Python Ranger

Before you start, you might wanna check Ranger for more details. You'll need it to follow some jargon being used in this readme.

There are 3 sections in here.

1. Ranger Service Finder
2. Ranger Service Provider
3. Ranger Daemon

Ranger Service Finder

A service finder in Ranger is something can be used to discover individual host:port pairs of a distributed service which allows clients to connect and request for services (make http calls). This finding is done using zookeeper. The following python class helps you do the same for any python based service/tool. It follows the same data models as present in the main ranger java library. (which is paramount for this to work across languages).

Similar details can be found at PyPi

Installation

python3.9 -m pip install python-ranger-tn

Usage

import requests
from rangermodels import *
from servicefinder import RangerServiceFinder, RoundRobinNodeSelector

## Create the ranger service provider
ranger = RangerServiceFinder(cluster_details=ClusterDetails(zk_string='localhost:2181', update_interval_in_secs=1),
                             namespace="org",
                             services=["serviceA", "serviceB"],
                             selector=RoundRobinNodeSelector())  # optional
# or in one line
ranger = RangerServiceFinder(ClusterDetails('localhost:2181'), "org", ["serviceA", "serviceB"])

## Start the updates in background (this is important)
ranger.start()

## Get one of the healthy nodes to make requests
node = ranger.get_node("serviceA")
response = requests.get(node.get_endpoint() + "/my/api")
node = ranger.get_node("serviceA")
response_again = requests.get(node.get_endpoint(secure=True) + "/my/secure/api")

## to get the full list of healthy nodes
nodes = ranger.get_all_nodes("serviceB")

## When you wish to clean up
ranger.stop()

Details

The above sample shows how to set up a service finder for 2 services. You get the node and then fetch the relevant details from the node. There would be one background thread created, that continuously refreshes updates from zookeeper. There is support for being able to apply a custom criteria based filter just like in the java lib(check criteria_filter) The only difference you might see from the java implementation, is the registration of services before the start (In the java lib, the expectation is to create one service finder per service, here we create one finder for all services that may be required for by your python app)

---

Ranger Service Provider

A service provider in Ranger does the opposite. It can a way to broadcast that a service is available at some host: port, where clients can connect and request services (make http calls). This broadcast is essentially done using zookeeper. The following python class helps you do the same for any python based service/tool. Again, it follows the same data models as present in the main ranger java library.

Usage

from rangermodels import *
from serviceprovider import RangerServiceProvider, HealthCheck

# Create the ranger service provider
ranger = RangerServiceProvider(cluster_details=ClusterDetails(zk_string='localhost:2181', update_interval_in_secs=1),
                               service_details=ServiceDetails(host='localhost', port=12211, environment='stage',
                                                              namespace='myorg',
                                                              service_name='python-test'),
                               health_check=HealthCheck(url='localhost:12211/health', scheme=UrlScheme.GET))

## Or in 2 lines
ranger = RangerServiceProvider(ClusterDetails('localhost:2181'),
                               ServiceDetails('localhost', 12211, 'stage', 'myorg', 'python-test'))

## Start the updates in background (this will update zookeeper at regular intervals)
ranger.start()

## You may also start the updates and block your current thread (until we hit an interrupt)
ranger.start(block=True)

## When you wish to stop updates
ranger.stop()

Details

The above sample shows how to set up a background thread, that does the job of publishing regular updates to zk. You can optionally provide a healthcheck url, which will receive a ping at regular intervals. A HEALTHY broadcast will only be done if the ping check was successful. You can check HealthCheck to customize the URL to your needs.

---

Ranger Daemon setup

This section deals with using the code as a simple light daemon that can run alongside your software (but outside it) to provide regular service discovery updates to zookeeper. As usual, check Ranger for more details.

Intent

Ideally, you would directly use the standard Ranger java client to deeply integrate the service's health updates with ranger.

In scenarios where you can't do the above, you can rely on this daemon. Say you need discovery updates to be published for a service written in a langauge other than java, or you are unable to add the ranger dependency directly, in your java application.

The intent of this daemon is to run along-side your software and publish updates, as long as your software is up and healthy. Currently, support has been added for a dockerized setup, as well as an import based custom setup. Currently, Support has been provided for the following:

1. Simple usage
2. Import based usage
3. Docker multi-container setup

1. Simple usage

If you just wish to invoke the script directly, clone the project and follow along the helper. Your command would look something like this

python3.9 serviceprovider/ranger_daemon.py -zk localhost:2181 -s myapp -host localhost -p 12211 -n org -e stage -hcu 'http://localhost:12211/healthcheck?pretty=true'

2. Import Based Usage

You can also choose to run the daemon from within another python file, by forwarding the command line arguments. Install the package first, as shown below

python3.9 -m pip install python-ranger-tn

import sys
from serviceprovider.ranger_daemon import ranger_daemon_trigger

ranger_daemon_trigger(sys.argv[1:])

3. Docker Based

Imagine a scenario where you already have a docker application, but you want to run this daemon alongside the container, to make the existing container discoverable, without having to code up an integration with ranger. The following is a solution to this problem. You can use docker compose to run your service and this daemon as a multi container docker application.
After this, your existing container should be ready for service discovery.

Docker containers are available on the DockerHub.

The following docker command can be used to start the daemon, using environment variables. The table below explains the various environment variables required to run the script

Env Variable	Description
HOST	Hostname
PORT	Port
RANGER_ZK	Zookeeper connection string
SERVICE_NAME	Name of service
ENV	Environment (stage/prod)
NAMESPACE	Namespace in zookeeper
HEALTH_CHECK	[optional] GET healthcheck URL to be used for pings
REGION	[optional] Region value
TAGS	[optional] Comma separated tags

docker run --rm -d -e RANGER_ZK=<zookeeper_info> -e SERVICE_NAME=<name_of_service> -e HOST=<host_of_machine> -e PORT=<port> -e ENV=<environment> -e NAMESPACE=<namespace> -e HEALTH_CHECK=<health_check_url> --name python-ranger-daemon tusharknaik/python-ranger-daemon:1.8.4

Here is an example for running it on a Mac machine, assuming your zookeeper is already running on localhost:2181 ( notice the network being set to host and zookeeper being sent as host.docker.internal for connecting to localhost from within docker)

docker run --rm -d --network host -e RANGER_ZK=host.docker.internal:2181 -e SERVICE_NAME=python-test -e HOST=localhost -e PORT=12211 -e ENV=stage -e NAMESPACE=myorg -e HEALTH_CHECK="localhost:12211/health" --name python-ranger-daemon tusharknaik/python-ranger-daemon:1.8.4

---

Under the hood

The daemon/thread will write data to zookeeper in the following format (datamodel from ranger):

{
  "host": "localhost",
  "port": 12211,
  "nodeData": {
    "environment": "stage",
    "tags": [
      "identity",
      "auth"
    ],
    "region": "IN-nm"
  },
  "healthcheckStatus": "healthy",
  "lastUpdatedTimeStamp": 1639044989841
}

Updates will be published in the path: /$NAMESPACE/$SERVICE_NAME at a periodic intervals of --interval (default: 1 second)

The following will be taken care of:

• Infinite retry and connection reattempts in case of zk connection issues
• Proper cleanup of zk connections to get rid of ephemeral nodes
• Proper logging
• Does continuous health check pings on a particular health check url if required [optional]