// tag::cloud[] **Use {kib}** //tag::kibana-api-ex[] . Log in to the {ess-console}[{ecloud} console]. + . On the **Elasticsearch Service** panel, click the name of your deployment. + NOTE: If the name of your deployment is disabled your {kib} instances might be unhealthy, in which case please contact https://support.elastic.co[Elastic Support]. If your deployment doesn't include {kib}, all you need to do is {cloud}/ec-access-kibana.html[enable it first]. + . Open your deployment's side navigation menu (placed under the Elastic logo in the upper left corner) and go to **Stack Management > Index Management**. . In the list of all your indices, click the `Replicas` column twice to sort the indices based on their number of replicas starting with the one that has the most. Go through the indices and pick one by one the index with the least importance and higher number of replicas. + WARNING: Reducing the replicas of an index can potentially reduce search throughput and data redundancy. + . For each index you chose, click on its name, then on the panel that appears click `Edit settings`, reduce the value of the `index.number_of_replicas` to the desired value and then click `Save`. + [role="screenshot"] image::images/troubleshooting/disk/reduce_replicas.png[Reducing replicas,align="center"] + . Continue this process until the cluster is healthy again. // end::cloud[] // tag::self-managed[] In order to estimate how many replicas need to be removed, first you need to estimate the amount of disk space that needs to be released. . First, retrieve the relevant disk thresholds that will indicate how much space should be released. The relevant thresholds are the <> for all the tiers apart from the frozen one and the <> for the frozen tier. The following example demonstrates disk shortage in the hot tier, so we will only retrieve the high watermark: + [source,console] ---- GET _cluster/settings?include_defaults&filter_path=*.cluster.routing.allocation.disk.watermark.high* ---- + The response will look like this: + [source,console-result] ---- { "defaults": { "cluster": { "routing": { "allocation": { "disk": { "watermark": { "high": "90%", "high.max_headroom": "150GB" } } } } } } } ---- // TEST[skip:illustration purposes only] + The above means that in order to resolve the disk shortage we need to either drop our disk usage below the 90% or have more than 150GB available, read more on how this threshold works <>. . The next step is to find out the current disk usage; this will indicate how much space should be freed. For simplicity, our example has one node, but you can apply the same for every node over the relevant threshold. + [source,console] ---- GET _cat/allocation?v&s=disk.avail&h=node,disk.percent,disk.avail,disk.total,disk.used,disk.indices,shards ---- + The response will look like this: + [source,console-result] ---- node disk.percent disk.avail disk.total disk.used disk.indices shards instance-0000000000 91 4.6gb 35gb 31.1gb 29.9gb 111 ---- // TEST[skip:illustration purposes only] . The high watermark configuration indicates that the disk usage needs to drop below 90%. Consider allowing some padding, so the node will not go over the threshold in the near future. In this example, let's release approximately 7GB. . The next step is to list all the indices and choose which replicas to reduce. + NOTE: The following command orders the indices with descending number of replicas and primary store size. We do this to help you choose which replicas to reduce under the assumption that the more replicas you have the smaller the risk if you remove a copy and the bigger the replica the more space will be released. This does not take into consideration any functional requirements, so please see it as a mere suggestion. + [source,console] ---- GET _cat/indices?v&s=rep:desc,pri.store.size:desc&h=health,index,pri,rep,store.size,pri.store.size ---- + The response will look like: + [source,console-result] ---- health index pri rep store.size pri.store.size green my_index 2 3 9.9gb 3.3gb green my_other_index 2 3 1.8gb 470.3mb green search-products 2 3 278.5kb 69.6kb green logs-000001 1 0 7.7gb 7.7gb ---- // TEST[skip:illustration purposes only] + . In the list above we see that if we reduce the replicas to 1 of the indices `my_index` and `my_other_index` we will release the required disk space. It is not necessary to reduce the replicas of `search-products` and `logs-000001` does not have any replicas anyway. Reduce the replicas of one or more indices with the <>: + WARNING: Reducing the replicas of an index can potentially reduce search throughput and data redundancy. + [source,console] ---- PUT my_index,my_other_index/_settings { "index.number_of_replicas": 1 } ---- // TEST[skip:illustration purposes only] // end::self-managed[] IMPORTANT: After reducing the replicas please consider there are enough replicas to ensure your search performance and reliability requirements. If not, at your earliest convenience (i) consider using <> to manage more efficiently the retention of your timeseries data, or (ii) reduce the amount of data you have by disabling the `source` or removing less important data, or (iii) increase your disk capacity.