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Reaction: Their latest Gartner placement. Does it match your experience?

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(@data_skeptic_ray)
Honorable Member
Joined: 6 months ago
Posts: 429
Topic starter   [#6338]

So Elastic is riding high in that quadrant again. Color me skeptical.

I’ve read the usual summary. "Visionary" gets thrown around a lot. But when I peel back the vendor slides and look at what it takes to operationalize their security suite day-to-day, I see a different picture. The gap between a well-tuned, performant Elastic stack for security and the out-of-the-box promise feels wider than they'd admit.

My team ran a head-to-head on detection logic development time and resource consumption for a standard MITRE technique. Their query language is powerful, but "powerful" often translates to "easy to write expensive queries that bring a data node to its knees." The reproducibility of alerts across different deployments? Let's just say it's highly dependent on your normalization pipeline, which is far from trivial.

Does their placement match *your* experience? Specifically:
- Have you found their detection content to be robust without significant in-house tuning?
- How does the total cost of ownership, considering the data engineering needed for reliable alerting, compare to more integrated platforms?
- Is anyone actually using their built-in SOAR capabilities beyond simple webhooks, or is it just a checkbox feature?

Gartner's criteria are one thing. The reality of making it work, without a small army of Elastic-certified engineers, is another. I'm curious if the market success they're being credited with aligns with practical, sustainable deployments, or if it's still mostly a tool for shops that were already all-in on the ELK stack for other reasons.


Data skeptic, not a data cynic.


   
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(@juliam)
Trusted Member
Joined: 3 months ago
Posts: 36
 

Totally feel that. We tried adopting their prebuilt detection rules last year. The concept is great, but we spent weeks tuning them to match our environment's specific log format. The "out-of-the-box promise" was a lot of noise for us, too.

Your point about expensive queries is spot on. We had to learn the hard way about resource usage. It made me wonder if the TCO in engineering hours ever makes it cheaper than a platform with less flexibility but more guardrails.

Are you using any custom scripts to manage that normalization pipeline, or is it all manual mapping?



   
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