I get a fair number of crashes of the latter which I have always assumed is because of bugs and the java runtime and that one of the advantages I might enjoy with filebeat is that it is written in Go and perhaps has better memory management, fewer leaks, and better architecture.
So I am searching for reasons as to how best to justify filebeat over logstash for a large installation.
I'll refine that question: DOES FILEBEAT CRASH AS MUCH AS LOGSTASH? The issue is that LOGSTASH 2.x crashes heavily here with a very plain, vanilla setup and I have CM restarting it regularly and want to get out from under the scenario above. FILEBEAT, if more stable, would be such a solution. Does anyone out there have filebeat running on a large number of servers and will they comment about the relative rate of their crashes of the filebeat client? Assume the clients are connecting to a logstash server rather than directly to elasticsearch.
Well, that's fresh out of the box, without any special rules or transformations, just collecting a bunch of logs and sending them off to an Elasticsearch cluster.
try:
response = rs.client_list()
print "redis server is up"
except redis.ConnectionError:
print "woops, redis server is down"
scracraft@devops1:~$ ./redis-tester.py
redis server is up
scracraft@devops1:~$
maybe this explains why the redis error messages stopped and we got the sincedb entries (sincedb is keeping track of file state). Is redis running stable? Regarding logstash maybe you're better of asking on logstash forum.
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