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> (and I've seen this trend a lot) any idea why? Seems like an odd approach to me.
by detaro 5y ago
> (and I've seen this trend a lot)
any idea why? Seems like an odd approach to me.
- denysvitali 5y agoBecause people like to have everything (logs + metrics) in the same place. And probably Beats makes it easier to just ship everything in Elasticsearch (but of course this doesn't make it good)
- atombender 5y agoBecause that's what Elastic is positioning Elasticsearch for. If you look at the features being added these last few years, so much is about time series stuff — aggregation, time-based partitioning, warm/cold storage, etc. Relatively little focus on structured search.
- moduspol 5y agoI was interviewing earlier this year and saw at least three companies actively planning to migrate from their existing relational databases into Elasticsearch. It seems to commonly be perceived as a panacea of databases.
- alkz 5y agoin most cases elastic is easier to scale than a relational or timeseries db
- moduspol 5y agoI mean, kind of? It depends on what your data looks like and how you're querying it. If you're not doing free-text search, and your data will fit in memory in a big relational database VM for the foreseeable future, why Elasticsearch?
- alkz 5y agosure relational db is ok if fits in memory, but if we're talking about TBs of metrics i'd rather look for another way
- closeparen 5y agoWhen I see a nonzero value in a metric about “things that shouldn’t happen,” the very next thing I’m going to ask for is examples. It’s generally considered too expensive to derive metrics from logs in this way, but it’d be a killer debugging experience.