• Version requirements
  • Elasticsearch version requirements
  • OpenSearch version requirements
• System requirements
• Install Elasticsearch
• Upgrade to a new Elasticsearch major version
• Elasticsearch repository indexer
  • Omnibus GitLab
  • From source
    • Install dependencies
      • Debian / Ubuntu
      • CentOS / RHEL
      • macOS
    • Build and install
  • View indexing errors
• Enable Advanced Search
  • Advanced Search configuration
  • Access requirements
    • Elasticsearch with role privileges
    • AWS OpenSearch Service with fine-grained access control
      • Connecting with a master user in the internal database
      • Connecting with an IAM user
      • Permissions for fine-grained access control
  • Limit the number of namespaces and projects that can be indexed
• Enable custom language analyzers
• Disable Advanced Search
• Unpause Indexing
• Zero downtime reindexing
  • Trigger the reindex via the Advanced Search administration
    • Elasticsearch zero-downtime reindexing
      • Slice multiplier
      • Maximum running slices
  • Mark the most recent reindex job as failed and resume the indexing
• Advanced Search migrations
  • Retry a halted migration
  • All migrations must be finished before doing a major upgrade
• GitLab Advanced Search Rake tasks
  • Environment variables
  • Indexing a range of projects or a specific project
• Advanced Search index scopes
• Tuning
  • Guidance on choosing optimal cluster configuration
  • Advanced Search integration settings guidance
  • How to index large instances efficiently
  • Deleted documents
• Index large instances with dedicated Sidekiq nodes or processes
  • Single node, two processes
  • Two nodes, one process for each
• Reverting to Basic Search
• Data recovery: Elasticsearch is a secondary data store only

Elasticsearch integration

This page describes how to enable Advanced Search. When enabled, Advanced Search provides faster search response times and improved search features.

Version requirements

Elasticsearch version requirements

Advanced Search works with the following versions of Elasticsearch.

Advanced Search follows the Elasticsearch end-of-life policy. When we change Elasticsearch supported versions in GitLab, we announce them in deprecation notes in monthly release posts before we remove them.

OpenSearch version requirements

If your version of Elasticsearch or OpenSearch is incompatible, to prevent data loss, indexing pauses and a message is logged in the elasticsearch.log file.

If you are using a compatible version and after connecting to OpenSearch, you get the message Elasticsearch version not compatible, unpause indexing.

System requirements

Elasticsearch requires additional resources to those documented in the GitLab system requirements.

Memory, CPU, and storage resource amounts vary depending on the amount of data you index into the Elasticsearch cluster. Heavily used Elasticsearch clusters may require more resources. The estimate_cluster_size Rake task (introduced in GitLab 13.10) uses the total repository size to estimate the Advanced Search storage requirements.

Install Elasticsearch

Elasticsearch is not included in the Omnibus packages or when you install from source. You must install it separately and ensure you select your version. Detailed information on how to install Elasticsearch is out of the scope of this page.

You can install Elasticsearch yourself, or use a cloud hosted offering such as Elasticsearch Service (available on AWS, GCP, or Azure) or the Amazon OpenSearch service.

You should install Elasticsearch on a separate server. Running Elasticsearch on the same server as GitLab is not recommended and can cause a degradation in GitLab instance performance.

For a single node Elasticsearch cluster, the functional cluster health status is always yellow due to the allocation of the primary shard. Elasticsearch cannot assign replica shards to the same node as primary shards.

The search index updates after you:

• Add data to the database or repository.
• Enable Elasticsearch in the Admin Area.

Upgrade to a new Elasticsearch major version

You are not required to change the GitLab configuration when you upgrade Elasticsearch.

Elasticsearch repository indexer

To index Git repository data, GitLab uses an indexer written in Go.

Depending on your GitLab version, there are different installation procedures for the Go indexer:

• For Omnibus GitLab 11.8 or greater, see Omnibus GitLab.
• For installations from source or older versions of Omnibus GitLab, install the indexer from source.
• If you are using GitLab Development Kit, see GDK Elasticsearch how-to.

Omnibus GitLab

Starting with GitLab 11.8, the Go indexer is included in Omnibus GitLab. The former Ruby-based indexer was removed in GitLab 12.3.

From source

First, we need to install some dependencies, then we build and install the indexer itself.

Install dependencies

This project relies on International Components for Unicode (ICU) for text encoding, therefore we must ensure the development packages for your platform are installed before running make.

Debian / Ubuntu

To install on Debian or Ubuntu, run:

sudo apt install libicu-dev

CentOS / RHEL

To install on CentOS or RHEL, run:

sudo yum install libicu-devel

macOS

To install on macOS, run:

brew install icu4c
export PKG_CONFIG_PATH="/usr/local/opt/icu4c/lib/pkgconfig:$PKG_CONFIG_PATH"

Build and install

To build and install the indexer, run:

indexer_path=/home/git/gitlab-elasticsearch-indexer

# Run the installation task for gitlab-elasticsearch-indexer:
sudo -u git -H bundle exec rake gitlab:indexer:install[$indexer_path] RAILS_ENV=production
cd $indexer_path && sudo make install

The gitlab-elasticsearch-indexer is installed to /usr/local/bin.

You can change the installation path with the PREFIX environment variable. Remember to pass the -E flag to sudo if you do so.

Example:

PREFIX=/usr sudo -E make install

After installation, be sure to enable Elasticsearch.

View indexing errors

Errors from the GitLab Elasticsearch Indexer are reported in the elasticsearch.log file and the sidekiq.log file with a json.exception.class of Gitlab::Elastic::Indexer::Error. These errors may occur when indexing Git repository data.

Enable Advanced Search

For GitLab instances with more than 50 GB repository data you can follow the instructions for how to index large instances efficiently below.

To enable Advanced Search, you must have administrator access to GitLab:

1. On the top bar, select Main menu > Admin.

2. On the left sidebar, select Settings > Advanced Search.

   To see the Advanced Search section, you need an active GitLab Premium license.
3. Configure the Advanced Search settings for your Elasticsearch cluster. Do not enable Search with Elasticsearch enabled yet.
4. Enable Elasticsearch indexing and select Save changes. This creates an empty index if one does not already exist.
5. Select Index all projects.
6. Select Check progress in the confirmation message to see the status of the background jobs.

7. Personal snippets must be indexed using another Rake task:

   # Omnibus installations
   sudo gitlab-rake gitlab:elastic:index_snippets
   
   # Installations from source
   bundle exec rake gitlab:elastic:index_snippets RAILS_ENV=production
   

8. After indexing completes, enable Search with Elasticsearch enabled and select Save changes.

Advanced Search configuration

The following Elasticsearch settings are available:

Access requirements

Elasticsearch with role privileges

To access and perform operations in Elasticsearch, GitLab requires a role with the following privileges:

{
  "cluster": ["monitor"],
  "indices": [
    {
      "names": ["gitlab-*"],
      "privileges": [
        "create_index",
        "delete_index",
        "view_index_metadata",
        "read",
        "manage",
        "write"
      ]
    }
  ]
}

For more information, see Elasticsearch security privileges.

AWS OpenSearch Service with fine-grained access control

To use the self-managed AWS OpenSearch Service with GitLab using fine-grained access control, try one of the recommended configurations.

Configure your instance’s domain access policies to allow es:ESHttp* actions. You can customize the following example configuration to limit principals or resources:

{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Effect": "Allow",
      "Principal": {
        "AWS": [
          "*"
        ]
      },
      "Action": [
        "es:ESHttp*"
      ],
      "Resource": "domain-arn/*"
    }
  ]
}

For more information, see Identity and Access Management in Amazon OpenSearch Service.

Connecting with a master user in the internal database

When using fine-grained access control with a user in the internal database, you should use HTTP basic authentication to connect to OpenSearch. You can provide the master username and password as part of the OpenSearch URL or in the Username and Password text boxes in the Advanced Search settings. See Tutorial: Internal user database and HTTP basic authentication for details.

Connecting with an IAM user

When using fine-grained access control with IAM credentials, you can provide the credentials in the AWS OpenSearch IAM credentials section in the Advanced Search settings.

Permissions for fine-grained access control

The following permissions are required for Advanced Search. See Creating roles for details.

{
  "cluster_permissions": [
    "cluster_composite_ops",
    "cluster_monitor"
  ],
  "index_permissions": [
    {
      "index_patterns": [
        "gitlab*"
      ],
      "allowed_actions": [
        "data_access",
        "manage_aliases",
        "search",
        "create_index",
        "delete",
        "manage"
      ]
    },
    {
      "index_patterns": [
        "*"
      ],
      "allowed_actions": [
        "indices:admin/aliases/get",
        "indices:monitor/stats"
      ]
    }
  ]
}

The index pattern * requires a few permissions for Advanced Search to work.

Limit the number of namespaces and projects that can be indexed

If you check checkbox Limit the number of namespaces and projects that can be indexed under Elasticsearch indexing restrictions more options become available.

You can select namespaces and projects to index exclusively. If the namespace is a group, it includes any subgroups and projects belonging to those subgroups to be indexed as well.

Advanced Search only provides cross-group code/commit search (global) if all name-spaces are indexed. In this particular scenario where only a subset of namespaces are indexed, a global search does not provide a code or commit scope. This is possible only in the scope of an indexed namespace. There is no way to code/commit search in multiple indexed namespaces (when only a subset of namespaces has been indexed). For example if two groups are indexed, there is no way to run a single code search on both. You can only run a code search on the first group and then on the second.

You can filter the selection dropdown list by writing part of the namespace or project name you’re interested in.

Enable custom language analyzers

You can improve the language support for Chinese and Japanese languages by utilizing smartcn and/or kuromoji analysis plugins from Elastic.

To enable languages support:

1. Install the desired plugins, refer to Elasticsearch documentation for plugins installation instructions. The plugins must be installed on every node in the cluster, and each node must be restarted after installation. For a list of plugins, see the table later in this section.
2. On the top bar, select Main menu > Admin.
3. On the left sidebar, select Settings > Advanced Search.
4. Locate Custom analyzers: language support.
5. Enable plugins support for Indexing.
6. Select Save changes for the changes to take effect.
7. Trigger Zero downtime reindexing or reindex everything from scratch to create a new index with updated mappings.
8. Enable plugins support for Searching after the previous step is completed.

For guidance on what to install, see the following Elasticsearch language plugin options:

Disable Advanced Search

To disable the Elasticsearch integration:

1. On the top bar, select Main menu > Admin.
2. On the left sidebar, select Settings > Advanced Search.
3. Uncheck Elasticsearch indexing and Search with Elasticsearch enabled.
4. Select Save changes.

5. Optional. Delete the existing indices:

   # Omnibus installations
   sudo gitlab-rake gitlab:elastic:delete_index
   
   # Installations from source
   bundle exec rake gitlab:elastic:delete_index RAILS_ENV=production
   

Unpause Indexing

1. On the top bar, select Main menu > Admin.
2. On the left sidebar, select Settings > Advanced Search.
3. Expand Advanced Search.
4. Clear the Pause Elasticsearch indexing checkbox.

Zero downtime reindexing

The idea behind this reindexing method is to leverage the Elasticsearch reindex API and Elasticsearch index alias feature to perform the operation. We set up an index alias which connects to a primary index which is used by GitLab for reads/writes. When reindexing process starts, we temporarily pause the writes to the primary index. Then, we create another index and invoke the Reindex API which migrates the index data onto the new index. After the reindexing job is complete, we switch to the new index by connecting the index alias to it which becomes the new primary index. At the end, we resume the writes and typical operation resumes.

Trigger the reindex via the Advanced Search administration

To trigger the reindexing process:

1. Sign in to your GitLab instance as an administrator.
2. On the top bar, select Main menu > Admin.
3. On the left sidebar, select Settings > Advanced Search.
4. Expand Elasticsearch zero-downtime reindexing.
5. Select Trigger cluster reindexing.

Reindexing can be a lengthy process depending on the size of your Elasticsearch cluster.

After this process is completed, the original index is scheduled to be deleted after 14 days. You can cancel this action by pressing the Cancel button on the same page you triggered the reindexing process.

While the reindexing is running, you can follow its progress under that same section.

Elasticsearch zero-downtime reindexing

1. On the top bar, select Main menu > Admin.
2. On the left sidebar, select Settings > Advanced Search.
3. Expand Elasticsearch zero-downtime reindexing, and you’ll find the following options:

• Slice multiplier
• Maximum running slices

Slice multiplier

The slice multiplier calculates the number of slices during reindexing.

GitLab uses manual slicing to control the reindex efficiently and safely, which enables users to retry only failed slices.

The multiplier defaults to 2 and applies to the number of shards per index. For example, if this value is 2 and your index has 20 shards, then the reindex task is split into 40 slices.

Maximum running slices

The maximum running slices parameter defaults to 60 and corresponds to the maximum number of slices allowed to run concurrently during Elasticsearch reindexing.

Setting this value too high can have adverse performance impacts as your cluster may become heavily saturated with searches and writes. Setting this value too low may lead the reindexing process to take a very long time to complete.

The best value for this depends on your cluster size, whether you’re willing to accept some degraded search performance during reindexing, and how important it is for the reindex to finish quickly and resume indexing.

Mark the most recent reindex job as failed and resume the indexing

Sometimes, you might want to abandon the unfinished reindex job and resume the indexing. You can achieve this via the following steps:

1. Mark the most recent reindex job as failed:

   # Omnibus installations
   sudo gitlab-rake gitlab:elastic:mark_reindex_failed
   
   # Installations from source
   bundle exec rake gitlab:elastic:mark_reindex_failed RAILS_ENV=production
   

2. On the top bar, select Main menu > Admin.
3. On the left sidebar, select Settings > Advanced Search.
4. Expand Advanced Search.
5. Clear the Pause Elasticsearch indexing checkbox.

Advanced Search migrations

With reindex migrations running in the background, there’s no need for a manual intervention. This usually happens in situations where new features are added to Advanced Search, which means adding or changing the way content is indexed.

To confirm that the Advanced Search migrations ran, you can check with:

curl "$CLUSTER_URL/gitlab-production-migrations/_search?q=*" | jq .

This should return something similar to:

{
  "took": 14,
  "timed_out": false,
  "_shards": {
    "total": 1,
    "successful": 1,
    "skipped": 0,
    "failed": 0
  },
  "hits": {
    "total": {
      "value": 1,
      "relation": "eq"
    },
    "max_score": 1,
    "hits": [
      {
        "_index": "gitlab-production-migrations",
        "_type": "_doc",
        "_id": "20201105181100",
        "_score": 1,
        "_source": {
          "completed": true
        }
      }
    ]
  }
}

To debug issues with the migrations you can check the elasticsearch.log file.

Retry a halted migration

Some migrations are built with a retry limit. If the migration cannot finish within the retry limit, it is halted and a notification is displayed in the Advanced Search integration settings. It is recommended to check the elasticsearch.log file to debug why the migration was halted and make any changes before retrying the migration. Once you believe you’ve fixed the cause of the failure, select “Retry migration”, and the migration is scheduled to be retried in the background.

If you cannot get the migration to succeed, you may consider the last resort to recreate the index from scratch. This may allow you to skip over the problem because a newly created index skips all migrations as the index is recreated with the correct up-to-date schema.

All migrations must be finished before doing a major upgrade

Before doing a major version GitLab upgrade, you should have completed all migrations that exist up until the latest minor version before that major version. If you have halted migrations, these need to be resolved and retried before proceeding with a major version upgrade. Read more about upgrading to a new major version.

GitLab Advanced Search Rake tasks

Rake tasks are available to:

• Build and install the indexer.
• Delete indices when disabling Elasticsearch.
• Add GitLab data to an index.

The following are some available Rake tasks:

Environment variables

In addition to the Rake tasks, there are some environment variables that can be used to modify the process:

Indexing a range of projects or a specific project

Using the ID_FROM and ID_TO environment variables, you can index a limited number of projects. This can be useful for staging indexing.

root@git:~# sudo gitlab-rake gitlab:elastic:index_projects ID_FROM=1 ID_TO=100

Because ID_FROM and ID_TO use the or equal to comparison, you can use them to index only one project by setting both to the same project ID:

root@git:~# sudo gitlab-rake gitlab:elastic:index_projects ID_FROM=5 ID_TO=5
Indexing project repositories...I, [2019-03-04T21:27:03.083410 #3384]  INFO -- : Indexing GitLab User / test (ID=33)...
I, [2019-03-04T21:27:05.215266 #3384]  INFO -- : Indexing GitLab User / test (ID=33) is done!

Advanced Search index scopes

When performing a search, the GitLab index uses the following scopes:

Tuning

Guidance on choosing optimal cluster configuration

For basic guidance on choosing a cluster configuration you may refer to Elastic Cloud Calculator. You can find more information below.

• Generally, you want to use at least a 2-node cluster configuration with one replica, which allows you to have resilience. If your storage usage is growing quickly, you may want to plan horizontal scaling (adding more nodes) beforehand.
• It’s not recommended to use HDD storage with the search cluster, because it takes a hit on performance. It’s better to use SSD storage (NVMe or SATA SSD drives for example).
• You can use the GitLab Performance Tool to benchmark search performance with different search cluster sizes and configurations.
• Heap size should be set to no more than 50% of your physical RAM. Additionally, it shouldn’t be set to more than the threshold for zero-based compressed oops. The exact threshold varies, but 26 GB is safe on most systems, but can also be as large as 30 GB on some systems. See Heap size settings and Setting JVM options for more details.
• Number of CPUs (CPU cores) per node usually corresponds to the Number of Elasticsearch shards setting described below.
• A good guideline is to ensure you keep the number of shards per node below 20 per GB heap it has configured. A node with a 30 GB heap should therefore have a maximum of 600 shards, but the further below this limit you can keep it the better. This generally helps the cluster stay in good health.
• Number of Elasticsearch shards:
  • Small shards result in small segments, which increases overhead. Aim to keep the average shard size between at least a few GB and a few tens of GB.
  • Another consideration is the number of documents. To determine the number of shards to use, sum the numbers in the Main menu > Admin > Dashboard > Statistics pane (the number of documents to be indexed), divide by 5 million, and add 5. For example:
    • If you have fewer than about 2,000,000 documents, use the default of 5 shards
    • 10,000,000 documents: 10000000/5000000 + 5 = 7 shards
    • 100,000,000 documents: 100000000/5000000 + 5 = 25 shards
• refresh_interval is a per index setting. You may want to adjust that from default 1s to a bigger value if you don’t need data in real-time. This changes how soon you see fresh results. If that’s important for you, you should leave it as close as possible to the default value.
• You might want to raise indices.memory.index_buffer_size to 30% or 40% if you have a lot of heavy indexing operations.

Advanced Search integration settings guidance

• The Number of Elasticsearch shards setting usually corresponds with the number of CPUs available in your cluster. For example, if you have a 3-node cluster with 4 cores each, this means you benefit from having at least 3*4=12 shards in the cluster. It’s only possible to change the shards number by using Split index API or by reindexing to a different index with a changed number of shards.
• The Number of Elasticsearch replicas setting should most of the time be equal to 1 (each shard has 1 replica). Using 0 is not recommended, because losing one node corrupts the index.

How to index large instances efficiently

This section may be helpful in the event that the other basic instructions cause problems due to large volumes of data being indexed.

1. Configure your Elasticsearch host and port.

2. Create empty indices:

   # Omnibus installations
   sudo gitlab-rake gitlab:elastic:create_empty_index
   
   # Installations from source
   bundle exec rake gitlab:elastic:create_empty_index RAILS_ENV=production
   

3. If this is a re-index of your GitLab instance, clear the index status:

   # Omnibus installations
   sudo gitlab-rake gitlab:elastic:clear_index_status
   
   # Installations from source
   bundle exec rake gitlab:elastic:clear_index_status RAILS_ENV=production
   

4. Enable Elasticsearch indexing.

5. Indexing large Git repositories can take a while. To speed up the process, you can tune for indexing speed:

   • You can temporarily disable refresh, the operation responsible for making changes to an index available to search.

   • You can set the number of replicas to 0. This setting controls the number of copies each primary shard of an index has. Thus, having 0 replicas effectively disables the replication of shards across nodes, which should increase the indexing performance. This is an important trade-off in terms of reliability and query performance. It is important to remember to set the replicas to a considered value after the initial indexing is complete.

   In our experience, you can expect a 20% decrease in indexing time. After completing indexing in a later step, you can return refresh and number_of_replicas to their desired settings.

   This step is optional but may help significantly speed up large indexing operations.

   curl --request PUT localhost:9200/gitlab-production/_settings --header 'Content-Type: application/json' \
        --data '{
          "index" : {
              "refresh_interval" : "-1",
              "number_of_replicas" : 0
          } }'
   

6. Index projects and their associated data:

   # Omnibus installations
   sudo gitlab-rake gitlab:elastic:index_projects
   
   # Installations from source
   bundle exec rake gitlab:elastic:index_projects RAILS_ENV=production
   

   This enqueues a Sidekiq job for each project that needs to be indexed. You can view the jobs in Main menu > Admin > Monitoring > Background Jobs > Queues Tab and select elastic_commit_indexer, or you can query indexing status using a Rake task:

   # Omnibus installations
   sudo gitlab-rake gitlab:elastic:index_projects_status
   
   # Installations from source
   bundle exec rake gitlab:elastic:index_projects_status RAILS_ENV=production
   
   Indexing is 65.55% complete (6555/10000 projects)
   

   If you want to limit the index to a range of projects you can provide the ID_FROM and ID_TO parameters:

   # Omnibus installations
   sudo gitlab-rake gitlab:elastic:index_projects ID_FROM=1001 ID_TO=2000
   
   # Installations from source
   bundle exec rake gitlab:elastic:index_projects ID_FROM=1001 ID_TO=2000 RAILS_ENV=production
   

   Where ID_FROM and ID_TO are project IDs. Both parameters are optional. The above example indexes all projects from ID 1001 up to (and including) ID 2000.

   Sometimes the project indexing jobs queued by gitlab:elastic:index_projects can get interrupted. This may happen for many reasons, but it’s always safe to run the indexing task again. It skips repositories that have already been indexed.

   As the indexer stores the last commit SHA of every indexed repository in the database, you can run the indexer with the special parameter UPDATE_INDEX and it checks every project repository again to make sure that every commit in a repository is indexed, which can be useful in case if your index is outdated:

   # Omnibus installations
   sudo gitlab-rake gitlab:elastic:index_projects UPDATE_INDEX=true ID_TO=1000
   
   # Installations from source
   bundle exec rake gitlab:elastic:index_projects UPDATE_INDEX=true ID_TO=1000 RAILS_ENV=production
   

   You can also use the gitlab:elastic:clear_index_status Rake task to force the indexer to “forget” all progress, so it retries the indexing process from the start.

7. Personal snippets are not associated with a project and need to be indexed separately:

   # Omnibus installations
   sudo gitlab-rake gitlab:elastic:index_snippets
   
   # Installations from source
   bundle exec rake gitlab:elastic:index_snippets RAILS_ENV=production
   

8. Enable replication and refreshing again after indexing (only if you previously disabled it):

   curl --request PUT localhost:9200/gitlab-production/_settings --header 'Content-Type: application/json' \
        --data '{
          "index" : {
              "number_of_replicas" : 1,
              "refresh_interval" : "1s"
          } }'
   

   A force merge should be called after enabling the refreshing above.

   For Elasticsearch 6.x, the index should be in read-only mode before proceeding with the force merge:

   curl --request PUT localhost:9200/gitlab-production/_settings --header 'Content-Type: application/json' \
        --data '{
          "settings": {
            "index.blocks.write": true
          } }'
   

   Then, initiate the force merge:

   curl --request POST 'localhost:9200/gitlab-production/_forcemerge?max_num_segments=5'
   

   After this, if your index is in read-only mode, switch back to read-write:

   curl --request PUT localhost:9200/gitlab-production/_settings --header 'Content-Type: application/json' \
        --data '{
          "settings": {
            "index.blocks.write": false
          } }'
   

9. After the indexing has completed, enable Search with Elasticsearch enabled.

Deleted documents

Whenever a change or deletion is made to an indexed GitLab object (a merge request description is changed, a file is deleted from the default branch in a repository, a project is deleted, etc), a document in the index is deleted. However, since these are “soft” deletes, the overall number of “deleted documents”, and therefore wasted space, increases. Elasticsearch does intelligent merging of segments to remove these deleted documents. However, depending on the amount and type of activity in your GitLab installation, it’s possible to see as much as 50% wasted space in the index.

In general, we recommend letting Elasticsearch merge and reclaim space automatically, with the default settings. From Lucene’s Handling of Deleted Documents, “Overall, besides perhaps decreasing the maximum segment size, it is best to leave Lucene defaults as-is and not fret too much about when deletes are reclaimed.”

However, some larger installations may wish to tune the merge policy settings:

• Consider reducing the index.merge.policy.max_merged_segment size from the default 5 GB to maybe 2 GB or 3 GB. Merging only happens when a segment has at least 50% deletions. Smaller segment sizes allows merging to happen more frequently.

  curl --request PUT localhost:9200/gitlab-production/_settings ---header 'Content-Type: application/json' \
       --data '{
         "index" : {
           "merge.policy.max_merged_segment": "2gb"
         }
       }'
  

• You can also adjust index.merge.policy.reclaim_deletes_weight, which controls how aggressively deletions are targeted. But this can lead to costly merge decisions, so we recommend not changing this unless you understand the tradeoffs.

  curl --request PUT localhost:9200/gitlab-production/_settings ---header 'Content-Type: application/json' \
       --data '{
         "index" : {
           "merge.policy.reclaim_deletes_weight": "3.0"
         }
       }'
  

• Do not do a force merge to remove deleted documents. A warning in the documentation states that this can lead to very large segments that may never get reclaimed, and can also cause significant performance or availability issues.

Index large instances with dedicated Sidekiq nodes or processes

Indexing a large instance can be a lengthy and resource-intensive process that has the potential of overwhelming Sidekiq nodes and processes. This negatively affects the GitLab performance and availability.

As GitLab allows you to start multiple Sidekiq processes, you can create an additional process dedicated to indexing a set of queues (or queue group). This way, you can ensure that indexing queues always have a dedicated worker, while the rest of the queues have another dedicated worker to avoid contention.

For this purpose, use the queue selectors option that allows a more general selection of queue groups using a worker matching query.

To handle these two queue groups, we generally recommend one of the following two options. You can either:

• Use two queue groups on one single node.
• Use two queue groups, one on each node.

For the steps below, consider:

• feature_category=global_search as an indexing queue group with its own Sidekiq process.
• feature_category!=global_search as a non-indexing queue group that has its own Sidekiq process.

Single node, two processes

To create both an indexing and a non-indexing Sidekiq process in one node:

1. On your Sidekiq node, change the /etc/gitlab/gitlab.rb file to:

   sidekiq['enable'] = true
   sidekiq['queue_selector'] = true
   sidekiq['queue_groups'] = [
      "feature_category=global_search",
      "feature_category!=global_search"
    ]
   

2. Save the file and reconfigure GitLab for the changes to take effect.

Two nodes, one process for each

To handle these queue groups on two nodes:

1. To set up the indexing Sidekiq process, on your indexing Sidekiq node, change the /etc/gitlab/gitlab.rb file to:

    sidekiq['enable'] = true
     sidekiq['queue_selector'] = true
     sidekiq['queue_groups'] = [
       "feature_category=global_search"
     ]
   

2. Save the file and reconfigure GitLab for the changes to take effect.

3. To set up the non-indexing Sidekiq process, on your non-indexing Sidekiq node, change the /etc/gitlab/gitlab.rb file to:

    sidekiq['enable'] = true
     sidekiq['queue_selector'] = true
     sidekiq['queue_groups'] = [
       "feature_category!=global_search"
     ]
   

   to set up a non-indexing Sidekiq process.

4. Save the file and reconfigure GitLab for the changes to take effect.

Reverting to Basic Search

Sometimes there may be issues with your Elasticsearch index data and as such GitLab allows you to revert to “basic search” when there are no search results and assuming that basic search is supported in that scope. This “basic search” behaves as though you don’t have Advanced Search enabled at all for your instance and search using other data sources (such as PostgreSQL data and Git data).

Data recovery: Elasticsearch is a secondary data store only

The use of Elasticsearch in GitLab is only ever as a secondary data store. This means that all of the data stored in Elasticsearch can always be derived again from other data sources, specifically PostgreSQL and Gitaly. Therefore, if the Elasticsearch data store is ever corrupted for whatever reason, you can reindex everything from scratch.