jordansissel
Joined 17 years ago
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13
Member since
Dec 8
Recent submissions
Comment · 13 years ago
Comment · 13 years ago
With logstash, I aim to make it as easy to deploy as possible. That is, in part, why the releases are self-contained jar files with all depenencies built-in (except for java itself). We also started working on shipping rpm/deb packages with recent releases.
Like I always say, if it's hard to use or appears to have major flaws or pains, it's a bug, and we can fix it. Let us know! :)
Comment · 13 years ago
I think it was roughly 300 million events/day (1kb per event). There is some overhead incurred by logstash (turning a log into json, parsing it into fields) and by elasticsearch (analyzing/indexing data).
In practical terms, and by way of example, a plain text apache access log, fully parsed by logstash (breaking out fields, etc), has historically bloated by quite a bit (6.2x I have measured). Lately, however, with improvements to logstash, better default settings, and elasticsearch being awesome, the 'inflation' number gets down to something more like 1.5x - which isn't bad considering all the awesome you get with it.
Long term, I am working towards making the 'raw data to stored data' ratio something less than 1x.
You can see some experiments I did a year ago on this: https://github.com/jordansissel/experiments/blob/master/elas...
I will repeat these experiments after the next release of logstash, and I expect storage ratios to improve significantly.
Comment · 13 years ago
At my last job (prior to joining elasticsearch), I had a cluster of 7 machines (16 cores, 16gb ram, 2TB raid1), each running logstash and elasticsearch.
The event rate going into this cluster was about 5000 events/sec on average (burst up to 10,000 events/sec sometimes).
During a maintenance (two machines going offline for disk repairs), I benchmarked the surviving 5-node cluster at 88,000 events/sec peak performance.
In terms of capacity planning, this means that we could have a 9x increase in normal event load and still not need to grow the cluster's processing capacity.
Persistent storage is another story. We stored about 300GB/day of events, getting us roughly 45 days of data retention before we would run out of space (2TB * 7 nodes / 300gb/day; roughly 45 days). I'm working on improving storage efficiency of logstash and elasticsearch, too, so retention should improve greatly in the long term.
For other experiences, it's useful to invoke the community and ask what others are done - the #logstash irc channel on freenode is very active as is the [email protected] mailling list.
Hope this helps!
Comment · 13 years ago
I don't know what bottlenecks you had when were observing high resource usage in logstash, but, in general, if there's a performance problem, it is a bug, and we can fix it.
The next release of logstash (1.2.0 is in beta) has a 3.5x improvement in event throughput. For numbers: on my workstation at home (6 vcpu on virtualbox, host OS windows, 8gb ram, host cpu is FX-8150) - with logstash 1.1.13, I can process roughly 31,000 events/sec parsing apache logs. With logstash 1.2.0.beta1, I can process 102,000 events/sec.
Processing speed will vary greatly by what you are doing with your events and it doesn't make sense to generalize performance characteristics globally, especially with a metric that, alone, doesn't really tell me much (cpu utilization).
If it's slow, it's a bug. We can fix it. :)
Further, you can use hekad with logstash and with elasticsearch (one or both together, it doesn't matter).
In terms of problems solved, logstash helps solve transport and real-time processing problems. In cases where the logstash agent is too resource intensive, the logstash community offers many alternatives on this site: http://cookbook.logstash.net/recipes/log-shippers/
The community (myself included) is very interested in helping logstash be a success for its users, so if you do see performance problems, things that behave weirdly, or anything strange, it's probably a bug, and we can fix it.
The short version of all of this is captured by the project principles listed in the logstash readme: https://github.com/logstash/logstash/#project-principles
<3
Comment · 16 years ago
logstash doesn't currently support saved queries (if you mean letting you save queries you like for later, easy recall), but I'm open to all feature suggestions.
File a request, or email the list: - http://code.google.com/p/logstash/issues/list - [email protected]
I'll know what to work on (besides my own priorities) based on requests/feedback :)
As mentioned in another comment in this post, I was doing 300gigs of data per day with an elasticsearch cluster size of 7 elasticsearch nodes (16 cores & 16gb ram per node) and load was around 5-10% cpu utilization.
100MB/day is pretty small in terms of log data, I think. If you attempt this again, please invoke the community (elasticsearch's is great!) and see if we can assist you in figuring out what's busted.