Package: graphite-metrics
graphite-metrics: metric collectors for various stuff not (or poorly) handled by other monitoring daemonsCore of the project is a simple daemon (harvestd), which collects metric
values and sends them to graphite carbon daemon (and/or other configured
destinations) once per interval.Includes separate data collection components (“collectors”) for
processing of:/proc/slabinfo for useful-to-watch values, not everything
(configurable)./proc/vmstat and /proc/meminfo in a consistent way./proc/stat for irq, softirq, forks./proc/buddyinfo and /proc/pagetypeinfo (memory fragmentation)./proc/interrupts and /proc/softirqs.Cron log to produce start/finish events and duration for each job
into a separate metrics, adapts jobs to metric names with regexes.Per-system-service accounting usingsystemdand
it’s cgroups (“Default…Accounting=” options in system.conf have to
be enabled for more recent versions).sysstatdata from
sadc logs (use something likesadc-F-L-SDISK-SXDISK-SPOWER 60to have more stuff logged
there) via sadf binary and it’s json export (sadf-j, supported
since sysstat-10.0.something, iirc).iptables rule “hits” packet and byte counters, taken from
ip{,6}tables-save, mapped via separate “table chain_name rule_no
metric_name” file, which should be generated along with firewall
rules (I usethis scriptto
do that).Additional metric collectors can be added via setuptools/distribute
graphite_metrics.collectorsentry
pointand confgured via the common configuration mechanism.Same for the datapoint sinks (destinations - it doesn’t have to be a
single carbon host), datapoint processors (mangle/rename/filter
datapoints) and the main loop, which can be replaced with the async
(simple case - threads or gevent) or buffering loop.Currently supported backends (data destinations, sinks):graphite carbon
daemon(enabled/used by default)librato metricsLook at the shipped collectors, processors, sinks and loops and their
base classes (likegraphite_metrics.sinks.Sinkorloops.Basic)
for API examples.InstallationIt’s a regular package for Python 2.7 (not 3.X).Usingpipis the best way:% pip install graphite-metricsIf you don’t have it, use:% easy_install pip
% pip install graphite-metricsAlternatively (see
also):% curl https://raw.github.com/pypa/pip/master/contrib/get-pip.py | python
% pip install graphite-metricsOr, if you absolutely must:% easy_install graphite-metricsBut, you really shouldn’t do that.Current-git version can be installed like this:% pip install 'git+https://github.com/mk-fg/graphite-metrics.git#egg=graphite-metrics'RequirementsBasic requirements are (pip or easy_install should handle these for
you):setuptools /
distribute(for entry
points)layered-yaml-attrdict-configSome shipped modules require additional packages to function (which can
be installed automatically by specifying extras on install, example:pip install'graphite-metrics[collectors.cgacct]'):collectorscgacctdbus-pythoncron_logxattr(unless
–xattr-emulation is used)iso8601sysstatxattr(unless
–xattr-emulation is used)(optional)simplejson- for
better performance than stdlib json modulesinkslibrato_metricsrequests(optional)simplejson- for
better performance than stdlib json module(optional)gevent-
to enable constant-time (more scalable) async submissions of
large data chunks via concurrent API requestsAlso seerequirements.txtfile or “install_requires” and “extras_require” insetup.py.RunningFirst run should probably look like this:% harvestd --debug -s dump -i10That will use default configuration with all the collectors enabled,
dumping data to stderr (only “dump” data-sink enabled) and using short
(5s) interval between collected datapoints, dumpng additional info about
what’s being done.After that, seedefault harvestd.yaml configuration
file,
which contains configuration for all loaded collectors and can/should be
overidden using -c option.Note that you don’t have to specify all the options in each
override-config, just the ones you need to update.For example, simple configuration file (say, /etc/harvestd.yaml) just to
specify carbon host and log lines format (dropping timestamp, since it
will be piped to syslog or systemd-journal anyway) might look like this:sinks:
  carbon_socket:
    host: carbon.example.host

logging:
  formatters:
    basic:
      format: '%(levelname)s :: %(name)s: %(message)s'And be started like this:harvestd-c/etc/harvestd.yamlSeeharvestd--helpoutput for a full CLI reference.Caveats, Stern Warnings and Apocalyptic PropheciesWhile most stock collectors here pull metrics from /proc once per some
interval, same as the other tools, be especially wary of the ones that
process memory metrics, like /proc/slabinfo and cgroup value parsers.So-called “files” in /proc are actually callbacks in the kernel code,
and to get consistent reading for the whole slabinfo table, (at least
some versions) of the kernel have to lock some operations, causing
unexpected lags and delays on the whole system under some workloads
(e.g. memcache servers).cgroup data collector processes lots of files, potentially dozens,
hundreds or even thoursands per collection cycle, which may also cause
similar issues.Special thanks to Marcus Barczak for pointing that out.RationaleMost other tools can (in theory) collect this data, and I’ve usedcollectdfor most of these, but it:Doesn’t provide some of the most useful stuff - nfs stats, disk
utilization time percentage, etc.Fails to collect some other stats, producing strange values like
0’es, unrealistic or negative values (for io, network, sensors, …).General-purpose plugins like “tail” add lot of complexity, making
configuration into a mess, while still lacking some basic
functionality which 10 lines of code (plugin) can easily provide
(support is there, but see below).Plugins change metric names from the ones provided by /proc,
referenced in kernel Documentation and on the internets, making
collected data unnecessary hard to interpret and raising questions
about it’s meaning (which is increasingly important for low-level and
calculated metrics).Initially I’ve tried to address these issues (implement the same
collectors) with collectd plugins, but it’s python plugin system turned
out to be leaking RAM and collectd itself segfaults something like
once-a-day, even in the latest releases, although probably because of
issues in C plugins.Plus, collectd data requires post-processing anyway - proper metric
namespaces, counter handling, etc.Given that the alternative is to just get the data and echo it as “name
val timestamp” to tcp socket, decided to avoid the extra complexity and
problems that collectd provides.Other than collectd, I’ve experimented withganglia,munin, and some other monitoring
infrastructures, but found little justification in re-using their
aggregation and/or collection infrastructure, if not outright
limitations (like static data schema in ganglia).Daemon binary is (weirdly) called “harvestd” because “metricsd” name is
already used to refer toanother related
daemon(also,there’s a
“metrics” w/o “d”, probably
others), and is too generic to be used w/o extra confusion, I think.
That, and I seem to lack creativity to come up with a saner name
(“reaperd” sounds too MassEffect’ish these days).