This issue exists to the right of your solution and is (for now) out of scope, but the biggest issue I have with security data lakes is the need to (easily) get both row-based data and visualizations. Back when I had access to a well-built and cared for Splunk environment, I would constantly run queries, build visualizations, go back to the results index, tweak the query, go back to viz, etc. This feedback loop is important and allows for fast iteration, especially if you are conducting a high-stakes investigation and need answers rapidly. I should be able to look at my available fields and tweak the viz accordingly in under a few seconds; preferably in one mouse click.

Now I live on an ELK stack and I experience nothing but full-time agony as I switch between Kibana and Kibana Lens constantly. It's clear they are two completely separate "products" built for different use-cases. The experience reminds you constantly that they were not purpose-built for how I use them, unlike Splunk.

Increasingly we are moving towards the reality of a security data lake, and all I can think is that I'm about to lose what little power I had left as I have to move to something like Mode, Sisense, or Tableau which again, were not purpose-built for these use-cases and even further separate the query/data discovery and visualization layers.

I hate how crufty and slow Splunk has gotten as an organization, and they use their accomplishments from 15 years ago to justify the exorbitant price they charge. I really hope the OSS/next-gen SaaS options can fill this need and security data lake becomes a reality. But for that to happen, more focus is needed on the user experience as well.

Regardless, very cool stuff and could definitely fill a need for organizations that are just starting to dip toes into security data lakes. I wish you success!

I loaded the GitHub link, bracing myself for yet another AGPL license, but no, it's Apache 2! So I wanted to say thank you for that and I hope to take a deeper look when I'm back at my desk because trying to keep Splunk alive and happy is a monster pain point. There are so many data sources we'd love to throw at it but we don't have the emotional energy to put up with Splunk crying about it
Interesting project.

A few remarks though.

- Doing real time data processing on tera/peta bytes involves a lot of IO, which is a significant part of of the cost in AWS. Things like Athena are simply not cheap to run at that scale.

- With time series data, the emphasis is usually on querying recent data, not all of the data. You retain older data for auditing for some time. But this can essentially be cold storage.

- Especially alerting related querying is effectively against recent data only. There's no good reason for this to be slow.

- People tend to scale Elasticsearch for the whole data set instead of just recent data. However, with suitable data stream and index life cycle management policies, you can contain the cost quite effectively.

- Elastic Common Schema is nice but also adds a lot of verbosity to your data, and queries. Bloating individual log entries to a KB or more. Parquet is a nice option for sparsely populated column oriented data of course. Probably the online disk storage is not massively different from a well tuned elastic index.

- Elastic and Opensearch have both announced stateless as a their next goal. So, architecturally similar to this and easier to scale horizontally.

- SIEM is just one use case. What about APM, log analytics, and other time series data? Security events usually involve looking at all of that.

Excited to give this a try and follow your progress!

In case anybody else is wondering how Matano compares to Panther (my first thought reading this launch post) there's a comparison on the Matano website[0].

Quick note to the Matano team, the "Elastic Common Schema (ECS)" link in the readme[1] seems to be broken.



Hi Shaeq and Samrose - congrats on the launch! Matano looks great.

Out of curiosity, at some point I believe you were working on a predecessor called AppTrail whic tackled (customer-facing) audit logs, it was something I was interested in at the time (and still am! I would've loved to use that).

Would you perhaps be willing to share your learnings from that product, and (I assume) why it evolved into Matano?

Oh, this very much has my attention. I'll be checking this out in depth.
How do you position this against AWS's own Security Lake announced at re:Invent in November ( ?

Your architecture diagram looks like a carbon copy of theirs.

What distinguishes a SIEM from traditional log analysis? I know the feature set is oriented towards SIEM but it seems like a super set of regular log analysis. I don't have a need for a SIEM now but this looks good even for non security logs.
I'm a vendor in the cyberspace so not a potential customer (feel free not to waste time answering) but am just intellectually curious who you're targeting this at. High-skill tech companies who are just building up a security program? I don't see most security teams building their own SIEM'ish solution just because they really don't have the chops or resource to do it. OTOH, it would be a big rip-out operation for F100 companies to change to this from Splunk et al.
I have been exploring this realm of SIEM, XDR, NDR etc. Sure, all proprietary SIEMs are expensive. But what is not clear is how you are going to price it. Security teams have dedicated budget. If you are coming cheaper than them, they you are destroying your TAM because I know customer would not mind paying those license fees. OSS GTM might work but might against your TAM.
What distinguishes Matano'd existing or planned products from Google Chronicle? Would you have any limits on data ingestion or retention?

Also, python detections sounds horrible! I love python but it sounds like you haven't considered the challenges of detection engineering. This one of my main "expertise" if you will. You should think more in the lines of flexible sql than python. People who write detection rules to the most part don't know python and even if they do it would be a nightmare to use for many reasons.

I hope someone from your team reads this comment: DO NOT try to invent your own query language but if you do, DON'T start from scratch. Your product could be the best people who like the fabulous splunk need to also like it. And for a security data lake, you must support Sigma rule conversion into your query/rule format. Python is a general purpose language, there are very good reasons why no one else from Splunk,elastic, graylog, Google,Microsoft use Python. Don't learn this hard lesson with your own money. Querying it needs to be very simple and most importantly you need to support regex with capture groups and the equivalent of "|stats" command from splunk if you want to quickly capture market share. I have used and evaluated many of these tools and have written a lot of detection content.

Your users are not coders, DB admins or exploit developers. They are really smart people whose focus is understand threat actors and responding to incidents -- not coding or anything sophisticated. FAANG background founders/devs have a hard time grasping this reality.

This is awesome. Nice work open-sourcing it! I used Splunk at Expedia and it was super expensive and slow. While I wasn't using it for security purposes, it could take 15-30 min for us to detect error logs, and I can imagine that's not okay for security purposes. Good luck guys!
Question to Matano authors - won't your solution simply enrich AWS by blowing up my cloud bill ?

Did you estimate how many times lambda will get invoked and what will be AWS bill for 1 million events ingested? I am curious to learn the price to pay for serverless SIEM

Anyone aware of a similar solution for Google Cloud / GCP?
Shaeq and Samrose: for us investors here, where are you in terms of fundraising? I'm an ex AWS (google me, you'll have a few laughs!), turned VC in the past few years. $HN_username at gmail if you want to reach out and chat!

Edit: here's me with Andy, from a millenium ago [0].


Super random question... I wonder if the name is related to Frank Matano, the italian youtuber/comedian.