azure-storage-logging 0.5.1

Logging handlers to send logs to Microsoft Azure Storage

azure-storage-logging provides functionality to send output from the standard Python logging APIs to Microsoft Azure Storage.

Dependencies

• azure-storage 0.33 or newer

Installation

Install the package via pip:

pip install azure-storage-logging

Usage

The module azure_storage_logging.handlers in the package contains the following logging handler classes. Each of them uses a different type of Microsoft Azure Storage to send its output to. They all are subclasses of the standard Python logging handler classes, so you can make use of them in the standard ways of Python logging configuration.

In addition to the standard formats for logging, the special format %(hostname)s is also available in your message formatter for the handlers. The format is introduced for ease of identifying the source of log messages which come from many computers and go to the same storage.

TableStorageHandler

The TableStorageHandler class is a subclass of logging.Handler class, and it sends log messages to Azure table storage and store them as entities in the specified table.

The handler puts a formatted log message from applications in the message property of a table entity along with some system-defined properties (PartitionKey, RowKey, and Timestamp) like this:

PartitionKey	RowKey	Timestamp	message
XXXXX	XXXXXXXXX	YYYY-MM-DD …	log message
XXXXX	XXXXXXXXX	YYYY-MM-DD …	log message
XXXXX	XXXXXXXXX	YYYY-MM-DD …	log message

• class azure_storage_logging.handlers.TableStorageHandler(account_name=None, account_key=None, protocol=’https’, table=’logs’, batch_size=0, extra_properties=None, partition_key_formatter=None, row_key_formatter=None, is_emulated=False)

  Returns a new instance of the TableStorageHandler class. The instance is initialized with the name and the key of your Azure Storage account and some optional parameters.

  The table specifies the name of the table that stores log messages. A new table will be created if it doesn’t exist. The table name must conform to the naming convention for Azure Storage table, see the naming convention for tables for more details.

  The protocol specifies the protocol to transfer data between Azure Storage and your application, http and https are supported.

  You can specify the batch_size in an integer if you want to use batch transaction when creating new log entities. If the batch_size is greater than 1, all new log entities will be transferred to the table at a time when the number of new log messages reaches the batch_size. Otherwise, a new log entity will be transferred to the table every time a logging is performed. The batch_size must be up to 100 (maximum number of entities in a batch transaction for Azure Storage table).

  The extra_properties accepts a sequence of the formats for logging. The handler-specific one %(hostname)s is also acceptable. The handler assigns an entity property for every format specified in extra_properties. Here is an example of using extra properties:

  import logging
  from azure_storage_logging.handlers import TableStorageHandler
  
  # configure the handler and add it to the logger
  logger = logging.getLogger('example')
  handler = TableStorageHandler(account_name='mystorageaccountname',
                                account_key='mystorageaccountkey',
                                extra_properties=('%(hostname)s',
                                                  '%(levelname)s'))
  logger.addHandler(handler)
  
  # output log messages
  logger.info('info message')
  logger.warning('warning message')
  logger.error('error message')

  And it will create the log entities, that have the extra properties in addition to the regular property message, into the table like this:

  PartitionKey	RowKey	Timestamp	hostname	levelname	message
  XXXXX	XXXXXXXXX	YYYY-MM-DD …	myhost	INFO	info message
  XXXXX	XXXXXXXXX	YYYY-MM-DD …	myhost	WARNING	warn message
  XXXXX	XXXXXXXXX	YYYY-MM-DD …	myhost	ERROR	error message

  You can specify an instance of your custom logging.Formatters for the partition_key_formatter or the row_key_formatter if you want to implement your own keys for the table. The default formatters will be used for partition keys and row keys if no custom formatter for them is given to the handler. The default values for partition keys are provided by the format %(asctime)s and the date format %Y%m%d%H%M (provides a unique value per minute). The default values for row keys are provided by the format %(asctime)s%(msecs)03d-%(hostname)s-%(process)d-%(rowno)02d and the date format %Y%m%d%H%M%S.

  Note that the format %(rowno)d is a handler-specific one only available for row keys. It would be formatted to a sequential and unique number in a batch that starts from 0. The format is introduced to avoid collision of row keys generated in a batch, and it would always be formatted to 0 if you don’t use batch transaction for logging to the table.

• setPartitionKeyFormatter(fmt)

  Sets the handler’s formatter for partition keys to fmt.

• setRowKeyFormatter(fmt)

  Sets the handler’s formatter for row keys to fmt.

QueueStorageHandler

The QueueStorageHandler class is a subclass of logging.Handler class, and it pushes log messages to specified Azure storage queue.

You can pop log messages from the queue in other applications using Azure Storage client libraries.

• class azure_storage_logging.handlers.QueueStorageHandler(account_name=None, account_key=None, protocol=’https’, queue=’logs’, message_ttl=None, visibility_timeout=None, base64_encoding=False, is_emulated=False)

  Returns a new instance of the QueueStorageHandler class. The instance is initialized with the name and the key of your Azure Storage account and some optional parameters.

  The queue specifies the name of the queue that log messages are added. A new queue will be created if it doesn’t exist. The queue name must conform to the naming convention for Azure Storage queue, see the naming convention for queues for more details.

  The protocol specifies the protocol to transfer data between Azure Storage and your application, http and https are supported.

  The message_ttl specifies the time-to-live interval for the message, in seconds. The maximum time-to-live allowed is 7 days. If this parameter is omitted, the default time-to-live is 7 days.

  The visibility_timeout specifies the visibility timeout value, in seconds, relative to server time. If not specified, the default value is 0 (makes the message visible immediately). The new value must be larger than or equal to 0, and cannot be larger than 7 days. The visibility_timeout cannot be set to a value later than the message_ttl, and should be set to a value smaller than the message_ttl.

  The base64_encoding specifies the necessity for encoding log text in Base64. If you set this to True, Unicode log text in a message is encoded in utf-8 first and then encoded in Base64. Some of Azure Storage client libraries or tools assume that text messages in Azure Storage queue are encoded in Base64, so you can set this to True to receive log messages correctly with those libraries or tools.

BlobStorageRotatingFileHandler

The BlobStorageRotatingFileHandler class is a subclass of logging.handlers.RotatingFileHandler class. It performs log file rotation and stores the outdated one in Azure blob storage container when the current file reaches a certain size.

• class azure_storage_logging.handlers.BlobStorageRotatingFileHandler(filename, mode=’a’, maxBytes=0, encoding=None, delay=False, account_name=None, account_key=None, protocol=’https’, container=’logs’, zip_compression=False, max_connections=1, max_retries=5, retry_wait=1.0, is_emulated=False)

  Returns a new instance of the BlobStorageRotatingFileHandler class. The instance is initialized with the name and the key of your Azure Storage account and some optional parameters.

  See RotatingFileHandler for its basic usage. The handler keeps the latest log file into the local file system. Meanwhile, the handler sends the outdated log file to the blob container immediately and then removes it from the local file system.

  The container specifies the name of the blob container that stores outdated log files. A new container will be created if it doesn’t exist. The container name must conform to the naming convention for Azure Storage blob container, see the naming convention for blob containers for more details.

  The protocol specifies the protocol to transfer data between Azure Storage and your application, http and https are supported.

  The zip_compression specifies the necessity for compressing every outdated log file in zip format before putting it in the container.

  The max_connections specifies a maximum number of parallel connections to use when the blob size exceeds 64MB. Set to 1 to upload the blob chunks sequentially. Set to 2 or more to upload the blob chunks in parallel, and this uses more system resources but will upload faster.

  The max_retries specifies a number of times to retry upload of blob chunk if an error occurs.

  The retry_wait specifies sleep time in secs between retries.

  The only two formatters %(hostname)s and %(process)d are acceptable as a part of the filename or the container. You can save log files in a blob container dedicated to each host or process by naming containers with these formatters, and also can store log files from multiple hosts or processes in a blob container by naming log files with them.

  Be careful to use the %(process)d formatter in the filename because inconsistent PIDs assigned to your application every time it gets started are included as a part of the name of log files to search for rotation. You should use the formatter in the filename only when the log file is generated by a long-running application process.

  Note that the hander class doesn’t take the backupCount parameter, unlike RotatingFileHandler does. The number of outdated log files that the handler stores in the container is unlimited, and the files are saved with the extension that indicates the time in UTC when they are replaced with a new one. If you want to keep the amount of outdated log files in the container in a certain number, you will need to do that using Azure management portal or other tools.

BlobStorageTimedRotatingFileHandler

The BlobStorageTimedRotatingFileHandler class is a subclass of logging.handlers.TimedRotatingFileHandler class. It performs log file rotation and stores the outdated one to Azure blob storage container at certain timed intervals.

• class azure_storage_logging.handlers.BlobStorageTimedRotatingFileHandler(filename, when=’h’, interval=1, encoding=None, delay=False, utc=False, account_name=None, account_key=None, protocol=’https’, container=’logs’, zip_compression=False, max_connections=1, max_retries=5, retry_wait=1.0, is_emulated=False)

  Returns a new instance of the BlobStorageTimedRotatingFileHandler class. The instance is initialized with the name and the key of your Azure Storage account and some optional parameters.

  See TimedRotatingFileHandler for its basic usage. The handler keeps the latest log file into the local file system. Meanwhile, the handler sends the outdated log file to the blob container immediately and then removes it from the local file system.

  The container specifies the name of the blob container that stores outdated log files. A new container will be created if it doesn’t exist. The container name must conform to the naming convention for Azure Storage blob container, see the naming convention for blob containers for more details.

  The protocol specifies the protocol to transfer data between Azure Storage and your application, http and https are supported.

  The zip_compression specifies the necessity for compressing every outdated log file in zip format before putting it in the container.

  The max_connections specifies a maximum number of parallel connections to use when the blob size exceeds 64MB. Set to 1 to upload the blob chunks sequentially. Set to 2 or more to upload the blob chunks in parallel, and this uses more system resources but will upload faster.

  The max_retries specifies a number of times to retry upload of blob chunk if an error occurs.

  The retry_wait specifies sleep time in secs between retries.

  The only two formatters %(hostname)s and %(process)d are acceptable as a part of the filename or the container. You can save log files in a blob container dedicated to each host or process by naming containers with these formatters, and also can store log files from multiple hosts or processes in a blob container by naming log files with them.

  Be careful to use the %(process)d formatter in the filename because inconsistent PIDs assigned to your application every time it gets started are included as a part of the name of log files to search for rotation. You should use the formatter in the filename only when the log file is generated by a long-running application process.

  Note that the hander class doesn’t take the backupCount parameter, unlike TimedRotatingFileHandler does. The number of outdated log files that the handler stores in the container is unlimited. If you want to keep the amount of outdated log files in the container in a certain number, you will need to do that using Azure management portal or other tools.

Example

Here is an example of the configurations and the logging that uses three different types of storage from the logger:

LOGGING = {
    'version': 1,
    'formatters': {
        'simple': {
            'format': '%(asctime)s %(message)s',
        },
        'verbose': {
            'format': '%(asctime)s %(levelname)s %(hostname)s %(process)d %(message)s',
        },
        # this is the same as the default, so you can skip configuring it
        'partition_key': {
            'format': '%(asctime)s',
            'datefmt': '%Y%m%d%H%M',
        },
        # this is the same as the default, so you can skip configuring it
        'row_key': {
            'format': '%(asctime)s%(msecs)03d-%(hostname)s-%(process)d-%(rowno)02d',
            'datefmt': '%Y%m%d%H%M%S',
        },
    },
    'handlers': {
        'file': {
            'account_name': 'mystorageaccountname',
            'account_key': 'mystorageaccountkey',
            'protocol': 'https',
            'level': 'DEBUG',
            'class': 'azure_storage_logging.handlers.BlobStorageTimedRotatingFileHandler',
            'formatter': 'verbose',
            'filename': 'example.log',
            'when': 'D',
            'interval': 1,
            'container': 'logs-%(hostname)s',
            'zip_compression': False,
        },
        'queue': {
            'account_name': 'mystorageaccountname',
            'account_key': 'mystorageaccountkey',
            'protocol': 'https',
            'queue': 'logs',
            'level': 'CRITICAL',
            'class': 'azure_storage_logging.handlers.QueueStorageHandler',
            'formatter': 'verbose',
        },
        'table': {
            'account_name': 'mystorageaccountname',
            'account_key': 'mystorageaccountkey',
            'protocol': 'https',
            'table': 'logs',
            'level': 'INFO',
            'class': 'azure_storage_logging.handlers.TableStorageHandler',
            'formatter': 'simple',
            'batch_size': 20,
            'extra_properties': ['%(hostname)s', '%(levelname)s'],
            'partition_key_formatter': 'cfg://formatters.partition_key',
            'row_key_formatter': 'cfg://formatters.row_key',
        },
    },
    'loggers': {
        'example': {
            'handlers': ['file', 'queue', 'table'],
            'level': 'DEBUG',
        },
    }
}

import logging
from logging.config import dictConfig

dictConfig(LOGGING)
logger = logging.getLogger('example')
logger.debug('debug message')
logger.info('info message')
logger.warning('warning message')
logger.error('error message')
logger.critical('critical message')

Notice

• Set is_emulated to True at initialization of the logging handlers if you want to use this package with Azure storage emulator.

License

Apache License 2.0

Credits

• Michiya Takahashi