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This reverts commit cb10b725c8929b8b4460f89c9d96c773af39ba6b.
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`endpoint.route` is calling `env[Grape::Env::GRAPE_ROUTING_ARGS][:route_info]`
but `env[Grape::Env::GRAPE_ROUTING_ARGS]` is `nil` in the case of a 405 response
Signed-off-by: Rémy Coutable <remy@rymai.me>
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- Use Route#request_method instead of Route#route_method
- Use Route#path instead of Route#route_path
Signed-off-by: Rémy Coutable <remy@rymai.me>
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GitLab Performance Monitoring is now able to track custom events not
directly related to application performance. These events include the
number of tags pushed, repositories created, builds registered, etc.
The use of these events is to get a better overview of how a GitLab
instance is used and how that may affect performance. For example, a
large number of Git pushes may have a negative impact on the underlying
storage engine.
Events are stored in the "events" measurement and are not prefixed with
"rails_" or "sidekiq_", this makes it easier to query events with the
same name triggered from different parts of the application. All events
being stored in the same measurement also makes it easier to downsample
data.
Currently the following events are tracked:
* Creating repositories
* Removing repositories
* Changing the default branch of a repository
* Pushing a new tag
* Removing an existing tag
* Pushing a commit (along with the branch being pushed to)
* Pushing a new branch
* Removing an existing branch
* Importing a repository (along with the URL we're importing)
* Forking a repository (along with the source/target path)
* CI builds registered (and when no build could be found)
* CI builds being updated
* Rails and Sidekiq exceptions
Fixes gitlab-org/gitlab-ce#13720
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This reduces the overhead of the method instrumentation code primarily
by reducing the number of method calls. There are also some other small
optimisations such as not casting timing values to Floats (there's no
particular need for this), using Symbols for method call metric names,
and reducing the number of Hash lookups for instrumented methods.
The exact impact depends on the code being executed. For example, for a
method that's only called once the difference won't be very noticeable.
However, for methods that are called many times the difference can be
more significant.
For example, the loading time of a large commit
(nrclark/dummy_project@81ebdea5df2fb42e59257cb3eaad671a5c53ca36)
was reduced from around 19 seconds to around 15 seconds using these
changes.
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info.
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Process.clock_gettime allows getting the real time in nanoseconds as
well as allowing one to get a monotonic timestamp. This offers greater
accuracy without the overhead of having to allocate a Time instance. In
general using Time.now/Time.new is about 2x slower than using
Process.clock_gettime(). For example:
require 'benchmark/ips'
Benchmark.ips do |bench|
bench.report 'Time.now' do
Time.now.to_f
end
bench.report 'clock_gettime' do
Process.clock_gettime(Process::CLOCK_MONOTONIC, :millisecond)
end
bench.compare!
end
Running this benchmark gives:
Calculating -------------------------------------
Time.now 108.052k i/100ms
clock_gettime 125.984k i/100ms
-------------------------------------------------
Time.now 2.343M (± 7.1%) i/s - 11.670M
clock_gettime 4.979M (± 0.8%) i/s - 24.945M
Comparison:
clock_gettime: 4979393.8 i/s
Time.now: 2342986.8 i/s - 2.13x slower
Another benefit of using Process.clock_gettime() is that we can simplify
the code a bit since it can give timestamps in nanoseconds out of the
box.
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Previously we'd create a separate Metric instance for every method call
that would exceed the method call threshold. This is problematic because
it doesn't provide us with information to accurately get the _total_
execution time of a particular method. For example, if the method
"Foo#bar" was called 4 times with a runtime of ~10 milliseconds we'd end
up with 4 different Metric instances. If we were to then get the
average/95th percentile/etc of the timings this would be roughly 10
milliseconds. However, the _actual_ total time spent in this method
would be around 40 milliseconds.
To solve this problem we now create a single Metric instance per method.
This Metric instance contains the _total_ real/CPU time and the call
count for every instrumented method.
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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.
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Instrument Grape API endpoints
See merge request !4587
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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
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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
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Also removes the note from the development/testing.md guide
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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.
Fixes gitlab-org/gitlab-ce#17239
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Fixes gitlab-org/gitlab-ce#15335
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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).
Fixes gitlab-org/gitlab-ce#15281
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This allows us to track how much time of a transaction is spent in
dealing with cached data.
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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.
Fixes gitlab-org/gitlab-ce#12450
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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.
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See merge request !2392
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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.
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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.
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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.
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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.
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While useful for finding out what methods/views belong to a transaction
this might result in too much data being stored in InfluxDB.
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This reverts commit 7549102bb727daecc51da84af39956b32fc41537.
Apparently I was wrong about
ActiveSupport::Notifications::Event#duration returning the duration in
seconds, instead it returns it in milliseconds already.
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Transaction timings are also already stored in milliseconds, this keeps
things consistent.
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This ensures Rails and Sidekiq transactions are split into the series
"rails_transactions" and "sidekiq_transactions" respectively.
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This removes the need for any tags to differentiate between Sidekiq and
Rails statistics while still being able to separate the two.
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This makes it easier to see where time is spent without having to
aggregate all the individual points in the method_calls series.
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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.
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This isn't hugely useful and mostly wastes InfluxDB space. We can re-add
this whenever needed (but only once we really need it).
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This removes the need for tagging all metrics with a "process_type" tag.
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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.
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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.
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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.
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Newlines aren't really needed and they may mess with InfluxDB's line
protocol.
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