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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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Merely setting the "action" tag will only result in the transaction
itself containing a value for this tag. To ensure other metrics also
contain this tag we must set the action using Transaction#action=
instead.
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One use case for this is manually setting the "action" tag for Grape API
calls. Due to Grape running blocks there are no human readable method
names that can be used for the "action" tag, thus we have to set these
manually on a case by case basis.
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If the measure method uses Transaction.current directly the SQL
subscriber (Subscribers::ActiveRecord) will add timings of queries
triggered by DB cleaner.
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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).
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This allows measuring of timings of arbitrary Ruby blocks, this allows
for more fine grained performance monitoring. Custom values and tags can
also be attached to a block.
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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 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 ensures we don't need to load anything from either PostgreSQL or
the Rails cache whenever creating new InfluxDB connections.
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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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This ensures we can still boot, even when the "application_settings"
table doesn't exist.
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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.
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