I am using logstash-2.3.1 and es-2.3.2. The hosts are in the same datacenter, but different vlans, from 10.10.20.0/255.255.255.0 to 10.10.22.0/255.255.255.0.
The Logstash host have 16G memory and 16 cores AMD 6128, but the free memory is about only 3G.
I'm not clear with the es cluster's hardware. But there are many other logs writing to es, it is the cluster operation engineer told me that my log write-in speed was much slower than others.
I would recommend upgrading to Logstash 2.4 and try increasing the number of elasticsearch output workers to 4 (the same number as your number of worker threads).
If you do not have access to the Elasticsearch cluster to measure throughput, you can try introducing the metrics filter and write this to e.g. a file using conditionals.
$ ping 10.10.22.13
PING 10.10.22.13 (10.10.22.13) 56(84) bytes of data.
64 bytes from 10.10.22.13: icmp_seq=1 ttl=63 time=0.133 ms
64 bytes from 10.10.22.13: icmp_seq=2 ttl=63 time=0.104 ms
64 bytes from 10.10.22.13: icmp_seq=3 ttl=63 time=0.123 ms
64 bytes from 10.10.22.13: icmp_seq=4 ttl=63 time=0.107 ms
64 bytes from 10.10.22.13: icmp_seq=5 ttl=63 time=0.099 ms
64 bytes from 10.10.22.13: icmp_seq=6 ttl=63 time=0.232 ms
64 bytes from 10.10.22.13: icmp_seq=7 ttl=63 time=0.121 ms
64 bytes from 10.10.22.13: icmp_seq=8 ttl=63 time=0.201 ms
64 bytes from 10.10.22.13: icmp_seq=9 ttl=63 time=0.100 ms
64 bytes from 10.10.22.13: icmp_seq=10 ttl=63 time=0.105 ms
64 bytes from 10.10.22.13: icmp_seq=11 ttl=63 time=0.324 ms
And the cluster op engineer have told me the es cluster's average rate is 8000/sec
I believe the metrics shown are number of documents processed per second measured over a period of 1 minute, not documents per minute. Based on the information you have provided it would seem it is possible that Elasticsearch is the bottleneck. The fact that it is processing 8000 events/second does not necessarily mean it has any spare capacity to process additional events.
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