Clone this repository:

git clone https://github.com/GabrielZuany/ElasticSearchLoggs.git

Install and run Docker in your machine (for local development).

Go to elastic-config and run the compose file to pull the necessary images:

cd elastic-config
docker compose up

Then await a few seconds and check the 2 urls below:

• http://localhost:9200/
• http://localhost:5601/

You must see these two windows:

• Elastic response:

• Elastic Interface:

So now your environment is setted up and ready to receive loggings from your Python application!

Creating a Data View based in an index pattern:

Check your new data view and associated indexes!

Create and activate the Virtual Environment:

python -m venv .venv
.venv/Scripts/Activate.ps1

Install the requirements:

pip install -r requirements.txt

Import the ElasticSearchLogging class to your source code and create an object to manipulate logs:

import ElasticsearchLogs.ElasticsearchLogging as esl

logging_sender = esl.ElasticsearchLogging(
  host="localhost",
  port=9200
  index=DEFAULT_INDEX
)

Once your setted up the host and port (and also index if you already have one), you can just send logs to Kibana:

import uuid

logger.info(message="Hello World!", user_id=uuid.uuid4())

try:
    res = 1 / 0
except Exception as e:
    logger.error(message="Error", user_id=uuid.uuid4(), exception=e)

Your logs also going to be writen in console.

Local logs (Console):