Selector AI Presents at Cloud Field Day 26

Multi-Cloud Observability with Selector

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In this Cloud Field Day 26 session, Reza Koohrangpour, head of product marketing at Selector, introduced the company and framed the problem it aims to solve in bringing cloud and network operations together. He explained that Selector’s founders previously led switching and routing at Juniper and that the team combines networking and AI expertise drawn from companies such as Juniper, Cisco, VMware, Google, and Nutanix. He described Selector as a networking team that built an AI platform, rather than an observability company that later discovered networking. The company has roughly 125 employees, shipped its first product in 2021, and counts Fortune 1000 organizations as about 75 percent of its customers, most of whom use it for tool consolidation, alert noise reduction, and automated incident remediation.

Koohrangpour argued that the core challenge in hybrid cloud observability is not a shortage of data but a lack of shared context. Large enterprises often run around 100 separate dashboards across network, infrastructure, application, and cloud domains, and each tool shows only its own slice of the environment. When an incident triggers tens of thousands of alerts, those alerts arrive without any connection to one another, leaving operators to correlate them manually. As a result, teams spend hours just identifying what the problem is and who owns it before any fix begins. He attributed this to the vertical pipeline design common in most tools, where metrics, logs, events, configurations, and CMDB data each have their own collector, store, and view, forcing someone to reconstruct context after the fact during high-pressure incidents.

Selector’s answer is a horizontal architecture that organizes processing by stage rather than by data type, moving from collection to normalization, then correlation and root cause analysis, and finally explainable output for the operator. The key differentiator, Koohrangpour stressed, is that every record delivered to an operator already carries topology, ownership, and maintenance context, because Selector attaches context as data moves in rather than reconstructing it as data moves out. He summarized the offering as three layers that build on one another: full-stack observability that brings cross-domain data into a single pane of glass, a shared correlation and causation layer that produces root cause insights, and Selector Foundry, an agentic runtime launched the day before the presentation that uses AI agents to investigate issues and take action.

Personnel: Reza Koohrangpour