Track method call times/counts as a single metric
This changes method call tracking so only a single metric is emitted regardless of the number of calls. This allows us to more accurately measure the total execution time of a method as well as the number of times a method is called. See 851e3ff7578973c2206628424eac3b951a3c656d for more details.
Method call tracking tracked calls individually meaning the end statistics may not always be accurate enough to get a good understanding of where time is spent.
See merge request !4754
We can't do a lot with classes without names as we can't filter by them,
have no idea where they come from, etc. As such it's best to just ignore
these.
By default instrumentation will instrument public,
protected and private methods, because usually
heavy work is done on private method or at least
that’s what facts is showing
Generating the following tags
Grape#GET /projects/:id/archive
from Grape::Route objects like
{ :path => /:version/projects/:id/archive(.:format)
:version => “v3”,
:method => “GET” }
Use an instance variable to cache raw_path transformations.
This variable is only going to growth to the number of
endpoints of the API, not with exact different requests
We can store this cache as an instance variable because
middleware are initialised only once
Because method call timings are inclusive (that is, they include the
time of any sub method calls) this would lead to the total method
execution time often being far greater than the total transaction time.
Because this is incredibly confusing it's best to simply _not_ track the
total method execution time, after all it's not that useful to begin
with.
Fixesgitlab-org/gitlab-ce#17239
By using Module#prepend we can define a Module containing all proxy
methods. This removes the need for setting up crazy method alias chains
and in turn prevents us from having to deal with all that madness (e.g.
methods calling each other recursively).
Fixesgitlab-org/gitlab-ce#15281
This makes it easier to query, simplifies the code, and makes it
possible to figure out what transaction the data belongs to (simply
because it's now stored _in_ the transaction).
This new setup keeps track of both the real/wall time _and_ CPU time
spent in a block, both measured using milliseconds (to keep all units
the same).
This changes the timestamp of metrics to be more accurate/unique by
using Time#to_f combined with a small random jitter value. This
combination hopefully reduces the amount of collisions, though there's
no way to fully prevent any from occurring.
Fixesgitlab-com/operations#175
This ensures that an instrumented method that doesn't take arguments
reports an arity of 0, instead of -1.
If Ruby had a proper method for finding out the required arguments of a
method (e.g. Method#required_arguments) this would not have been an
issue. Sadly the only two methods we have are Method#parameters and
Method#arity, and both are equally painful to use.
Fixesgitlab-org/gitlab-ce#12450
Sampling data at a fixed interval means we can potentially miss data
from events occurring between sampling intervals. For example, say we
sample data every 15 seconds but Unicorn workers get killed after 10
seconds. In this particular case it's possible to miss interesting data
as the sampler will never get to actually submitting data.
To work around this (at least for the most part) the sampling interval
is randomized as following:
1. Take the user specified sampling interval (15 seconds by default)
2. Divide it by 2 (referred to as "half" below)
3. Generate a range (using a step of 0.1) from -"half" to "half"
4. Every time the sampler goes to sleep we'll grab the user provided
interval and add a randomly chosen "adjustment" to it while making
sure we don't pick the same value twice in a row.
For a specified timeout of 15 this means the actual intervals can be
anywhere between 7.5 and 22.5, but never can the same interval be used
twice in a row.
The rationale behind this change is that on dev.gitlab.org I'm sometimes
seeing certain Gitlab::Git/Rugged objects being retained, but only for a
few minutes every 24 hours. Knowing the code of Gitlab and how much
memory it uses/leaks I suspect we're missing data due to workers getting
terminated before the sampler can write its data to InfluxDB.
Where a vew is called from doesn't matter as much. We already know what
action they belong to and this is more than enough information. By
removing the file/line number from the list of tags we should also be
able to reduce the number of series stored in InfluxDB.
This gives a very rough estimate of how much memory is allocated during
a transaction. This only works reliably when using a single-threaded
application server and a Ruby implementation with a GIL as otherwise
memory allocated by other threads might skew the statistics. Sadly
there's no way around this as Ruby doesn't provide a reliable way of
gathering accurate object sizes upon allocation on a per-thread basis.
Without this it's impossible to find out what methods/views/queries are
executed by a certain controller or Sidekiq worker. While this will
increase the total number of series it should stay within reasonable
limits due to the amount of "actions" being small enough.
Since filtering by these values is very rare (they're mostly just
displayed as-is) we don't need to waste any index space by saving them
as tags. By storing them as values we also greatly reduce the number of
series in InfluxDB.
This reverts commit 7549102bb7.
Apparently I was wrong about
ActiveSupport::Notifications::Event#duration returning the duration in
seconds, instead it returns it in milliseconds already.
This will be used to store/increment the total query/view rendering
timings on a per transaction basis. This in turn can greatly reduce the
amount of metrics stored.
This particular setup had 3 problems:
1. Storing SQL queries as tags is very inefficient as InfluxDB ends up
indexing every query (and they can get pretty large). Storing these
as values instead means we can't always display the SQL as easily.
2. We already instrument ActiveRecord query methods, thus we already
have timing information about database queries.
3. SQL obfuscation is difficult to get right and I'd rather not expose
sensitive data by accident.
While it's useful to keep track of the different versions (Ruby, GitLab,
etc) doing so for every point wastes disk space and possibly also RAM
(which InfluxDB is all to eager to gobble up). If we want to see the
performance differences between different GitLab versions simply looking
at the performance since the last release date should suffice.
This removes the need for Sidekiq and any overhead/problems introduced
by TCP. There are a few things to take into account:
1. When writing data to InfluxDB you may still get an error if the
server becomes unavailable during the write. Because of this we're
catching all exceptions and just ignore them (for now).
2. Writing via UDP apparently requires the timestamp to be in
nanoseconds. Without this data either isn't written properly.
3. Due to the restrictions on UDP buffer sizes we're writing metrics one
by one, instead of writing all of them at once.
This ensures we don't end up wasting resources by tracking method calls
that only take a few microseconds. By default the threshold is 10
milliseconds but this can be changed using the gitlab.yml configuration
file.
InfluxDB escapes double quotes upon output which makes it a pain to deal
with. This ensures that if we're using PostgreSQL we don't store any
queries containing double quotes in InfluxDB, solving the escaping
problem.
When using instrument_methods/instrument_instance_methods we only want
to instrument methods defined directly in a class, not those included
via mixins (e.g. whatever RSpec throws in during development).
In case an externally included method _has_ to be instrumented we can
still use the regular instrument_method/instrument_instance_method
methods.
The methods Instrumentation.instrument_methods and
Instrumentation.instrument_instance_methods can be used to instrument
all methods of a module at once.
The use of ActiveSupport would slow down instrumented method calls by
about 180x due to:
1. ActiveSupport itself not being the fastest thing on the planet
2. caller_locations() having quite some overhead
The use of caller_locations() has been removed because it's not _that_
useful since we already know the full namespace of receivers and the
names of the called methods.
The use of ActiveSupport has been replaced with some custom code that's
generated using eval() (which can be quite a bit faster than using
define_method).
This new setup results in instrumented methods only being about 35-40x
slower (compared to non instrumented methods).
Robert SpeicherandRobert Speicher
Yorick PeterseandRobert Speicher
Paco Guzman
Pablo Carranza