Disclaimer: I'm a founder at Gravwell, a log analytics startup
I agree, even when applicable LLMs are relegated to analyzing subselected data, so logs have to go somewhere else first. I think understanding logs is brain intensive because it can be a tricky problem. It gets easier with good tools, but often those tools are the kind that need to be used to build something else that solves the problem, rather than solve the problem themselves (e.g. building a good query + automation). I think LLMs can get better at creating the queries which would help a lot.
We started Gravwell to try bring some magic. It's a schema-on-read time-series data lake that will eat text or binary and comes in SaaS or self-hosted (on-prem). We built our backend from scratch to offer maximum flexibility in query. The search syntax looks like a linux command line, and kinda behaves like one too. Chain modules together to extract, filter, aggregate, enrich, etc. Automation system included. If you like Splunk, you should check us out.
There's a free community edition (personal or commercial use) for 2GB/day anon or 14GB/day w/ email. Tech docs are open at docs.gravwell.io.
Hey snisarenko, you could use the Gravwell Community Edition which is free up to 2GB/day. 4GB/day if you participate in the current alpha testing program. https://www.gravwell.io/download
Disclaimer: I'm one of the founders. We built it to be a Splunk alternative and I think it does a great job from a data ingest, scalability, and data querying perspective. We're lacking some of the out-of-the-box capability, but not for long. Kits (our "apps") release is coming this quarter.
I agree, even when applicable LLMs are relegated to analyzing subselected data, so logs have to go somewhere else first. I think understanding logs is brain intensive because it can be a tricky problem. It gets easier with good tools, but often those tools are the kind that need to be used to build something else that solves the problem, rather than solve the problem themselves (e.g. building a good query + automation). I think LLMs can get better at creating the queries which would help a lot.
We started Gravwell to try bring some magic. It's a schema-on-read time-series data lake that will eat text or binary and comes in SaaS or self-hosted (on-prem). We built our backend from scratch to offer maximum flexibility in query. The search syntax looks like a linux command line, and kinda behaves like one too. Chain modules together to extract, filter, aggregate, enrich, etc. Automation system included. If you like Splunk, you should check us out.
There's a free community edition (personal or commercial use) for 2GB/day anon or 14GB/day w/ email. Tech docs are open at docs.gravwell.io.