The Situation
The SaaS platform received thousands of alerts each day. Analysts were overwhelmed, triage was slow and real incidents risked being missed among false positives.
What Made The Situation Difficult.
Monitoring had grown tool by tool as the platform scaled to new regions. Identity, endpoint and cloud alerts arrived in separate consoles with no shared context, so analysts had to pivot between screens to understand a single event. Night and weekend coverage depended on an on-call rota that was close to burnout, and response quality varied from shift to shift.
1. Alert overload
Duplicate and low-value alerts buried the signals that mattered.
2. Siloed context
Identity, endpoint and cloud data were never correlated together.
3. Thin coverage
Off-hours response relied on a small and exhausted on-call team.
A phased plan instead of a giant transformation.
Cybevra moved the platform to a managed SOC model in stages. Detection rules were tuned first, signals were correlated into single cases and analysts gained automated enrichment, cutting manual triage time sharply.
01. Consolidate the telemetry
Brought all identity, endpoint and cloud logs into one detection pipeline, giving every alert the user, device and workload context analysts needed to decide quickly whether each new event was real or harmless.
02. Tune detection quality
Removed noisy rules, added behavior-based detections and grouped related alerts into cases so analysts reviewed real incidents instead of raw events, cutting the daily alert volume by more than half within weeks.
03. Automate the first response
Added playbooks that isolate devices, disable risky sessions and open tickets automatically, while 24/7 analysts handled confirmed incidents and shared clear, short summaries with the wider product platform team.
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