When it comes to how much data you can hold on a node it often comes down to how well you manage heap usage, as this is likely to be the limiting factor. It can therefore vary from use-case to use case.
With a 15GB heap I think you are unlikely to get to 10TB, which means that you either end up with smaller or fewer shards.
A good rule-of-thumb is to ensure you keep the number of shards per node below 20 to 25 per GB heap it has configured
So 15GB Heap size multiplied by minimum of 20 shards means I can have minimum 300 shards in a node with 30GB RAM
Aim to keep the average shard size between a few GB and a few tens of GB. For use-cases with time-based data, it is common to see shards between 20GB and 40GB in size
If I use the minimum 20GB per shard multiplied by minimum number of 300 shards gives be 6TB of minimum.
It is not a minimum, it is a range for a maximum. The most common problem we see is that users end up having far too many small shards, which is why we have provided a recommendation around the maximum number of shards you should have. If you are using large shards you are likely to be below this recommended maximum number of shards per node.
A good rule-of-thumb is to ensure you keep the number of shards per node below 20 to 25 per GB heap it has configured
So 25 is maximum. That means 375 shards
Aim to keep the average shard size between a few GB and a few tens of GB. For use-cases with time-based data, it is common to see shards between 20GB and 40GB in size
40GB is maximum. So 375*40 = 15000 = 14.6TB Disk space is maximum
The large number of small shards you have, which brings down the average size, will consume resources and affect cluster performance. I would recommend reducing and/or consolidating these, e.g. by changing the number of primary shards, consolidating indices and/or switching to weekly or monthly indices instead of daily.
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