A standard cloud data warehouse is fine until you ask it to run a SOC. Query petabytes continuously, stream telemetry in around the clock, keep a cluster live 24/7. And the cost curve, plus the latency, stops the approach cold. That breaking point is where this Mitiga Mic episode starts, with Brian Contos, Amir Gabrieli, and Yosi Navaro unpacking the blog they co-wrote, "Beyond Standard Data Lakes: Why We Built the Backbone for Zero-Impact SOC."
What is a Zero-Impact SOC?
It's a model that assumes a breach will happen and minimizes its impact by shrinking the time from intrusion to containment to minutes. The constraint isn't detection alone. It's having full-fidelity data available the instant you need it.
Why can't a standard data warehouse run a SOC?
Continuous querying at petabyte scale runs the meter non-stop. To control the bill, most teams quietly drop their most verbose logs, then go looking for exactly those logs the day they're breached. Yosi explains Mitiga's alternative: orchestrate its own compute, with Airflow driving EMR, so the team controls COGS while keeping the data lake at full fidelity. Nothing gets normalized away, and answers still return fast enough to act on.
Why does speed of access matter as much as the artifact?
In a cloud breach the artifact you need usually exists somewhere, but if reaching it takes two hours, the attacker has already moved. Amir's point: full-fidelity data that's immediately available, already correlated, and ready for investigation is what turns hours into minutes — and that speed is the substance of Zero-Impact.
What happens to SIEM and SOAR?
As agentic SOC moves from experiment to operations, the monolithic SIEM and rules-driven SOAR lose their central role, and the quality of the underlying data decides whether AI helps or hallucinates. Feed an agentic SOC partial data and it won't ask for more. It answers anyway. As Amir puts it, data is the plumbing of the SOC: an engineering challenge, not an AI challenge, and one most vendors avoid because solving it doesn't fit their margin.
Watch the full episode above, and read the blog that sparked it here.
