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.
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.
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 adds the ability to write application metrics (e.g. SQL timings) to
InfluxDB. These metrics can in turn be visualized using Grafana, or
really anything else that can read from InfluxDB. These metrics can be
used to track application performance over time, between different Ruby
versions, different GitLab versions, etc.
== Transaction Metrics
Currently the following is tracked on a per transaction basis (a
transaction is a Rails request or a single Sidekiq job):
* Timings per query along with the raw (obfuscated) SQL and information
about what file the query originated from.
* Timings per view along with the path of the view and information about
what file triggered the rendering process.
* The duration of a request itself along with the controller/worker
class and method name.
* The duration of any instrumented method calls (more below).
== Sampled Metrics
Certain metrics can't be directly associated with a transaction. For
example, a process' total memory usage is unrelated to any running
transactions. While a transaction can result in the memory usage going
up there's no accurate way to determine what transaction is to blame,
this becomes especially problematic in multi-threaded environments.
To solve this problem there's a separate thread that takes samples at a
fixed interval. This thread (using the class Gitlab::Metrics::Sampler)
currently tracks the following:
* The process' total memory usage.
* The number of file descriptors opened by the process.
* The amount of Ruby objects (using ObjectSpace.count_objects).
* GC statistics such as timings, heap slots, etc.
The default/current interval is 15 seconds, any smaller interval might
put too much pressure on InfluxDB (especially when running dozens of
processes).
== Method Instrumentation
While currently not yet used methods can be instrumented to track how
long they take to run. Unlike the likes of New Relic this doesn't
require modifying the source code (e.g. including modules), it all
happens from the outside. For example, to track `User.by_login` we'd add
the following code somewhere in an initializer:
Gitlab::Metrics::Instrumentation.
instrument_method(User, :by_login)
to instead instrument an instance method:
Gitlab::Metrics::Instrumentation.
instrument_instance_method(User, :save)
Instrumentation for either all public model methods or a few crucial
ones will be added in the near future, I simply haven't gotten to doing
so just yet.
== Configuration
By default metrics are disabled. This means users don't have to bother
setting anything up if they don't want to. Metrics can be enabled by
editing one's gitlab.yml configuration file (see
config/gitlab.yml.example for example settings).
== Writing Data To InfluxDB
Because InfluxDB is still a fairly young product I expect the worse.
Data loss, unexpected reboots, the database not responding, you name it.
Because of this data is _not_ written to InfluxDB directly, instead it's
queued and processed by Sidekiq. This ensures that users won't notice
anything when InfluxDB is giving trouble.
The metrics worker can be started in a standalone manner as following:
bundle exec sidekiq -q metrics
The corresponding class is called MetricsWorker.
