• Using Correlation IDs to investigate distributed requests
  • Developer guidelines for working with correlation IDs
• Enabling distributed tracing
• Using Jaeger in the GitLab Development Kit
• Using Jaeger without the GitLab Developer Kit
  • 1. Start Jaeger
    • Using Docker
    • Using the Jaeger process
  • 2. Configure the GITLAB_TRACING environment variable
  • 3. Start the GitLab application
  • 4. Open the Jaeger Search UI

Distributed tracing development guidelines

GitLab is instrumented for distributed tracing. Distributed tracing in GitLab is currently considered experimental, as it has not yet been tested at scale on GitLab.com.

According to Open Tracing:

Distributed tracing, also called distributed request tracing, is a method used to profile and monitor applications, especially those built using a microservices architecture. Distributed tracing helps to pinpoint where failures occur and what causes poor performance.

Distributed tracing is especially helpful in understanding the lifecycle of a request as it passes through the different components of the GitLab application. At present, Workhorse, Rails, Sidekiq, and Gitaly support tracing instrumentation.

Distributed tracing adds minimal overhead when disabled, but imposes only small overhead when enabled and is therefore capable in any environment, including production. For this reason, it can be useful in diagnosing production issues, particularly performance problems.

Services have different levels of support for distributed tracing. Custom instrumentation code must be added to the application layer in addition to pre-built instrumentation for the most common libraries.

For service-specific information, see:

• Using Jaeger for Gitaly local development

Using Correlation IDs to investigate distributed requests

The GitLab application passes correlation IDs between the various components in a request. A correlation ID is a token, unique to a single request, used to correlate a single request between different GitLab subsystems (for example, Rails, Workhorse). Since correlation IDs are included in log output, Engineers can use the correlation ID to correlate logs from different subsystems and better understand the end-to-end path of a request through the system. When a request traverses process boundaries, the correlation ID is injected into the outgoing request. This enables the propagation of the correlation ID to each downstream subsystem.

Correlation IDs are usually generated in the Rails application in response to certain web requests. Some user facing systems don’t generate correlation IDs in response to user requests (for example, Git pushes over SSH).

Developer guidelines for working with correlation IDs

When integrating tracing into a new system, developers should avoid making certain assumptions about correlation IDs. The following guidelines apply to all subsystems at GitLab:

• Correlation IDs are always optional.
  • Never have non-tracing features depend on the existence of a correlation ID from an upstream system.
• Correlation IDs are always free text.
  • Correlation IDs should never be used to pass context (for example, a username or an IP address).
  • Correlation IDs should never be parsed, or manipulated in other ways (for example, split).

The LabKit library provides a standardized interface for working with GitLab correlation IDs in the Go programming language. LabKit can be used as a reference implementation for developers working with tracing and correlation IDs on non-Go GitLab subsystems.

Enabling distributed tracing

GitLab uses the GITLAB_TRACING environment variable to configure distributed tracing. The same configuration is used for all components (for example, Workhorse, Rails, etc).

When GITLAB_TRACING is not set, the application isn’t instrumented, meaning that there is no overhead at all.

To enable GITLAB_TRACING, a valid “configuration-string” value should be set, with a URL-like form:

GITLAB_TRACING=opentracing://<driver>?<param_name>=<param_value>&<param_name_2>=<param_value_2>

In this example, we have the following hypothetical values:

• driver: the driver such a Jaeger.
• param_name, param_value: these are driver specific configuration values. Configuration parameters for Jaeger are documented further on in this document they should be URL encoded. Multiple values should be separated by & characters like a URL.

GitLab Rails provides pre-implemented instrumentations for common types of operations that offer a detailed view of the requests. However, the detailed information comes at a cost. The resulting traces are long and can be difficult to process, making it hard to identify bigger underlying issues. To address this concern, some instrumentations are disabled by default. To enable those disabled instrumentations, set the following environment variables:

• GITLAB_TRACING_TRACK_CACHES: enable tracking cache operations, such as cache read, write, or delete.
• GITLAB_TRACING_TRACK_REDIS: enable tracking Redis operations. Most Redis operations are for caching, though.

Using Jaeger in the GitLab Development Kit

The first tracing implementation that GitLab supports is Jaeger, and the GitLab Development Kit supports distributed tracing with Jaeger out-of-the-box. GDK automatically adds GITLAB_TRACING environment variables to add services.

Configure GDK for Jaeger by editing the gdk.yml file and adding the following settings:

tracer:
  build_tags: tracer_static tracer_static_jaeger
  jaeger:
    enabled: true
    listen_address: 127.0.0.1
    version: 1.43.0

After modifying the gdk.yml file, reconfigure your GDK by running the gdk reconfigure command. This ensures that your GDK is properly configured and ready to use.

The above configuration sets the tracer_static and tracer_static_jaeger build tags when rebuilding services written in Go for the first time. Any changes made afterward require rebuilding them with those build tags. You can either:

• Add those build tags to the default set of build tags.
• Manually attach them to the build command. For example, Gitaly supports adding build tag out of the box. You can run make all WITH_BUNDLED_GIT=YesPlease BUILD_TAGS="tracer_static tracer_static_jaeger".

After reconfiguration, Jaeger dashboard is available at http://localhost:16686. Another way to access tracing from a GDK environment is through the performance-bar. This can be shown by typing p b in the browser window.

Once the performance bar is enabled, select Trace in the performance bar to go to the Jaeger UI.

The Jaeger search UI returns a query for the Correlation-ID of the current request. This search should return a single trace result. Selecting this result shows the detail of the trace in a hierarchical time-line.

Using Jaeger without the GitLab Developer Kit

Distributed Tracing can be enabled in non-GDK development environments as well as production or staging environments, for troubleshooting. At this time, this functionality is experimental, and not supported in production environments at present. In this first release, it is intended to be used for debugging in development environments only.

Jaeger tracing can be enabled through a three-step process:

1. Start Jaeger.
2. Configure the GITLAB_TRACING environment variable.
3. Start the GitLab application.
4. Go to the Jaeger Search UI in your browser.

1. Start Jaeger

Jaeger has many configuration options, but is very easy to start in an “all-in-one” mode which uses memory for trace storage (and is therefore non-persistent). The main advantage of “all-in-one” mode being ease of use.

For more detailed configuration options, refer to the Jaeger documentation.

Using Docker

If you have Docker available, the easier approach to running the Jaeger all-in-one is through Docker, using the following command:

$ docker run \
  --rm \
  -e COLLECTOR_ZIPKIN_HTTP_PORT=9411  \
  -p 5775:5775/udp \
  -p 6831:6831/udp \
  -p 6832:6832/udp \
  -p 5778:5778 \
  -p 16686:16686 \
  -p 14268:14268 \
  -p 9411:9411 \
  jaegertracing/all-in-one:latest

Using the Jaeger process

Without Docker, the all-in-one process is still easy to set up.

1. Download the latest Jaeger release for your platform.
2. Extract the archive and run the bin/all-in-one process.

This should start the process with the default listening ports.

2. Configure the GITLAB_TRACING environment variable

After you have Jaeger running, configure the GITLAB_TRACING variable with the appropriate configuration string.

If you’re running everything on the same host, use the following value:

export GITLAB_TRACING="opentracing://jaeger?http_endpoint=http%3A%2F%2Flocalhost%3A14268%2Fapi%2Ftraces&sampler=const&sampler_param=1"

This configuration string uses the Jaeger driver opentracing://jaeger with the following options:

Other parameter values are also possible:

3. Start the GitLab application

After the GITLAB_TRACING environment variable is exported to all GitLab services, start the application.

When GITLAB_TRACING is configured properly, the application logs this on startup:

13:41:53 gitlab-workhorse.1      | 2019/02/12 13:41:53 Tracing enabled
...
13:41:54 gitaly.1                | 2019/02/12 13:41:54 Tracing enabled
...

If GITLAB_TRACING is not configured correctly, this issue is logged:

13:43:45 gitaly.1                | 2019/02/12 13:43:45 skipping tracing configuration step: tracer: unable to load driver mytracer

By default, GitLab ships with the Jaeger tracer, but other tracers can be included at compile time. Details of how this can be done are included in the LabKit tracing documentation.

If no log messages about tracing are emitted, the GITLAB_TRACING environment variable is likely not set.

4. Open the Jaeger Search UI

By default, the Jaeger search UI is available at http://localhost:16686/search.