A library for python-based application logging and data collection


License
ISC
Install
pip install blueox==0.11.3

Documentation

BlueOx - A python application logging framework

BlueOx is a python based logging and data collection framework. The problem it attempts to solve is one where you have multiple python processes across multiple hosts processing some sort of requests. You generally want to collect:

  • Performance data (counters, timers, etc)
  • User activity
  • Errors (and debugging data)

Use BlueOx to record that data, aggregate it to a central logging server where it can be written to disk.

In addition, it's often useful to be able to plug reporting scripts into the logging server so as to generate live stats and reports or do ad hoc analysis.

BlueOx's collection functionality is fairly advanced allowing heirarchies of collectors and queuing in the event of failure. For example, it's recommend to run an instance of oxd on each host, and then configure each of those collectors to forward log events to a central collector on a dedicated log machine.

BlueOx is named after Paul Bunyan's Blue Ox "Babe". A great help for giant logging problems.

Installation

BlueOx requires Python 2.7, ZeroMQ and MsgPack.

The full python library requirements are given requirements.txt and is designed to be used with virtualenv.

Tornado is not required for operation of BlueOx, but development and running tests will likely require it.

I expect debian packaging will be developed soon.

Application Integration

Applications emit BlueOx events by using a context manager and globally accessible BlueOx functions.

Events have a type, which indicates what will be ultimately logged together.

Events also have an id that can be used to tie them together with other related events.

For example, in a web application, an application might choose the use BlueOx as follows:

def handle(request):
    with blueox.Context('request'):
        blueox.set('user_agent', self.headers['UserAgent'])

        with blueox.timeit('request_time'):
            do_stuff()

        blueox.set('response.status', self.response.status)
        blueox.set('response.size', len(self.response.body))

The above sample would generate one event that contains all the details about a specific request.

Contexts can be heirarchical. This means you can generate sub-events that are related to the parent event and can be joined together in post-processing by the common id they share. Indicate you want this behavior for your context by naming with a prefixing '.'.

For example, inside some application code (in do_stuff() above), you might execute some SQL queries.

def execute(cursor, query, args):
    with blueox.Context('.db):
        blueox.set('query', query)
        with blueox.timeit('query_time'):
            res = cursor.execute(query, args)
        blueox.set('row_count', len(res))
    return res

Each SQL query would then be logged as a seperate event. However, each event will have the unique id provided by the parent request context. The name of the context will become request.db.

Where your context fits into the heirarchy can also be controlled. For example, if you wanted to ensure all your SQL logging was in the same event name, you would base your new context on the top-level using the prefix ^:

def execute(cursor, query, args):
    with blueox.Context('^.db):
        blueox.set('query', query)
    return res

Or, if you know exactly what the heirarchy looks like, you can directly specifify the event name:

def execute(cursor, query, args):
    with blueox.Context('request.db):
        blueox.set('query', query)
    return res

BlueOx also provides the ability to do sampling. This means only a set percentage of generated events will actually be logged. You can choose sampling based on any level of the context:

with blueox.Context('.memcache', sample=('..', 0.25)):
    blueox.set('key', key)
    client.set(key, value)

In the above example, only 25% of requests will include the memcache data. If the sample argument where ('memcache', 0.25) then 25% of all memcache events would be logged.

Configuration

If BlueOx has not been explicitly configured, all the calls to BlueOx will essentially be no-ops. This is rather useful in testing contexts so as to not generate a bunch of bogus data.

For production use, you'll need to set the collection host:

blueox.default_configure()

This will use the default of 127.0.0.1:3514 or respect the environment variable BLUEOX_HOST. Alternately, you can explicitly configure a host:

blueox.default_configure("hostname")

Logging module integration

BlueOx comes with a log handler that can be added to your logging module setup for easy integration into existing logging setups.

For example:

handler = blueox.LogHandler()
handler.setLevel(logging.INFO)
logging.getLogger('').addHandler(handler)

By default, all log event will show up as a sub-event .log but this can be configured by passing a type_name to the LogHandler

Tornado Integration

BlueOx comes out of the box with support for Tornado web server. This is particularly challenging since one of the goals for BlueOx is to, like the logging module, have globally accessible contexts so you don't have to pass anything around to have access to all the heirarchical goodness.

Since you'll likely want to have a context per web request, special care must be taken to work around tornado's async machinery. Fear not, batteries included: blueox.tornado_utils

The most straightfoward way to integrate BlueOx into a tornado application requires two things:

  1. Include blueox.tornado_utils.BlueOxRequestHandlerMixin to create a context for each request
  2. Use or re-implement the provided base request handler blueox.tornado_utils.SampleRequestHandler This puts helpful data into your context, like URI, method and the like.
  3. If using coroutines, (tornado.gen) you'll need to use blueox.tornado_utils.coroutine which is wrapper that supports context switching.

If you are using the autoreload module for tornado, you should also add a call to shutdown() as a reload hook to avoid leaking file descriptors.

See tests/tornado_app.py for an example of all this.

Flask Integration

BlueOx also has Flask integration. The basic integration provides logging all requests, their environment data, headers, url, ip, response code, response size. Optionally if there are request.user.id, request.version, or request.key, they are also logged. Furthermore, all uncaught user exceptions that occur during a request are also logged to BlueOx.

To setup Flask integration please take a look at the following example:

Flask Code Example:

```python
from flask import Flask
from blueox.contrib.flask import BlueOxMiddleware

app = Flask(__name__)
app.config.from_object("some.object.that.includes.blueox.config")

BlueOxMiddleware(app)
```

By default, BlueOx will log to a running oxd instance on localhost. This can be configured via Flask ApplicationConfig object:

Flask Configuration Example:

```python
class ApplicationConfig(object):
    BLUEOX_HOST = 'hostname'
    BLUEOX_NAME = 'myapp'
```

Setting BLUEOX_HOST = None will disable logging. This may be helpful in a testing context.

Django Integration

BlueOx provides middleware that can be plugged in to any Django application.

MIDDLEWARE_CLASSES.append('blueox.contrib.django.middleware.Middleware')

Default settings should work fine, but BlueOx can be customized by setting something like the following:

BLUEOX_HOST='hostname'
BLUEOX_NAME='myapp'

The request keys are someone similiar between Tornado integration and Django, except that it's assumed Django is running under WSGI, where certain items like headers are not given raw.

It's recommmended that you also include BlueOx as a logging handler. You should do something like:

LOGGING {
    'handlers':
       ...
       'blueox': {
           'level': 'INFO',
           'class': 'blueox.LogHandler',
       },
       ...
    'loggers':
      '': {
          'handlers': ['blueox', ..],
      },
}

BlueOx also detects use of 'Dealer' middleware which adds a revision key to your request indicating the SCM version of your application. This will be included as a version.

Systems Integration

If all your application logs are collected via BlueOx, you might want to use the same for other system level log files. The oxingest command allows you use BlueOx's transport for any general line based input.

For example, in a shell script:

echo "I'm all done" | oxingest notices

If you want to monitor existing log files:

oxingest -F /var/log/syslog -F /var/log/mail.err

Type names will be inferred by the filenames provided, but that often isn't good enough. Try:

oxingest -F nginx_access:/var/log/nginx/access.log -F nginx_error:/var/log/nginx/error.log

Event Collection

Events are collected by a BlueOx daemon (oxd) and can be configured in a variety of topologies.

It's recommended that you run a BlueOx daemon on each host, and then a master BlueOx daemon that collects all the streams together for logging. In this configuration, failure of the centralized collector would not result in any data loss as the local instances would just queue up their events.

So on your local machine, you'd run:

oxd --forward=hostname

And on the master collection machine, you'd run:

oxd --collect="*" --log-path=/var/log/blueox/

Events will be logged individually in log files for each day. You can also specify specify rotation hours to create logs more frequently. This is useful if you want to archive your logs more frequently or the size of the files starts to become prohibitively large for easy analysis.

oxd --log-path=/var/log/blueox --rotate-hours=2

Now you can connect to oxd and get a live streaming of log data:

oxview -H hostname --type-name="request*"

Note the use of '*' to indicate a prefix query for the type filter. This will return all events with a type that begins with 'request'

Of course you'll want to access these logs once they are stored on disk. Logs are encoded in the MsgPack format (http://msgpack.org/), so you'll need some tooling for doing log analysis. This is easily done with the tool oxview.

You access the files directly, for example:

cat /var/log/blueox/120310/request-120310.log | oxview

Where request is the event type you're interested in.

You can also use the provided tool to manage log files and even archive and retrive them from S3.

Keep your logs small by zipping them up:

oxstore zip --log-path=/var/log/blueox

If you don't need to keep everything:

oxstore prune --log-path=/var/log/blueox --retain-days=7

Retrieve your log data over a date span

oxstore cat --log-path=/var/log/blueox --start=20120313 --end=20120315 request

Store your zipped logs in an S3 bucket:

oxstore upload --log-path=/var/log/blueox --bucket=example-ox --zipped-only

Most usefully, you can combine your maintenance tasks into one command:

oxstore archive --log-path=/var/log/blueox --bucket=example-ox

Retrieve your logs back from S3:

oxstore cat --bucket=example-ox --start=20120313 --end=20120315 request

Or if you want to see your local logs for the last few hours (assuming an hourly rotation)

oxstore cat --local --log-path=/var/log/blueox --start="20120313 12:00" request | oxview -p

Dealing with Failure

When an oxd instance becomes unavailable, clients will spool messages in memory up to some internal limit. After hitting this limit, exceptions will be logged.

For an oxd forwarding to another oxd, the only limit is how much memory the process can allocate.

A Note About Ports

There are several types of network ports in use with BlueOx:

  1. Control Port (default 3513)
  2. Collection Port (default 3514)
  3. Streaming Port (randomonly assigned from 35000 to 36000)

Both the Control and Collection ports are configurable from the command line.

When configuring forwarding between oxd instances, you'll want to always use the collection port.

When configuring an application to send data to a oxd instance, you'll want to use the collection port as well.

For administrative (and oxview work) you'll use the control port. The control port (and BlueOx administrative interface) can be used to discover all the other ports. The reason the collection port must be configured explicitly for actual logging purposes is to better handle reconnects and failures.

The streaming port is used for clients to retrieve live data from oxd. This port is allocated randomly in the range 35000 to 36000, the client will retrieve the actual port using a request through the control port.

Administration

Use the oxctl tool to collect useful stats or make other adjustments to a running oxd instance.

For example:

oxctl

Reporting

oxstash

oxstash is a tool that can ship blueox logs to a running elasticsearch cluster where it can be used with the tool Kibana to explore and generate reports and dashboards.

oxstash can be setup in a few ways.

The defaults are essentially:

$ oxstash -p blueox -n "*" -e "localhost:9200"

This would ship all logs from the local oxd instance to the elasticsearch node running on port 9200. These logs will be stored indexes named blueox-[YYYY.MM.DD] which is similiar to logstash's scheme.

You can also use oxstash to ship existing log files, by simply:

$ oxstash < requests.log

If you have logs that need particular filtering or manipulation, you can still use oxstash as part of your pipeline.

$ cat requests.log | python clean_requests.py | oxstash

clean_requests.py can be written to work over stdin or by connecting to a oxd instance by using tools provided in blueox.client

Development

Using the magic of Make, virtualenv and pip, setting up your development environment is a snap:

make dev

This will create a virtualenv in env directory. Running the tests is just a simple:

make test

Or if you are running individual tests, use testify directly:

testify -v tests

TODO List

  • Failure of the central collector is only recoverable if the oxd instance comes back on the same ip address. It would be nice to be able to live reconfigure through oxctl to point to a backup collector.
  • Debian packaging would probably be convinient.
  • Need more Real World data on what becomes a bottleneck first: CPU or Network. Adding options for compression would be pretty easy.
  • More examples of what to do with the data would make this project more compelling visually.