Autonomous cloud resource management for Kubernetes and AI workloads
ScaleOps builds automation for cloud infrastructure, targeting waste reduction and cost efficiency in production Kubernetes environments. The stack—Kubernetes, Prometheus, Grafana, Istio, plus emerging AI tools (LangGraph, PydanticAI)—reveals infrastructure-first engineering focused on observability and real-time optimization. Sales-heavy hiring (22 roles) against smaller engineering (10) signals a GTM-driven growth phase, while pain-point clustering around manual resource allocation and DevOps-to-application-owner friction points directly at their core value: removing friction from cloud operations.
Notable leadership hires: Tech Lead, Sales Director
ScaleOps operates a platform for autonomous cloud resource management, built on Kubernetes and designed for organizations running production workloads across AWS, GCP, and Azure. Founded in 2022 and based in New York, the company operates as a 51–200-person team serving infrastructure and DevOps-focused buyers. The product surface spans real-time resource optimization, cost reduction, and application-aware automation. The organization is structured around sales (largest department), engineering, marketing, and product, with active hiring across the US, UK, Israel, Brazil, and India.
Core: Kubernetes, Prometheus, Grafana, Istio, Helm. Languages: Go, Python, TypeScript, React. Cloud: AWS EKS, Azure Kubernetes Service, GCP. Emerging: LangGraph, PydanticAI. Sales/ops: HubSpot, Salesforce, Jira, Confluence.
Kubernetes resource management platform, core product UI components, AI-driven content creation, and new sales channels. Active focus on product launch, partner enablement, and analyst relations.
ScaleOps's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.