logger-to-kibana

---

This project is inteded to generate view from the log messages encountered.

The python executable can be found in https://pypi.org/project/logger-to-kibana/

You will need to install the dependences by running

pip install -r requirements.txt

To get the programs help just type:

python main.py

This returns:

  Usage: main.py [OPTIONS] COMMAND [ARGS]...

  Process the file provided according to conditions

Options:
  --help  Show this message and exit.

Commands:
  pommands:
  process                    Process the folder
  process_and_generate       Process the folder and generate visualization
  process_generate_and_send  Process the folder, generate visualization and
                             send

I have created a dev.to series explaining how this project works and any learning that I have taken from doing so. You can find it in https://dev.to/ismaelmartinez/setting-up-my-first-opensource-python-project-4k1o

Default settings

The default settings can be found in the settings.ini file. You can provide a different settings file by specifying it as an environment variable LOGGER_TO_KIBANA_CONFIG

commands

The current available commands are:

process

Process a folder and prints out the processed functions/logs in the following format:

[{'subfolder': '<folder_name>', 'filename': '<filename>', 'function': '<function_name>', 'type': '<log_type>', 'query': 'message: "<log_filter>"', 'label': '<log_type>: <log_filter>'}]

To execute the command run:

python main.py process -f <folder_location>

Check the table under How does it work section to get more info about log_type and log_filter.

process_and_generate

Process a folder (as shown in the process section) and generates a table visualization for kibana.

To execute the command run:

python main.py process_and_generate -f <folder_location>

process_generate_and_send

Process a folder, generates a table visualization for kibana and send it to kibana (currently in localhost:5601)

To execute the command run:

python main.py process_and_generate -f <folder_location>

How does it work

By default, it scans for files under the folder specified and with the pattern app/src/**/*.py. You can specify another patter in the FilesMatchFilter in the settings.ini

This program uses different regex detectors to filter logs and files to process.

Those can be changed in the settings.ini file.

The current available detectors are:

Detector	Default Value	Propose
FilesMatchFilter	app/src/**/*.py	Filter the files to process in the provided folder
FunctionMappingDetector	def	Detect a function
FunctionMappingFilter	(?<=def ).*?(?=()	Filter the function name
LogDebugDetector	LOG.debug	Detect the log debug message
LogDebugFilter	(?<=LOG.debug(["']).*?(?=["'])	Filter the log debug message
LogInfoDetector	LOG.info	Detect the log info message
LogInfoFilter	(?<=LOG.info(["']).*?(?=["'])	Filter the log info message
LogWarnDetector	LOG.warn	Detect the log warn message
LogWarnFilter	(?<=LOG.warn(["']).*?(?=["'])	Filter the log warn message
LogErrorDetector	LOG.error	Detect the log error message
LogErrorFilter	(?<=LOG.error(["']).*?(?=["'])	Filter the log error message
LogCriticalDetector	LOG.critical	Detect the log critical message
LogCriticalFilter	(?<=LOG.critical(["']).*?(?=["'])	Filter the log critical message
LogExceptionDetector	LOG.exception	Detect the log exception message
LogExceptionFilter	(?<=LOG.exception(["']).*?(?=["'])	Filter the log exception message

Other configuration available in the settings.ini file are:

Type	Value	Propose
BaseUrl	http://localhost:5601	Kibana base url
Index	59676040-e7fd-11e9-9209-1f165c3af176	Kibana index
VisualizationType	metric	Type of visualization to generate. Valid options are metric or table
AuthType	None	Authentication Type. You can use 'aws' to use requests_aws4auth to authenticate with aws

The process

The commands for the application are done in the following logical order.

process -> generate -> send

As an example, when processing a file in tests/unit/resources/example.py with the content:

def lambda_handler(_event: dict, _context):
    LOG.debug('Initialising')
    LOG.info('Processing')
    LOG.warn('Success')
    LOG.error('Failure')
    LOG.critical('Bananas')
    LOG.exception('Exception')
)

Will return the next object:

[{'subfolder': 'resources', 'filename': 'example.py', 'function': 'lambda_handler', 'type': 'debug', 'query': 'message: "Initialising"', 'label': 'debug: Initialising'},
{'subfolder': 'resources', 'filename': 'example.py', 'function': 'lambda_handler','type': 'info', 'query': 'message: "Processing"', 'label': 'info: Processing'},
{'subfolder': 'resources', 'filename': 'example.py', 'function': 'lambda_handler', 'type': 'warn', 'query': 'message: "Success"', 'label': 'warn: Success'},
{'subfolder': 'resources', 'filename': 'example.py', 'function': 'lambda_handler', 'type': 'error', 'query': 'message: "Failure"', 'label': 'error: Failure'},
{'subfolder': 'resources', 'filename': 'example.py', 'function': 'lambda_handler', 'type': 'critical', 'query': 'message: "Bananas"', 'label': 'critical: Bananas'},
{'subfolder': 'resources', 'filename': 'example.py', 'function': 'lambda_handler', 'type': 'exception', 'query': 'message: "Exception"', 'label': 'exception: Exception'}]

It will generate a metric visualization with filters for all the logs that have found.

Those visualisations will be split by function, then filename and then subfolder.

You can change the type of visualization generated by modifying the VisualizationType in the settings.ini. The current available values are metric or table. The default value is metric.

To finish, it sends the generated visualization to Kibana with the following name format:

[Generated - <folder> <subfolder> <filename> <function> ]

Limitations

It does not detect logs assign to variables or constants. They will not appear in your visualizations. #40 should address this.