ScaleOps’ cover photo
ScaleOps

ScaleOps

Software Development

New York, NY 18,323 followers

Autonomous cloud & AI resource management. Built for production. Trusted by the world's leading companies.

About us

ScaleOps is redefining cloud resource management from the ground up. Led by a team of cloud infrastructure experts and built for critical production environments, ScaleOps is on a mission to build the Cloud Operating System for the AI era, one that unlocks efficiency and scale while maximizing performance in critical and complex production environments. By bringing real-time, application context-aware automation to cloud resource management, the ScaleOps platform helps organizations eliminate waste, reduce costs, and run critical applications with confidence across any environment.

Website
https://www.scaleops.com
Industry
Software Development
Company size
51-200 employees
Headquarters
New York, NY
Type
Privately Held
Founded
2022
Specialties
Kubernetes, Cloud Infrastructure, Resource Optimization, Cost Reduction, DevOps, FinOps, Continuous Optimization , and Cost Optimization

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Updates

  • 🎬 Armis, now part of ServiceNow, runs one of the most demanding production environments in cybersecurity. Multiple clusters, stale configs, and a team that can't slow down to babysit resource tuning when enterprises depend on them to stay secure. For a company whose business is keeping critical infrastructure secure, trusting a platform to manage production autonomously is a high bar. Here's what happened when they cleared it, and what it did to their cluster performance, utilization, and costs. "Manually tuning has essentially disappeared from our workflow. Developers can now focus on what matters most: building the product. Now it's all handled autonomously." – Lior Ran, Staff Infrastructure Engineer, Armis

  • 🚀 ScaleOps took over Miami for SKO 2026. We spent a week together, the entire a-team, every timezone in one room, building the future. The world deployed AI everywhere, almost overnight. But the platform and infra teams now running it are stuck - more agents, more models, more clusters, all on infrastructure that was never built for this. ScaleOps was built for exactly this moment. The autonomous layer that keeps enterprise AI infrastructure running. This is just the beginning - and we’re hiring across all roles and functions. If you want to be in that room next year, we want to hear from you. 🔗 https://lnkd.in/dn7nqvzh

  • View organization page for ScaleOps

    18,323 followers

    🎥 Island runs one of the most demanding Kubernetes environments in enterprise infrastructure. Thousands of critical production workloads. Multiple regions. A platform that scaled 4-5x in the last year with zero tolerance for latency or downtime. And a team that doesn't have the time to focus on tuning and babysitting resource configs. Here's what they did instead, and what happened to their performance and cloud costs. "ScaleOps delivered for us in ways that we proudly deliver for our customers. More efficient, simpler infrastructure, flawless performance." - Omri Cohen, Director of Engineering, Island

  • SKO 2026. Miami. 🏝️ The whole team is here, and these are exactly the people you want together in a room to build the future of AI infrastructure management. The world shifted to AI almost overnight. The infrastructure underneath didn't. Every enterprise is running more agents, more models, more workloads. All on infrastructure that was never built for this scale. ScaleOps was built for this moment. The autonomous layer powering the apps, agents, and models that the world's leading enterprises run. No manual tuning. No waste. No engineers babysitting clusters. We're just getting started. Let's yalla. 🚀

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  • ScaleOps has been named to Redpoint's 2026 InfraRed 100, alongside the companies defining the next decade of infrastructure and AI. Thank you to Redpoint Ventures, to our customers, and to the ScaleOps team building the autonomous cloud and AI infrastructure resource management platform every day. We're just getting started. 🚀

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  • The Kubernetes scheduler has one job: filter, score, bind. It doesn't provision Nodes. It doesn't consolidate workloads. It doesn't rightsize requests. It doesn't revisit its own decisions. This is why your cluster sits at 30–40% utilization while Cluster Autoscaler or Karpenter refuses to scale down. Nothing is broken. The layered system is missing the piece that actually packs the cluster. Nicolas Vermandé breaks down how the scheduler really works, why LeastAllocated quietly costs you money, and where the scheduler's job ends and Cluster Autoscaler and Karpenter's begins. Read more 🔗 https://lnkd.in/ebZRqgQb

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