The Ancient Art of SIEM: Why 2003 Problems Look So Familiar in 2026
Lately, Iβve been reading a lot of insightful posts related to best practices in SIEM, detection, and logs (written in 2026). The interesting bit is that a lot of these best practices looked good to me and made senseβββand yet, they felt incredibly familiarβ¦
As I dug deeper, I realized they reminded me of things I had written 10, or sometimes even 20 (23 in one case) yearsΒ ago.

What does this mean? I hope you donβt take this post as something written purely to prove that Iβm very smart and totally prescient (I am smart / I am not prescient). No, the actual lesson here is that things changed much less at many organizations than peopleΒ assume.
So, letβs review some of the older wisdom from the mid-2000s and early 2010s and match it up against what people report as todayβs best practices.
#1 Centralization
Letβs start with pure comedy. In 2003, I recommended that peopleΒ β¦ wait for itβ¦ centralize security data (funny enough, in 2023, I briefly questioned this idea). But on a more serious note, this is stillβββmostlyβββgood advice, with some notable exceptions [A.C.βββlook at that emdash sucker there, gotΒ it?].

#2 Context
I am surprised about it myself, but back in 2003 I was a big fan of adding what later became known as context data into a SIEM. Asset info, vulnerability scans, etc need to go into your SIEM (well, SIM and SEM at the time; SIEM was born inΒ 2005).

#3 Planning
Since the day I first laid my eyes on a SIEM in January 2002 (well, technically, it was a SIM), I realized that project planning makes or breaks a SIEM deployment. 20+ years did NOT teach many this lesson, as modern advice, sadly, is the same. Generic advice? Sure, but also evergreen!

#4 Buy vsΒ DIY
You may think because I worked for vendors, I was always a fan of βbuy from a vendorβ as a default choice, and only resort to βbuildβ or βbuy then buildβ as an exception.No, I saw too many DIY SIEM disasters. Here we confirm that despite major changes in tooling (AI agents), for most organizations build vs buy decision remained largely the same, forΒ now.

(a fun ancient exception: a certain βI-suspect-whoβ had to analyze 300TB (~ 1 trillion messages) of logs in 2005, and advice they were given is: DIY, nothing commercial can handle itΒ β¦ and as we learned later wonβt for another 5β7 years atΒ least)
#5 Output-driven SIEM
The idea of βOutput-driven SIEMβ was stolen by me in 2011 and then popularized widely my Gartner βmegaphone.β I did a refresh on this in 2025, but, in brief, it means βdeploying your SIEM in such a way that NOTHING comes into your SIEM unless and until you know how it would be utilized and/or presented.β This is very relevant today, because in the past it was hardware and not perhaps it means tokens. But βSIEM costs killβ messageΒ remains.
#6 CrownΒ Jewels
Sometime around 2013, I was giving many clients this advice: do NOT start your security monitoring (really, D&R) scope from the most important assets, or crown jewels. Many a CISO argued hard (βbut Anton, what about βimportant first.ββ Yes, SAP is important but if you onboard SAP logs before firewall logs, you will probably die in the process. And step 2 will never happen. Modern advice seems to match perfectly.
#7 Retention
βKeep logs. If you donβt know better, keep logs for a year.β I said around 2006β2008. Then in 2019, I got somewhat shocked that keeping logs for a year is seen as a luxury by many. Today with data lakes and all sorts of crazy cloud storage peopleΒ β¦ wellβ¦ often still donβt keep logs longΒ enough.

#8 SIEM vs Log Management
SIEM vs LM was a hot topic in the mid-2000s. We had architectured for broad collection in LM and security focused subset in a SIEM. Today this just means SIEM and a data lake. So, this also aged veryΒ well.
#9 Log Data Mining akaΒ UEBA
A lot of my early work in what I called βlog data miningβ predated UEBA, and my predictions that rules will be complemented by analytics (hi Captain Obvious!) aged weirdly. They agend well, then not well, then well again. Today we have non-deterministic AI analyzing logs, and back then we had Marcus Ranum βNBSβ for Never BeforeΒ Seenβ¦.
#10 Misc
In my consulting days (pre-Gartner, which means pre-2011), I did a lot of βbest / worst practicesβ presentations, such as this one. I think these aged well, but perhaps because they were a bit generic. Example that aged very wellΒ include:
- βPhased Approach: Rather than feeding βallβ logs into a SIEM immediately, organizations should start with limited devices (e.g., DMZ) and events (e.g., authentication)β thenΒ expand.
- βFocus on Use Cases: SIEM requirements should be driven by specific problems the organization wants to solve, such as tracking unauthorized access or detecting web application hacking.β
- βTuning Ability: The organization must accept responsibility for customizing and tuning the tool, as βout-of-the-boxβ SIEM deployments rarely succeed.β
All of the above are from the early to mid 2000s. These also aged well, despite being almost ΒΌ of a centuryΒ oldβ¦
Lessons? So what does it mean that advice from 2003 still works in 2026? A few uncomfortable lessons:
- SIEM problems were never technology problems. They wereβββand are, and perhaps will beβββpeople, process, and organizational physics problems wearing a technology costume. This is why 23-year-old advice still applies: the vendors shipped new tech, but nobody shipped new organizations.
- The βwhatβ aged well; the βhowβ got replaced. Output-driven collection, phasing, use cases, context, tuning ownershipβββall still true. What changed is the plumbing: appliances became data lakes, EPS became tokens, correlation rules got a non-deterministic AI sidekick. If your strategy changes every time the plumbing changes, you never had a strategy. Good news!?Β Yes!
- Cost pain is eternal; only the currency changes. In 2003 you ran out of hardware, in 2015 you ran out of ingest budget, in 2026 you run out of tokens. βSIEM costs killβ is apparently a law of nature, so architect for it (output-driven!) rather than being surprised by it.Β Again.
- If the advice didnβt change, but you still donβt follow it, the advice was never the problem. Everyone βknowsβ to plan the deployment, start with use cases, and own the tuning. Knowing isnβt the bottleneck. Doing is. AI wonβt fix that eitherβββit will just help you not-do itΒ faster.
- The industry has a roughly 7-year memory. Every cycle, βnewβ best practices get rediscoveredβββat $xxx/hour consulting ratesβββby people who could have read my 2005 SlideShare for free. Reading old stuff is the cheapest security investment youβll make thisΒ year?
So no, Iβm not prescient. The organizations are just slow (as I said after leaving Gartner: βIT inertia is the most powerful force in the Universeβ). We had 23 years of progress, and the best practice is still βhave a plan and donβt ingest garbage.β See you in 2043, when this post ages wellΒ tooβ¦
Related posts:
- 20 Years of SIEM: Celebrating My Dubious Anniversary
- 20 Years of SIEM Webinar Q&A andΒ slides
- Security Correlation Then and Now: A Sad Truth AboutΒ SIEM
- Stop Building a 2003 SOC with AI: Triage Must Die (PartΒ 2)
- Stop Building a 2003 SOC with AI: A Modern People & Process Framework (PartΒ 1)
- A Fair Weather SOC: 5 Signs Itβs Time to Panic (and FixΒ It!)
- WTH is Modern SOC, Part 1 (There is no part 2.Β Yet?)
- Beware: Clown-grade SOCs StillΒ Abound
- The Return of the Baby ASO: Why SOCs StillΒ Suck?
The Ancient Art of SIEM: Why 2003 Problems Look So Familiar in 2026 was originally published in Anton on Security on Medium, where people are continuing the conversation by highlighting and responding to this story.
