From: Taewan Kim Date: Wed, 29 Mar 2023 09:57:17 +0000 (+0900) Subject: Update installation-guide.rst X-Git-Url: https://gerrit.o-ran-sc.org/r/gitweb?a=commitdiff_plain;h=51ad61e5af093d433ec0cc9b6276542abc03d0b1;p=aiml-fw%2Faimlfw-dep.git Update installation-guide.rst Issue-Id: AIMLFW-39 Signed-off-by: Taewan Kim Change-Id: I0fd7dcffb81b93850c45257355b3d23ad8596179 --- diff --git a/docs/installation-guide.rst b/docs/installation-guide.rst index 648346c..c80b3c3 100644 --- a/docs/installation-guide.rst +++ b/docs/installation-guide.rst @@ -43,7 +43,7 @@ Introduction This document describes the supported software and hardware configurations for the reference component as well as providing guidelines on how to install and configure such reference system. -The audience of this document is assumed to have good knowledge in RAN network nd Linux system. +The audience of this document is assumed to have good knowledge in RAN network and Linux system. Hardware Requirements @@ -52,10 +52,10 @@ Hardware Requirements Below are the minimum requirements for installing the AIMLFW -1. OS: Ubuntu 18.04 server -2. 8 cpu cores -3. 16 GB RAM -4. 60 GB harddisk +#. OS: Ubuntu 18.04 server +#. 8 cpu cores +#. 16 GB RAM +#. 60 GB harddisk Software Installation and Deployment ------------------------------------ @@ -66,8 +66,9 @@ Software Installation and Deployment git clone "https://gerrit.o-ran-sc.org/r/aiml-fw/aimlfw-dep" cd aimlfw-dep -Update recipe file “RECIPE_EXAMPLE/example_recipe_latest_stable.yaml” which includes update of VM IP and datalake details -Note: In case the Influx DB datalake is not available, this can be skipped at this stage and can be updated after installing datalake. +Update recipe file :file:`RECIPE_EXAMPLE/example_recipe_latest_stable.yaml` which includes update of VM IP and datalake details. + +**Note**: In case the Influx DB datalake is not available, this can be skipped at this stage and can be updated after installing datalake. .. code:: bash @@ -89,7 +90,7 @@ Check the AIMLFW dashboard by using the following url http://localhost:32005/ -In case Influx DB datalake not available, it can be installed using the steps mentioned in section “Install influx db as datalake”. Once installed the access details of the datalake can be updated in RECIPE_EXAMPLE/example_recipe_latest_stable.yaml . Once updated, follow the below steps for reinstall of some components: +In case Influx DB datalake not available, it can be installed using the steps mentioned in section :ref:`install-influx-db-as-datalake`. Once installed the access details of the datalake can be updated in :file:`RECIPE_EXAMPLE/example_recipe_latest_stable.yaml`. Once updated, follow the below steps for reinstall of some components: .. code:: bash @@ -112,11 +113,14 @@ Software Uninstallation bin/uninstall_traininghost.sh +.. _install-influx-db-as-datalake: + Install Influx DB as datalake ----------------------------- .. code:: bash + helm repo add bitnami https://charts.bitnami.com/bitnami helm install my-release bitnami/influxdb kubectl exec -it bash @@ -130,10 +134,10 @@ eg: {"id":"0a576f4ba82db000","token":"xJVlOom1GRUxDNkldo1v","status":"active", Use the tokens further in the below configurations and in the recipe file. -Following are the steps to add qoe data to influx DB +Following are the steps to add qoe data to Influx DB. -Execute below from inside influx Db container to create a bucket: +Execute below from inside Influx DB container to create a bucket: .. code:: bash @@ -148,7 +152,7 @@ Install the following dependencies sudo pip3 install influxdb_client -Use the insert.py in ric-app/qp repository to upload the qoe data in influx DB +Use the :file:`insert.py` in ``ric-app/qp repository`` to upload the qoe data in Influx DB .. code:: bash @@ -156,9 +160,9 @@ Use the insert.py in ric-app/qp repository to upload the qoe data in influx DB git clone https://gerrit.o-ran-sc.org/r/ric-app/qp cd qp/qp -update insert.py file with the following content: +Update :file:`insert.py` file with the following content: -.. code:: bash +.. code-block:: python import pandas as pd from influxdb_client import InfluxDBClient @@ -213,7 +217,7 @@ update insert.py file with the following content: populatedb() -Update in insert.py file +Update ```` in :file:`insert.py` file Follow below command to port forward to access Influx DB @@ -227,7 +231,7 @@ To insert data: python3 insert.py -To check inserted data in Influx DB , execute below command inside the influx DB container: +To check inserted data in Influx DB , execute below command inside the Influx DB container: .. code:: bash @@ -252,9 +256,9 @@ Create namespace using command below kubectl create namespace kserve-test -Create qoe.yaml file with below contents +Create :file:`qoe.yaml` file with below contents -.. code:: bash +.. code-block:: yaml apiVersion: "serving.kserve.io/v1beta1" kind: "InferenceService" @@ -274,7 +278,7 @@ Create qoe.yaml file with below contents memory: 0.5Gi -To deploy model update the Model URL in the qoe.yaml file and execute below command to deploy model +To deploy model update the Model URL in the :file:`qoe.yaml` file and execute below command to deploy model .. code:: bash @@ -297,9 +301,12 @@ Use below command to obtain Ingress port for Kserve. kubectl get svc istio-ingressgateway -n istio-system Obtain nodeport corresponding to port 80. -In the below example, the port is 31206 -NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE -istio-ingressgateway LoadBalancer 10.105.222.242 15021:31423/TCP,80:31206/TCP,443:32145/TCP,31400:32338/TCP,15443:31846/TCP 4h15m +In the below example, the port is 31206. + +.. code:: + + NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE + istio-ingressgateway LoadBalancer 10.105.222.242 15021:31423/TCP,80:31206/TCP,443:32145/TCP,31400:32338/TCP,15443:31846/TCP 4h15m Create predict.sh file with following contents @@ -309,9 +316,9 @@ Create predict.sh file with following contents model_name=qoe-model curl -v -H "Host: $model_name.kserve-test.example.com" http://:/v1/models/$model_name:predict -d @./input_qoe.json -Update the IP of host where Kserve is deployed and ingress port of Kserve obtained using above method. +Update the ``IP`` of host where Kserve is deployed and ingress port of Kserve obtained using above method. -Create sample data for predictions in file input_qoe.json. Add the following content in input_qoe.json file. +Create sample data for predictions in file :file:`input_qoe.json`. Add the following content in :file:`input_qoe.json` file. .. code:: bash