logging-azure-rest

Python Logging Azure Workspace OMS Extension

This package provides an asynchronous solution for uploading application logs to an Azure Log Workspace using their provided REST API, all supplied as a handler and service extension for python builtin logging module.

The service works by instantiating an always-alive (non-daemonized) thread connected to a log request pool in which logs will be queued, then periodically running through the pool in order to send the requests in bulk using the requests package. This is all to intend logging safely without interrupting or slowing down the main process execution as transparently as possible.

Installation

For installing via the distributed package via PyPi:

$ pip install logging-azure-rest

Or if you which to install from the source, you can checkout the git repository and install using setuptools:

$ python setup.py install

Usage

Package Configuration

The following environment variables are read to configure the extension and are required:

• AZURE_LOG_CUSTOMER_ID: Customer ID for the Azure Log Workspace
• AZURE_LOG_SHARED_KEY: Customer shared key for the Azure Log Workspace
• AZURE_LOG_DEFAULT_NAME: The default "log type" name to indicate where the logs are stored. This will be suffixed with "_CL" within the Azure Log Workspace.

The following environment variables are read to tweak some parameters of the extension, they all have default values and therefore are optional:

• AZURE_LOG_SEND_FREQUENCY: Default: 5 How many seconds the service thread should wait before sending pooled logs.

Logging Configuration

As you would any other handler, you only require to define a handler using the logging_azure.handler.AzureLogServiceHandler class:

[...]
    "handlers": {
        "console": {"level": logging.DEBUG, "class": "logging.StreamHandler", "formatter": "colorize"},
        "azure_log_oms": {
            "level": logging.INFO, "class": "logging_azure.handler.AzureLogServiceHandler", "formatter": "azure"
        },
        "default": {"level": logging.INFO, "class": "logging.StreamHandler", "formatter": "default"},
    },
[...]

Then add the handler to your selected logger instance:

[...]
    "loggers": {
        LOGGER_NAME: {
            "handlers": ["console"] if IS_LOCAL_DEV_INSTANCE else ["default", "azure_log_oms"],
            "level": LOG_LEVEL,
            "propagate": True,
        }
    },
[...]

Recommendations

Set an appropriate log level minimum

In order to prevent additional cost from Azure Log OMS ingestion for talkative applications, it is recommended to set an adequate LOG_LEVEL for your application (avoid logging.DEBUG for example).

It is also recommended configuring your loggers appropriately so the AzureLogServiveHandler isn't used during local development or CI environments for example.

You are warned.

Set a clear formatter for messages

This package supplies a decent amount of information already to complement the message in a clean way by reading the log record in order to facilitate Azure Log OMS Queries and ingestion, so you may only require using a specific formatter that will only format the message itself as follows:

[...]
    "formatters": {
        "default": {
            "format": '[%(asctime)s] %(levelname)s %(name)s %(module)s "%(message)s"',
            "datefmt": "%d/%b/%Y %H:%M:%S",
        },
        "azure": {
            "format": '%(message)s',
        },
[...]

This provides the following output within the Azure Portal for example:

This allows for easily creating custom queries and alerts for your application directly from the Azure Log OMS solution.

Useful links

• Create a Log Analytics workspace in the Azure portal
• Create a Log Analytics workspace with Azure CLI 2.0
• Manage access to log data and workspaces in Azure Monitor
• Azure Monitor pricing

Package requirements

• requests
• injector