Maestro Server

Maestro Server is an open source software platform for management and discovery servers, apps and system for Hybrid IT. Can manage small and large environments, be able to visualize the latest multi-cloud environment state.

Demo

To test out the demo, Demo Online

Documentation

Maestro Server - Discovery API

Discovery App is a crawler accountable to connect to cloud providers.

To manager and authenticate on each cloud provider
Translate cloud data to maestro data.

Core API:

API Rest
Worker - Scan
Worker - Translate
Worker - Insert
Worker - Notification

TechStack

Python <3.4
Flask
Celery
RabbitMq

Connect to:

Maestro Data

Setup

Installation by docker

version: '2'

services:
discovery:
    image: maestroserver/discovery-maestro
    ports:
    - "5000:5000"
    environment:
    - "CELERY_BROKER_URL=amqp://rabbitmq:5672"
    - "MAESTRO_DATA_URI=http://data:5010"

discovery-celery:
    image: maestroserver/discovery-maestro-celery
    environment:
    - "CELERY_BROKER_URL=amqp://rabbitmq:5672"
    - "MAESTRO_DATA_URI=http://data:5010"
    - "MAESTRO_AUDIT_URI=http://audit:10900"
    - "MAESTRO_SERVER_URI=http://server:8888"

Dev Env

cd devtools/

docker-compose up -d

Configure rabbitmq service in .env file

CELERY_BROKER_URL="amqp://localhost:5672"
CELERYD_TASK_TIME_LIMIT=30

Install pip dependences

pip install -r requeriments.txt

Run server

python -m flask run.py

or

FLASK_APP=run.py FLASK_DEBUG=1 flask run

or 

npm run server

Run workers

celery -A app.celery worker -E -Q discovery --hostname=discovery@%h --loglevel=info

or 

npm run celery

Run all tests

python -m unittest discover

Create doc

npm install
apidoc -i app/controller/ -o docs/

Env variables

Env Variables	Example	Description
MAESTRO_DATA_URI	http://localhost:5005	Data App - API URL
MAESTRO_AUDIT_URI	http://localhost:10900	Audit App - API URL
MAESTRO_SERVER_URI	http://localhost:8888	Server App - API URL
MAESTRO_WEBSOCKET_URI	http://localhost:8000	Websocket App - API URL

FLASK_ENV	development	production
MAESTRO_GWORKERS	2	Gunicorn multi process
MAESTRO_TRANSLATE_QTD	200	Prefetch used in translate worker
MAESTRO_COUNTDOWN_LAST	10	Time in seconds to run the last task
MAESTRO_COUNTDOWN_WS	2	Delayed time to run ws notification

MAESTRO_SECRETJWT	XXXX	Secret key - JWT for connections
MAESTRO_WEBSOCKET_SECRET	XXXX	Secret Key - JWT Websocket connections
MAESTRO_SECRETJWT_PRIVATE	XXX	Secret Key - JWT private connections
MAESTRO_NOAUTH	XXX	Secret Pass to validate private connections

CELERY_BROKER_URL	XXXX	Rabbitmq URL
CELERYD_TASK_TIME_LIMIT	500	Timeout - worker

Contribute

Are you interested in developing Maestro Server, creating new features or extending them?

We created a set of documentation, explaining how to set up your development environment, coding styles, standards, learn about the architecture and more. Welcome to the team and contribute with us.

See our developer guide

Contact

We may be able to resolve support queries via email. Please send me a message here

Donate

I have made Maestro Server with my heart, think to solve a real operation IT problem. Its not easy, take time and resources.

The donation will be user to:

Create new features, implement new providers.
Maintenance libs, securities flaws, and technical points.

hteo1337/discovery-api