@@ -476,6 +476,25 @@ When performing a search, the GitLab index will use the following scopes:
## Tuning
### Guidance on choosing optimal cluster configuration
For basic guidance on choosing a cluster configuration you may refer to [Elasic Cloud Calculator](https://cloud.elastic.co/pricing). You can find more information below.
- Generally, you will want to use at least a 2-node cluster configuration with one replica, which will allow 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 will take 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](https://gitlab.com/gitlab-org/quality/performance) 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 [Setting the heap size](https://www.elastic.co/guide/en/elasticsearch/reference/current/heap-size.html#heap-size) for more details.
- Number of CPUs (CPU cores) per node is 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 30GB heap should therefore have a maximum of 600 shards, but the further below this limit you can keep it the better. This will generally help the cluster stay in good health.
- 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, you should aim for this simple formula for the number of shards: `number of expected documents / 5M +1`.
-`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 realtime. This will change how soon you will 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`](https://www.elastic.co/guide/en/elasticsearch/reference/current/indexing-buffer.html) to 30% or 40% if you have a lot of heavy indexing operations.
### Elasticsearch integration settings guidance
- The `Number of Elasticsearch shards` setting usually corresponds with number of CPUs available in your cluster. For example, if you have a 3-node cluster with 4 cores each, this means you will benefit from having at least 3*4=12 shards in the cluster. Please note, it's only possible to change the shards number by using [Split index API](https://www.elastic.co/guide/en/elasticsearch/reference/current/indices-split-index.html) 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 will have 1 replica). Using `0` is not recommended, because losing one node will corrupt the index.
### 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 master 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 in order 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.
