Add extension point to record execution times in a performance log

Add a new extension point that is invoked for all operations for which
the execution time is measured. The invocation of the extension point
does not happen immediately, but only at the end of a request (REST
call, SSH call, git push). Implementors can write the execution times
into a performance log for further analysis.

In Gerrit there are 2 possibilities to measure and record the execution
time of an operation:

1. TraceTimer:
   Opens an autocloseable context to execute an operation. On close the
   execution time is written to the server logs, but only if the request
   is traced (or if log level was set to fine).
2. Timer Metrics:
   Record execution times as a metric.
   In addition this writes the execution time to the server logs, but
   only if the request is traced (or if log level was set to fine).

These are the 2 places where performance log entries must be captured.

Performance log entries are stored in the LoggingContext which is based
on ThreadLocals. LoggingContextAwareRunnable and
LoggingContextAwareCallable which are used by all executors ensure that
captured performance log entries are properly copied between threads.

At the end of a request (supported are REST call, SSH call and git push)
the captured performance log entries are handed over to the
PerformanceLogger implementations.

If no PerformanceLogger is registered, or if execution times of
operations outside of request scope are measured, performance log
entries are not captured because nobody would consume them.

Storing the performance log records in the LoggingContext and invoking
the PerformanceLogger plugins only at the end of a request has some
advantages and disadvantages:

1. [advantage] Users of TraceTimer can continue to use the static
   methods calls to create a TraceTimer (TraceContext.newTimer(...)). To
   invoke the plugins immediately we would need to get them injected
   into TraceTimer, hence callers would need a factory to create a
   TraceTimer. That would result in quite some boilerplate code and in
   addition some places that use TraceTimer (in VersionedMetaData)
   cannot use injection.
2. [advantage] The metric system is setup very early in the injector
   chain (in the DB injector, see SiteProgram#createDbInjector(boolean)).
   To invoke the plugins directly from the timer metrics we would need
   to have the PerformanceLogger plugins already available on this
   injector level, which is difficult.
3. [disadvantage] The captured performance log records are kept in
   memory while a request is processed. This leads to higher memory
   foodprint, but we think this is OK.

To keep the performance and memory overhead for recording performance as
low as possible we did some optimizations:

1. Performance log entries are only created if there is a consumer (at
   least one PerformanceLogger plugin + time measured inside request
   context)
2. Performance log entries avoid the instantiation of a Map to record
   meta data (instead we have dedicated fields for meta data keys and
   values).

For the timer metrics we use generic names for the meta data keys
("field1", "field2", "field3"). This is because the actual field names
are not available at this place. We may make them available, but that's
outside the scope of this change and may be done in a follow-up change.

To be able to write stable acceptance tests that verify that the
PerformanceLogger plugins are invoked, it is important that the server
calls the plugins before the response is sent back to the client. This
is why the scope of the PerformanceLogContext in RestApiServlet is a
little smaller than the scope of the TraceContext.

Change-Id: I699db01609a1b4a88cee8959bdd9f1dfbb8dc74e
Signed-off-by: Edwin Kempin <ekempin@google.com>
25 files changed
tree: 3224f3e3ee756892fb09b88ae687499008f4328e
  1. .settings/
  2. antlr3/
  3. contrib/
  4. Documentation/
  5. java/
  6. javatests/
  7. lib/
  8. plugins/
  9. polygerrit-ui/
  10. prolog/
  11. prologtests/
  12. proto/
  13. resources/
  14. tools/
  15. webapp/
  16. .bazelproject
  17. .bazelrc
  18. .bazelversion
  19. .editorconfig
  20. .git-blame-ignore-revs
  21. .gitignore
  22. .gitmodules
  23. .mailmap
  24. .pydevproject
  25. BUILD
  26. COPYING
  27. INSTALL
  28. package.json
  29. README.md
  30. SUBMITTING_PATCHES
  31. version.bzl
  32. WORKSPACE
README.md

Gerrit Code Review

Gerrit is a code review and project management tool for Git based projects.

Build Status

Objective

Gerrit makes reviews easier by showing changes in a side-by-side display, and allowing inline comments to be added by any reviewer.

Gerrit simplifies Git based project maintainership by permitting any authorized user to submit changes to the master Git repository, rather than requiring all approved changes to be merged in by hand by the project maintainer.

Documentation

For information about how to install and use Gerrit, refer to the documentation.

Source

Our canonical Git repository is located on googlesource.com. There is a mirror of the repository on Github.

Reporting bugs

Please report bugs on the issue tracker.

Contribute

Gerrit is the work of hundreds of contributors. We appreciate your help!

Please read the contribution guidelines.

Note that we do not accept Pull Requests via the Github mirror.

Getting in contact

The IRC channel on freenode is #gerrit. An archive is available at: echelog.com.

The Developer Mailing list is repo-discuss on Google Groups.

License

Gerrit is provided under the Apache License 2.0.

Build

Install Bazel and run the following:

    git clone --recurse-submodules https://gerrit.googlesource.com/gerrit
    cd gerrit && bazel build release

Install binary packages (Deb/Rpm)

The instruction how to configure GerritForge/BinTray repositories is here

On Debian/Ubuntu run:

    apt-get update & apt-get install gerrit=<version>-<release>

NOTE: release is a counter that starts with 1 and indicates the number of packages that have been released with the same version of the software.

On CentOS/RedHat run:

    yum clean all && yum install gerrit-<version>[-<release>]

On Fedora run:

    dnf clean all && dnf install gerrit-<version>[-<release>]

Use pre-built Gerrit images on Docker

Docker images of Gerrit are available on DockerHub

To run a CentOS 7 based Gerrit image:

    docker run -p 8080:8080 gerritforge/gerrit-centos7[:version]

To run a Ubuntu 15.04 based Gerrit image:

    docker run -p 8080:8080 gerritforge/gerrit-ubuntu15.04[:version]

NOTE: release is optional. Last released package of the version is installed if the release number is omitted.