Komodor expands Kubernetes platform with real-time cost optimization tools

Komodor Ltd. today unveiled new cost optimization capabilities to its Kubernetes management platform that allow organizations to reduce cloud spend while maintaining performance and reliability across their entire Kubernetes estate.

Kubernetes is an open-source orchestration platform for containers, which contain microservices, the components of modern applications — something of an operating systems for clusters of computers running applications.

Komodor’s new features assist with Kubernetes workloads that grow in size and complexity, driving up cloud spend at the same time, along with engineering teams that regularly overprovision infrastructure “just in case,” resulting in idle resource waste. Komodor argues that while this happens, mission-critical workloads can’t be evicted, limiting autoscaler efficiency, but optimizing for cost alone often leads to misconfigured workloads, scaling failures or reduced application reliability.

The platform’s new enhancements are designed to extend and augment real-time workload right-sizing, to deliver up to 40% to 60% in additional savings, without compromising stability or speed.

“In large-scale Kubernetes environments, cutting costs without visibility into application behavior is a recipe for downtime,” explains Itiel Shwartz, co-founder and chief technology officer of Komodor. “What organizations need is a way to optimize cost and performance — across the full scope of infrastructure and application operations. That’s what we’ve built.”

Komodor’s new cost optimization features are designed to move teams away from static resource planning and toward dynamic, real-time optimization. The platform now offers visibility into cloud, hybrid and on-premises environments, with drill-down filters by cluster, service and namespace. The result helps teams better understand where resources are going and make smarter, more accountable decisions.

The platform introduces intelligent workload right-sizing based on real usage patterns. Komodor recommends the appropriate resources to prevent both waste and underperformance by analyzing processor, memory, throttling and scheduling signals.

Additional new features such as advanced bin-packing and pod placement enhancements help resolve common blockers like pod disruption budgets and affinity rules to improve node utilization and reduce fragmentation. A new Autopilot mode also allows for continuous optimization with built-in safety guardrails. Teams can choose from conservative to aggressive profiles, while smart headroom management ensures spare capacity is available when needed without overprovisioning.

Komodor is a venture capital-backed startup that has raised $72 million over three rounds, including rounds of $21 million in June 2021 and $42 million in May 2022. Investors in the company include Tiger Global Management, Accel Partners LP, Felicis Ventures Management Co., NFX Guild, Oldslip Group, Pitango Venture Capital Ltd. and Vine Ventures.

Image: Komodor

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