We’re rolling out Graphite and statsd at work, and I’ve spend some time debugging our setup. Most of the time, the only thing I need is
tcpdump to verify that a host is sending correctly the various metrics.
But today, thanks to a stupid reason, I’ve learned about another way to debug carbon: the manhole. The idea of the manhole is to give you a access to a REPL attached to the live process. When my boss told me about it, I was at first surprised to see this in a Python application. I’ve already been exposed to this kind of debugging thanks to Clojure, where it’s not uncommon to connect a REPL to your live application (for example, Heroku document how to connect to a remote live REPL in your application). When I first heard of that I was very skeptical (give access to a live environment, and let the developer mess with the process ?!). But I’ve learned to love it and I feel naked when I’m working in an environment where this is not available. So I was happy to jump and take a look at that feature.
Since it’s not very well documented and I had a hard time finding some information, let me share here the basics.
First you’ll need to configure Carbon’s to allow the connection:
ENABLE_MANHOLE = True # by default it's set to False MANHOLE_INTERFACE = 127.0.0.1 MANHOLE_PORT = 7222 MANHOLE_USER = admin MANHOLE_PUBLIC_KEY = <your public SSH key, the string, not the path to the key>
Now you can restart carbon, and connect to the Python shell with
ssh firstname.lastname@example.org -p7222. This manhole is useful to get an idea of the data structure your process is handling, or to get an idea of what’s going on (is there a lot of keys being held in memory? Is the queue size for one metric huge? etc).
From here, you can execute Python code to examine the data of the process:
>>> from carbon.cache import MetricCache >>> print MetricCache['PROD.apps.xxx.yyy.zzz] [(1357861603.0, 93800.0), (1357861613.0, 98200.0), (1357861623.0, 91900.0)]
MetricCache class is a Python dictionary where you can access your keys. You can also list all the metrics with the size of their queue with
Or even force the daemon to write to disk all the data points:
>>> from carbon.writer import writeCachedDataPoints >>> writeCachedDataPoints()
Before doing any of that, I would recommend to read the code of carbon. It’s pretty short and quiet straight forward, especially the code of the writer.
Of course, you have to know what you’re doing when you’re executing code from a REPL in a live environment.