--- stage: Monitor group: Monitor info: To determine the technical writer assigned to the Stage/Group associated with this page, see https://about.gitlab.com/handbook/engineering/ux/technical-writing/#assignments --- # GitLab Developers Guide to Logging **(FREE)** [GitLab Logs](../administration/logs.md) play a critical role for both administrators and GitLab team members to diagnose problems in the field. ## Don't use `Rails.logger` Currently `Rails.logger` calls all get saved into `production.log`, which contains a mix of Rails' logs and other calls developers have inserted in the codebase. For example: ```plaintext Started GET "/gitlabhq/yaml_db/tree/master" for 168.111.56.1 at 2015-02-12 19:34:53 +0200 Processing by Projects::TreeController#show as HTML Parameters: {"project_id"=>"gitlabhq/yaml_db", "id"=>"master"} ... Namespaces"."created_at" DESC, "namespaces"."id" DESC LIMIT 1 [["id", 26]] CACHE (0.0ms) SELECT "members".* FROM "members" WHERE "members"."source_type" = 'Project' AND "members"."type" IN ('ProjectMember') AND "members"."source_id" = $1 AND "members"."source_type" = $2 AND "members"."user_id" = 1 ORDER BY "members"."created_at" DESC, "members"."id" DESC LIMIT 1 [["source_id", 18], ["source_type", "Project"]] CACHE (0.0ms) SELECT "members".* FROM "members" WHERE "members"."source_type" = 'Project' AND "members". (1.4ms) SELECT COUNT(*) FROM "merge_requests" WHERE "merge_requests"."target_project_id" = $1 AND ("merge_requests"."state" IN ('opened','reopened')) [["target_project_id", 18]] Rendered layouts/nav/_project.html.haml (28.0ms) Rendered layouts/_collapse_button.html.haml (0.2ms) Rendered layouts/_flash.html.haml (0.1ms) Rendered layouts/_page.html.haml (32.9ms) Completed 200 OK in 166ms (Views: 117.4ms | ActiveRecord: 27.2ms) ``` These logs suffer from a number of problems: 1. They often lack timestamps or other contextual information (for example, project ID or user) 1. They may span multiple lines, which make them hard to find via Elasticsearch. 1. They lack a common structure, which make them hard to parse by log forwarders, such as Logstash or Fluentd. This also makes them hard to search. Note that currently on GitLab.com, any messages in `production.log` aren't indexed by Elasticsearch due to the sheer volume and noise. They do end up in Google Stackdriver, but it is still harder to search for logs there. See the [GitLab.com logging documentation](https://gitlab.com/gitlab-com/runbooks/blob/master/logging/doc/README.md) for more details. ## Use structured (JSON) logging Structured logging solves these problems. Consider the example from an API request: ```json {"time":"2018-10-29T12:49:42.123Z","severity":"INFO","duration":709.08,"db":14.59,"view":694.49,"status":200,"method":"GET","path":"/api/v4/projects","params":[{"key":"action","value":"git-upload-pack"},{"key":"changes","value":"_any"},{"key":"key_id","value":"secret"},{"key":"secret_token","value":"[FILTERED]"}],"host":"localhost","ip":"::1","ua":"Ruby","route":"/api/:version/projects","user_id":1,"username":"root","queue_duration":100.31,"gitaly_calls":30} ``` In a single line, we've included all the information that a user needs to understand what happened: the timestamp, HTTP method and path, user ID, etc. ### How to use JSON logging Suppose you want to log the events that happen in a project importer. You want to log issues created, merge requests, etc. as the importer progresses. Here's what to do: 1. Look at [the list of GitLab Logs](../administration/logs.md) to see if your log message might belong with one of the existing log files. 1. If there isn't a good place, consider creating a new filename, but check with a maintainer if it makes sense to do so. A log file should make it easy for people to search pertinent logs in one place. For example, `geo.log` contains all logs pertaining to GitLab Geo. To create a new file: 1. Choose a filename (for example, `importer_json.log`). 1. Create a new subclass of `Gitlab::JsonLogger`: ```ruby module Gitlab module Import class Logger < ::Gitlab::JsonLogger def self.file_name_noext 'importer' end end end end ``` 1. In your class where you want to log, you might initialize the logger as an instance variable: ```ruby attr_accessor :logger def initialize @logger = Gitlab::Import::Logger.build end ``` Note that it's useful to memoize this because creating a new logger each time you log opens a file, adding unnecessary overhead. 1. Now insert log messages into your code. When adding logs, make sure to include all the context as key-value pairs: ```ruby # BAD logger.info("Unable to create project #{project.id}") ``` ```ruby # GOOD logger.info(message: "Unable to create project", project_id: project.id) ``` 1. Be sure to create a common base structure of your log messages. For example, all messages might have `current_user_id` and `project_id` to make it easier to search for activities by user for a given time. #### Implicit schema for JSON logging When using something like Elasticsearch to index structured logs, there is a schema for the types of each log field (even if that schema is implicit / inferred). It's important to be consistent with the types of your field values, otherwise this might break the ability to search/filter on these fields, or even cause whole log events to be dropped. While much of this section is phrased in an Elasticsearch-specific way, the concepts should translate to many systems you might use to index structured logs. GitLab.com uses Elasticsearch to index log data. Unless a field type is explicitly mapped, Elasticsearch infers the type from the first instance of that field value it sees. Subsequent instances of that field value with different types either fail to be indexed, or in some cases (scalar/object conflict), the whole log line is dropped. GitLab.com's logging Elasticsearch sets [`ignore_malformed`](https://www.elastic.co/guide/en/elasticsearch/reference/current/ignore-malformed.html), which allows documents to be indexed even when there are simpler sorts of mapping conflict (for example, number / string), although indexing on the affected fields breaks. Examples: ```ruby # GOOD logger.info(message: "Import error", error_code: 1, error: "I/O failure") # BAD logger.info(message: "Import error", error: 1) logger.info(message: "Import error", error: "I/O failure") # WORST logger.info(message: "Import error", error: "I/O failure") logger.info(message: "Import error", error: { message: "I/O failure" }) ``` List elements must be the same type: ```ruby # GOOD logger.info(a_list: ["foo", "1", "true"]) # BAD logger.info(a_list: ["foo", 1, true]) ``` Resources: - [Elasticsearch mapping - avoiding type gotchas](https://www.elastic.co/guide/en/elasticsearch/guide/current/mapping.html#_avoiding_type_gotchas) - [Elasticsearch mapping types]( https://www.elastic.co/guide/en/elasticsearch/reference/current/mapping-types.html) #### Logging durations Similar to timezones, choosing the right time unit to log can impose avoidable overhead. So, whenever challenged to choose between seconds, milliseconds or any other unit, lean towards _seconds_ as float (with microseconds precision, i.e. `Gitlab::InstrumentationHelper::DURATION_PRECISION`). In order to make it easier to track timings in the logs, make sure the log key has `_s` as suffix and `duration` within its name (for example, `view_duration_s`). ## Multi-destination Logging GitLab is transitioning from unstructured/plaintext logs to structured/JSON logs. During this transition period some logs are recorded in multiple formats through multi-destination logging. ### How to use multi-destination logging Create a new logger class, inheriting from `MultiDestinationLogger` and add an array of loggers to a `LOGGERS` constant. The loggers should be classes that descend from `Gitlab::Logger`. For example, the user-defined loggers in the following examples could be inheriting from `Gitlab::Logger` and `Gitlab::JsonLogger`, respectively. You must specify one of the loggers as the `primary_logger`. The `primary_logger` is used when information about this multi-destination logger is displayed in the application (for example, using the `Gitlab::Logger.read_latest` method). The following example sets one of the defined `LOGGERS` as a `primary_logger`. ```ruby module Gitlab class FancyMultiLogger < Gitlab::MultiDestinationLogger LOGGERS = [UnstructuredLogger, StructuredLogger].freeze def self.loggers LOGGERS end def primary_logger UnstructuredLogger end end end ``` You can now call the usual logging methods on this multi-logger. For example: ```ruby FancyMultiLogger.info(message: "Information") ``` This message is logged by each logger registered in `FancyMultiLogger.loggers`. ### Passing a string or hash for logging When passing a string or hash to a `MultiDestinationLogger`, the log lines could be formatted differently, depending on the kinds of `LOGGERS` set. For example, let's partially define the loggers from the previous example: ```ruby module Gitlab # Similar to AppTextLogger class UnstructuredLogger < Gitlab::Logger ... end # Similar to AppJsonLogger class StructuredLogger < Gitlab::JsonLogger ... end end ``` Here are some examples of how messages would be handled by both the loggers. 1. When passing a string ```ruby FancyMultiLogger.info("Information") # UnstructuredLogger I, [2020-01-13T18:48:49.201Z #5647] INFO -- : Information # StructuredLogger {:severity=>"INFO", :time=>"2020-01-13T11:02:41.559Z", :correlation_id=>"b1701f7ecc4be4bcd4c2d123b214e65a", :message=>"Information"} ``` 1. When passing a hash ```ruby FancyMultiLogger.info({:message=>"This is my message", :project_id=>123}) # UnstructuredLogger I, [2020-01-13T19:01:17.091Z #11056] INFO -- : {"message"=>"Message", "project_id"=>"123"} # StructuredLogger {:severity=>"INFO", :time=>"2020-01-13T11:06:09.851Z", :correlation_id=>"d7e0886f096db9a8526a4f89da0e45f6", :message=>"This is my message", :project_id=>123} ``` ### Logging context metadata (through Rails or Grape requests) `Gitlab::ApplicationContext` stores metadata in a request lifecycle, which can then be added to the web request or Sidekiq logs. The API, Rails and Sidekiq logs contain fields starting with `meta.` with this context information. Entry points can be seen at: - [`ApplicationController`](https://gitlab.com/gitlab-org/gitlab/blob/master/app/controllers/application_controller.rb) - [External API](https://gitlab.com/gitlab-org/gitlab/blob/master/lib/api/api.rb) - [Internal API](https://gitlab.com/gitlab-org/gitlab/blob/master/lib/api/internal/base.rb) #### Adding attributes When adding new attributes, make sure they're exposed within the context of the entry points above and: - Pass them within the hash to the `with_context` (or `push`) method (make sure to pass a Proc if the method or variable shouldn't be evaluated right away) - Change `Gitlab::ApplicationContext` to accept these new values - Make sure the new attributes are accepted at [`Labkit::Context`](https://gitlab.com/gitlab-org/labkit-ruby/blob/master/lib/labkit/context.rb) See our [HOWTO: Use Sidekiq metadata logs](https://www.youtube.com/watch?v=_wDllvO_IY0) for further knowledge on creating visualizations in Kibana. The fields of the context are currently only logged for Sidekiq jobs triggered through web requests. See the [follow-up work](https://gitlab.com/gitlab-com/gl-infra/scalability/-/issues/68) for more information. ### Logging context metadata (through workers) Additional metadata can be attached to a worker through the use of the [`ApplicationWorker#log_extra_metadata_on_done`](https://gitlab.com/gitlab-org/gitlab/-/blob/16ecc33341a3f6b6bebdf78d863c5bce76b040d3/app/workers/concerns/application_worker.rb#L31-34) method. Using this method adds metadata that is later logged to Kibana with the done job payload. ```ruby class MyExampleWorker include ApplicationWorker def perform(*args) # Worker performs work # ... # The contents of value will appear in Kibana under `json.extra.my_example_worker.my_key` log_extra_metadata_on_done(:my_key, value) end end ``` Please see [this example](https://gitlab.com/gitlab-org/gitlab/-/blob/16ecc33341a3f6b6bebdf78d863c5bce76b040d3/app/workers/ci/pipeline_artifacts/expire_artifacts_worker.rb#L20-21) which logs a count of how many artifacts are destroyed per run of the `ExpireArtifactsWorker`. ## Exception Handling It often happens that you catch the exception and want to track it. It should be noted that manual logging of exceptions is not allowed, as: 1. Manual logged exceptions can leak confidential data, 1. Manual logged exception very often require to clean backtrace which reduces the boilerplate, 1. Very often manually logged exception needs to be tracked to Sentry as well, 1. Manually logged exceptions does not use `correlation_id`, which makes hard to pin them to request, user and context in which this exception was raised, 1. Manually logged exceptions often end up across multiple files, which increases burden scraping all logging files. To avoid duplicating and having consistent behavior the `Gitlab::ErrorTracking` provides helper methods to track exceptions: 1. `Gitlab::ErrorTracking.track_and_raise_exception`: this method logs, sends exception to Sentry (if configured) and re-raises the exception, 1. `Gitlab::ErrorTracking.track_exception`: this method only logs and sends exception to Sentry (if configured), 1. `Gitlab::ErrorTracking.log_exception`: this method only logs the exception, and DOES NOT send the exception to Sentry, 1. `Gitlab::ErrorTracking.track_and_raise_for_dev_exception`: this method logs, sends exception to Sentry (if configured) and re-raises the exception for development and test environments. It is advised to only use `Gitlab::ErrorTracking.track_and_raise_exception` and `Gitlab::ErrorTracking.track_exception` as presented on below examples. Consider adding additional extra parameters to provide more context for each tracked exception. ### Example ```ruby class MyService < ::BaseService def execute project.perform_expensive_operation success rescue => e Gitlab::ErrorTracking.track_exception(e, project_id: project.id) error('Exception occurred') end end ``` ```ruby class MyService < ::BaseService def execute project.perform_expensive_operation success rescue => e Gitlab::ErrorTracking.track_and_raise_exception(e, project_id: project.id) end end ``` ## Additional steps with new log files 1. Consider log retention settings. By default, Omnibus rotates any logs in `/var/log/gitlab/gitlab-rails/*.log` every hour and [keep at most 30 compressed files](https://docs.gitlab.com/omnibus/settings/logs.html#logrotate). On GitLab.com, that setting is only 6 compressed files. These settings should suffice for most users, but you may need to tweak them in [Omnibus GitLab](https://gitlab.com/gitlab-org/omnibus-gitlab). 1. If you add a new file, submit an issue to the [production tracker](https://gitlab.com/gitlab-com/gl-infra/production/-/issues) or a merge request to the [`gitlab_fluentd`](https://gitlab.com/gitlab-cookbooks/gitlab_fluentd) project. See [this example](https://gitlab.com/gitlab-cookbooks/gitlab_fluentd/-/merge_requests/51/diffs). 1. Be sure to update the [GitLab CE/EE documentation](../administration/logs.md) and the [GitLab.com runbooks](https://gitlab.com/gitlab-com/runbooks/blob/master/docs/logging/README.md).