I'm administrating an elastic stack at the moment and my current method right now is closing indexes older than 2 weeks and keeping the last 2 weeks in hot state. If people need to check logs older than 2 weeks they contact me and I just reopen them until they're finished. There is a considerable amount of daha flow to the stack and if I don't do reguler cleaning/closing I mostly get request timeouts from kibana. Is it better to change the older logs' states to warm/cold rather than closing? Will I notice a performance boost while querying?
If you are already getting request timeouts when searching hot/warm data, then that might indicate your cluster is already under stress. Are you aware that when you reopen a closed index it is reindexing based on the documents? See the docs on closed indices.
Have you considered using frozen indices instead of closing? It would allow occasional requests on-demand, without your intervention.
Have you read the guide on tuning for search speed?
Thanks for the valuable info @wylie .
I was wondering something else since I can't seem to find solid numbers anywhere. I think that my shard load can be downsized making logical groups for different indices via logstash.conf. For example let's say i have 100 different indices created each day with 1p and 1r shards and i make groups that include 3 indices each. Each group has its own identified ports and indexnames etc.
This will roughly make 33 logstash instances or 33 pipelines (again this is only a mock scenario). I will start to get a third of my shard load which will increase overall kibana/elasticsearch performance i suppose.
But will it cause logstash to consume much more memory or cpu?
I'm a Kibana developer, so I might not be able to help as much as an expert on those particular parts of the stack- feel free to ask again in the other parts of the forum. What I can point you to are some things that commonly cause performance issues:
- Having either too many or too few shards
- Not using ILM to automate the shard sizing
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