SCNET · Enterprise IT · Ankara, Türkiye
AIOps is the layer that turns the alert flood from monitoring tools into meaningful incidents. Sanal Çekirdek builds it with correlation rules and measured outcomes rather than as a black box.
Automation does not organize a disorganized operation; it accelerates it. Incident flow first, automation second.
One server outage produces alerts from dozens of systems. Correlation gathers them into a single incident and separates cause from consequence. The goal is fewer decisions, not fewer alerts.
A component failure cannot be prioritized without knowing which business service it affects. A service map translates a technical event into business impact; the same server failure can be critical for one service and immaterial for another.
For recurring events with known outcomes, first response is automated: restarting a service, clearing disk space, adding capacity. Every automation carries a boundary and a way back.
Automated response closes the symptom, not the cause. Recurring events go into a separate queue and are routed to a durable fix; otherwise automation becomes a curtain that hides the problem.
Usually not. The AIOps layer sits above existing tools and consumes the alerts they produce; replacing a tool only arises where data quality is insufficient.
Decisions stay with rules rather than the model. The model proposes correlation and patterns; where automated response runs is set by a written boundary, and every run leaves a record.
Noise reduction usually shows first because it works on data you already have. Service mapping and automation take longer, in proportion to how mature the inventory is.
Share a week of alert history; we will show the noise ratio and the correlation potential in numbers.
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