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As cloud adoption and hybrid infrastructure expansion have become the operational norm, teams need a way to preserve context across the full environment rather than investigating network, infrastructure, and cloud issues in separate silos. While the hybrid path has become mission-critical, correlation across that path was never built into monitoring architecture.
The resulting complexity and dependencies on domain-specific tools make finding root causes harder and outages last longer, thereby increasing operational burden on enterprises. For enterprises migrating to hybrid environments, this visibility gap is no longer just inconvenient; it is costly.
Unlike tools that treat cloud and network observability as separate domains, the Selector solution is built around the end-to-end operational path. Its differentiation starts with how data is ingested, enriched, and correlated from the point of collection onward. Selector’s patented data ingestion model harmonizes the data across different domains while preserving context across cloud, network, and infrastructure telemetry.
Selector AI and ML engines work on this harmonized data to correlate disparate signals from across domains, identify what changed, determine where an issue started, and explain how far the impact extends.
The new capabilities include:
“Modern infrastructure is hybrid by default, but most operations workflows remain fragmented,” said Nitin Kumar, CTO at Selector. “Selector’s solution brings cloud into the same operational model as network observability, giving teams one correlated view across the hybrid path, so they can see the full context, reduce noise, and get to the true root cause faster.”
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