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- In Elasticsearch 6.x, Fortinet has observed that Elasticsearch CLI performance degrades when the total number of shards in the cluster (including Hot and Warm nodes) is more than 15K. Newer versions may have a higher upper limit.
Dedicated master nodes in Amazon OpenSearch Service
https://docs.aws.amazon.com/opensearch-service/latest/developerguide/managedomains-dedicatedmasternodes.html
Instance count | Master node RAM size | Maximum supported shard count | Recommended minimum dedicated master instance type |
|---|---|---|---|
1–10 | 8 GiB | 10K | m5.large.search or m6g.large.search |
11–30 | 16 GiB | 30K | c5.2xlarge.search or c6g.2xlarge.search |
| 31–75 | 32 GiB | 40K | r5.xlarge.search or r6g.xlarge.search |
| 76 – 125 | 64 GiB | 75K | r5.2xlarge.search or r6g.2xlarge.search |
126 – 200 | 128 GiB | 75K | r5.4xlarge.search or r6g.4xlarge.search |
Best Practice in AWS, Elasticsearch
https://www.elastic.co/guide/en/elasticsearch/plugins/current/cloud-aws-best-practices.html
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| Type | AWS Instance Type | Hardware Spec | Num of Instances | Note |
|---|---|---|---|---|
| Collector | c4.xlarge | 4vCPU, 7 GB RAM | ||
| Worker | c4.2xlarge | 8vCPU, 15 GB RAM | 3 | logstash |
| Super | m4.4xlarge | 16vCPU, 64 GB RAM, CMDB Disk 10K IOPS | 1 | kibana |
| Elastic Search Master Node | c3.2xlarge (구세대 인스턴스) | 8vCPU, 16 GB RAM 8 GB JVM 2 x 80GB Instance Store | 1 | |
| Elastic Search Coordinating Node | m5.4xlarge | 16vCPU, 64 GB RAM 30 GB JVM | 1 | |
| Elastic Search Data Node | i3.4xlarge | 16vCPU, 122 GB RAM, 2 x 1900 NVMe SSD 30 GB JVM | 5 | hot, warm |
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