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adding feedback from Alejandro to clarify instructions #48

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89 changes: 56 additions & 33 deletions README.md
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Original file line number Diff line number Diff line change
Expand Up @@ -7,8 +7,10 @@ This repository contains the [Pyrrha](https://github.com/Pyrrha-Platform/Pyrrha)
This service wakes up every minute and calculates time weighted average exposures for all fire fighters and compares them to the configured limits.

## Contents

- [Contents](#contents)
- [Prerequisites](#prerequisites)
- [Running MariaDB](#running-mariadb)
- [Run locally with Python](#run-locally-with-python)
- [Run locally with Docker](#run-locally-with-docker)
- [Run on Kubernetes](#run-on-kubernetes)
Expand All @@ -18,37 +20,43 @@ This service wakes up every minute and calculates time weighted average exposure
- [License](#license)

## Prerequisites

1. [Docker](https://docs.docker.com/desktop/)
2. [IBM CLI](https://cloud.ibm.com/docs/cli?topic=cli-install-ibmcloud-cli)
2. [Docker-Compose](https://docs.docker.com/compose/)
3. [Kubectl](https://kubernetes.io/docs/tasks/tools/install-kubectl/)
4. [Helm](https://helm.sh/docs/intro/install/)
5. [Skaffold](https://skaffold.dev/docs/install/)
6. [IBM CLI](https://cloud.ibm.com/docs/cli?topic=cli-install-ibmcloud-cli)

## Running MariaDB

MariaDB is a prerequisite for running the rules and decision engine service. Follow the instructions in [Pyrrha-Database repository](https://github.com/Pyrrha-Platform/Pyrrha-Database) to build and run MariaDB locally using Docker. The following steps assume you have MariaDB running locally as a standalone service or as a docker container.

## Run locally with Python
You can run this solution locally in docker as follows

1. Set up environment variables in the `src/.env` file
2. Install mariadb locally
1. pull mariadb from dockerhub
```
docker pull mariadb
```
2. run the image
```
docker run -p 3306:3306 --name pyrrha-mariadb -e MYSQL_ROOT_PASSWORD='' -d mariadb
```
3. Test the image - TBD
3. Create python virtual environment
1. Copy `src/.env.example` to `src/.env` and fill out with MariaDB credentials that you set up in the previous step.
```
MARIADB_HOST=localhost
MARIADB_PORT=3306
MARIADB_USERNAME=root
MARIADB_PASSWORD=${MDB_PASSWORD}
MARIADB_DB=pyrrha
```
2. Create python virtual environment
```
python3 -m venv python3
python3 -m venv python3
```
4. Activate virtual environment
3. Activate virtual environment
```
source python3/bin/activate
source python3/bin/activate
```
4. Install the dependencies
```
pip install -r requirements.txt
```
5. Run the application
```
python src/core_decision_flask_app.py 8080
python src/core_decision_flask_app.py 8080
```
6. You should see the following output
```
Expand All @@ -58,17 +66,32 @@ You can run this solution locally in docker as follows
WARNING: Do not use the development server in a production environment.
Use a production WSGI server instead.
* Debug mode: off
* Running on http://0.0.0.0:8080/ (Press CTRL+C to quit)
Use a production WSGI server instead.
* Debug mode: off
INFO:werkzeug: * Running on http://0.0.0.0:8080/ (Press CTRL+C to quit)
```

## Run locally with Docker

If you are running MariaDB as a docker container, we recommend you use the build file located in the [Pyrrha-Deployment-Configurations](https://github.com/Pyrrha-Platform/Pyrrha-Deployment-Configurations) repository to start the rules and decision engine service. Run the following after configuring the services as explained in [the instructions](https://github.com/Pyrrha-Platform/Pyrrha-Deployment-Configurations/blob/main/Docker_Compose.md).

```
docker-compose up --build pyrrha-rulesdecision
```
You can stop the services with:
```
docker-compose stop pyrrha-rulesdecision
```

If you want to run build and run this image as a docker container and not use docker-compose, you can follow these steps:

1. Build the image
```
docker build . -t rulesdecision
```
2. Run the image
```
docker run -p8080:8080 -t rulesdecision
docker build . -t rulesdecision
```
2. Run the image using the following command. Notice we are passing in the `src/.env` file as environment variable. This will not work if MariaDB is running in a docker image as `localhost:3306` will not resolve to the right image.
```
docker run -p8080:8080 --env-file src/.env -t rulesdecision
```
3. You should see the application logs
```
Expand All @@ -80,25 +103,25 @@ You can run this solution locally in docker as follows
* Debug mode: off
* Running on http://0.0.0.0:8080/ (Press CTRL+C to quit)
```
You can also use docker-compose to run all the services by using the build file located in the [Pyrrha-Deployment-Configurations](https://github.com/Pyrrha-Platform/Pyrrha-Deployment-Configurations) repository.

## Run on Kubernetes
You can run this application on Kubernetes. The skaffold.yaml file let's you quickly run the application on the cluster by using [Skaffold](https://skaffold.dev/docs/pipeline-stages/deployers/helm/). There are two profiles provided. To run the solution on the `test` namespace use:
```
skaffold dev -p test
```

You can run this application on Kubernetes using the helm charts provided in [Pyrrha-Deployment-Configurations](https://github.com/Pyrrha-Platform/Pyrrha-Deployment-Configurations/tree/main/k8s) repository. The [skaffold.yaml](https://github.com/Pyrrha-Platform/Pyrrha-Rules-Decision/blob/main/skaffold.yaml) file provided here let's you quickly run the application on the cluster by using [Skaffold](https://skaffold.dev/docs/pipeline-stages/deployers/helm/). There are two profiles provided. To run the solution on the `test` namespace use:
`skaffold dev -p test`

## Troubleshooting

1. Database does not connect
1. ensure `.env` file has the correct values for database connection
2. Change the db password

## Built with

* Docker
* MariaDB
* Flask
* [IBM Kubernetes Service](https://cloud.ibm.com/kubernetes/overview)

- Docker
- MariaDB
- Flask
- [IBM Kubernetes Service](https://cloud.ibm.com/kubernetes/overview)

## Contributing

Expand Down