg/python-build-standalone/releases>`_ according to required 
+python version, target machine architecture and etc. Then extract the distribution 
+to a directory of your choice.
+
+.. code-block:: console
+
+   $ curl -L "https://github.com/indygreg/python-build-standalone/releases/download/${PYTHON_RELEASE_DATE}/cpython-${PYTHON_VERSION}+${PYTHON_RELEASE_DATE}-${TARGET_MACHINE_ARCHITECTURE}-${ARCHIVE_FLAVOR}.tar.gz" > cpython-${PYTHON_VERSION}+${PYTHON_RELEASE_DATE}-${TARGET_MACHINE_ARCHITECTURE}-${ARCHIVE_FLAVOR}.tar.gz
+   $ tar -xf "cpython-${PYTHON_VERSION}+${PYTHON_RELEASE_DATE}-${TARGET_MACHINE_ARCHITECTURE}-${ARCHIVE_FLAVOR}.tar.gz"
+   $ mkdir -p "/home/${USERNAME}/.static-python/versions"
+   $ mv python "/home/${USERNAME}/.static-python/versions/${PYTHON_VERSION}"
+
+For example,
+
+.. code-block:: console
+
+   $ curl -L "https://github.com/indygreg/python-build-standalone/releases/download/20231002/cpython-3.11.6+20231002-x86_64-unknown-linux-gnu-install_only.tar.gz" > cpython-3.11.6+20231002-x86_64-unknown-linux-gnu-install_only.tar.gz
+   $ tar -xf "cpython-3.11.6+20231002-x86_64-unknown-linux-gnu-install_only.tar.gz"
+   $ mkdir -p "/home/bai/.static-python/versions"
+   $ mv python "/home/bai/.static-python/versions/3.11.6"
+
+Then, you can create multiple virtual environments per service. To create a
+virtual environment for Backend.AI Manager and activate it, for example, you may run:
+
+.. code-block:: console
+
+   $ mkdir "${HOME}/manager"
+   $ cd "${HOME}/manager"
+   $ ~/.static-python/versions/3.11.6/bin/python3 -m venv .venv
+   $ source .venv/bin/activate
+   $ pip install -U pip setuptools wheel
+
+You also need to make ``pip`` available to the Python installation with the
+latest ``wheel`` and ``setuptools`` packages, so that any non-binary extension
+packages can be compiled and installed on your system.
 
-Use pyenv to manually build and select a specific Python version
+
+
+(Alternative) Use pyenv to manually build and select a specific Python version
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+If you prefer, there is no problem using pyenv and pyenv-virtualenv.
 
 Install `pyenv <https://github.com/pyenv/pyenv>`_ and
 `pyenv-virtualenv <https://github.com/pyenv/pyenv-virtualenv>`_. Then, install
@@ -150,14 +190,6 @@ latest ``wheel`` and ``setuptools`` packages, so that any non-binary extension
 packages can be compiled and installed on your system.
 
 
-Use a standalone static built Python
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-
-We can `use a standalone static built Python <https://github.com/indygreg/python-build-standalone/releases>`_.
-
-.. warning:: Details will be added later.
-
-
 Configure network aliases
 -------------------------
 

docs/install/install-from-package/prepare-cache-service.rst

@@ -3,7 +3,7 @@ Prepare Cache Service
 
 Backend.AI makes use of Redis as its main cache service. Launch the service
 using docker compose by generating the file
-``$HOME/halfstack/docker-compose.hs.redis.yaml`` and populating it with the
+``$HOME/halfstack/redis-cluster-default/docker-compose.yaml`` and populating it with the
 following YAML. Feel free to adjust the volume paths and port settings. Please
 refer
 `the latest configuration <https://github.com/lablup/backend.ai/blob/main/docker-compose.halfstack-main.yml>`_
@@ -50,9 +50,9 @@ Execute the following command to start the service container. The project
 
 .. code-block:: console
 
-   $ cd ${HOME}/halfstack
-   $ docker compose -f docker-compose.hs.redis.yaml -p ${USER} up -d
+   $ cd ${HOME}/halfstack/redis-cluster-default
+   $ docker compose up -d
    $ # -- To terminate the container:
-   $ # docker compose -f docker-compose.hs.redis.yaml -p ${USER} down
+   $ # docker compose down
    $ # -- To see the container logs:
-   $ # docker compose -f docker-compose.hs.redis.yaml -p ${USER} logs -f
+   $ # docker compose logs -f

docs/install/install-from-package/prepare-config-service.rst

@@ -3,7 +3,7 @@ Prepare Config Service
 
 Backend.AI makes use of Etcd as its main config service. Launch the service
 using docker compose by generating the file
-``$HOME/halfstack/docker-compose.hs.etcd.yaml`` and populating it with the
+``$HOME/halfstack/etcd-cluster-default/docker-compose.yaml`` and populating it with the
 following YAML. Feel free to adjust the volume paths and port settings. Please
 refer
 `the latest configuration <https://github.com/lablup/backend.ai/blob/main/docker-compose.halfstack-main.yml>`_
@@ -59,9 +59,9 @@ Execute the following command to start the service container. The project
 
 .. code-block:: console
 
-   $ cd ${HOME}/halfstack
-   $ docker compose -f docker-compose.hs.etcd.yaml -p ${USER} up -d
+   $ cd ${HOME}/halfstack/etcd-cluster-default
+   $ docker compose up -d
    $ # -- To terminate the container:
-   $ # docker compose -f docker-compose.hs.etcd.yaml -p ${USER} down
+   $ # docker compose down
    $ # -- To see the container logs:
-   $ # docker compose -f docker-compose.hs.etcd.yaml -p ${USER} logs -f
+   $ # docker compose logs -f

docs/install/install-from-package/prepare-database.rst

@@ -3,7 +3,7 @@ Prepare Database
 
 Backend.AI makes use of PostgreSQL as its main database. Launch the service
 using docker compose by generating the file
-``$HOME/halfstack/docker-compose.hs.postgres.yaml`` and populating it with the
+``$HOME/halfstack/postgres-cluster-default/docker-compose.yaml`` and populating it with the
 following YAML. Feel free to adjust the volume paths and port settings. Please
 refer
 `the latest configuration <https://github.com/lablup/backend.ai/blob/main/docker-compose.halfstack-main.yml>`_
@@ -22,7 +22,7 @@ refer
    services:
       backendai-pg-active:
          <<: *base
-         image: postgres:13.2-alpine
+         image: postgres:15.1-alpine
          restart: unless-stopped
          command: >
             postgres
@@ -58,9 +58,9 @@ Execute the following command to start the service container. The project
 
 .. code-block:: console
 
-   $ cd ${HOME}/halfstack
-   $ docker compose -f docker-compose.hs.postgres.yaml -p ${USER} up -d
+   $ cd ${HOME}/halfstack/postgres-cluster-default
+   $ docker compose up -d
    $ # -- To terminate the container:
-   $ # docker compose -f docker-compose.hs.postgres.yaml -p ${USER} down
+   $ # docker compose down
    $ # -- To see the container logs:
-   $ # docker compose -f docker-compose.hs.postgres.yaml -p ${USER} logs -f
+   $ # docker compose logs -f