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StormForge Channel Partner Program Launched

StormForge announced its Channel Partner Program.

The StormForge Channel Partner Program focuses on providing distributors, resellers and other partners with the most effective resources to put the StormForge machine learning-based optimization platform within every enterprise’s reach. The Channel Partner Program complements the StormForge Cloud Provider Alliance Partner Program.

“The Kubernetes developer and user communities are incredibly large and diverse – and they’re growing rapidly. So it’s natural for us to design a Channel Partner program that extends the reach of StormForge’s patent-pending machine learning technology to as many enterprises as possible,” said Amy Medeiros, Head of Marketing, StormForge. “StormForge optimizes Kubernetes at scale in ways that no other solution can. We want to help as many customers as possible achieve success with their Kubernetes journey, and that means arming our partners with game-changing solutions that make that process as smooth and effective as possible. The Partner Program keeps customer relationships front and center, while also offering a simple, collaborative, and rewarding experience for our partners.”

The StormForge Partner Program consists of solutions, training including hands-on certification and tools that enable its partners to offer customers the most effective platform for optimizing Kubernetes at scale. Partners gain access to an exclusive partner portal, deal registration, integrated campaign kits, sales tools, technical training support, sales incentives and a dedicated StormForge Certified Kubernetes expert.

StormForge’s flagship product, StormForge Optimize Live, delivers ML-powered Kubernetes resource optimization through analysis of observability data, intelligent recommendations, and automated action based on that analysis. The ML focus goes beyond cost or performance alone, optimizing both at any scale to enable intelligent business decisions with minimal trade-offs. Just last month, the platform added bi-dimensional Kubernetes pod autoscaling, which minimizes cloud waste during the autoscaling process without sacrificing application performance. This powerful platform puts the best possible offerings in the hands of partners and resellers, whose customers need flexibility across cloud environments and the ability to optimize in production and non-production environments.

Purpose-built for Kubernetes, StormForge runs in any CNCF-certified distribution and integrates easily with existing Kubernetes environments, including all Kubernetes cloud services, management platforms and observability solutions. It also enables fast time-to-value with one-click deployment and continuous, automated Kubernetes resource optimization.

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StormForge Channel Partner Program Launched

StormForge announced its Channel Partner Program.

The StormForge Channel Partner Program focuses on providing distributors, resellers and other partners with the most effective resources to put the StormForge machine learning-based optimization platform within every enterprise’s reach. The Channel Partner Program complements the StormForge Cloud Provider Alliance Partner Program.

“The Kubernetes developer and user communities are incredibly large and diverse – and they’re growing rapidly. So it’s natural for us to design a Channel Partner program that extends the reach of StormForge’s patent-pending machine learning technology to as many enterprises as possible,” said Amy Medeiros, Head of Marketing, StormForge. “StormForge optimizes Kubernetes at scale in ways that no other solution can. We want to help as many customers as possible achieve success with their Kubernetes journey, and that means arming our partners with game-changing solutions that make that process as smooth and effective as possible. The Partner Program keeps customer relationships front and center, while also offering a simple, collaborative, and rewarding experience for our partners.”

The StormForge Partner Program consists of solutions, training including hands-on certification and tools that enable its partners to offer customers the most effective platform for optimizing Kubernetes at scale. Partners gain access to an exclusive partner portal, deal registration, integrated campaign kits, sales tools, technical training support, sales incentives and a dedicated StormForge Certified Kubernetes expert.

StormForge’s flagship product, StormForge Optimize Live, delivers ML-powered Kubernetes resource optimization through analysis of observability data, intelligent recommendations, and automated action based on that analysis. The ML focus goes beyond cost or performance alone, optimizing both at any scale to enable intelligent business decisions with minimal trade-offs. Just last month, the platform added bi-dimensional Kubernetes pod autoscaling, which minimizes cloud waste during the autoscaling process without sacrificing application performance. This powerful platform puts the best possible offerings in the hands of partners and resellers, whose customers need flexibility across cloud environments and the ability to optimize in production and non-production environments.

Purpose-built for Kubernetes, StormForge runs in any CNCF-certified distribution and integrates easily with existing Kubernetes environments, including all Kubernetes cloud services, management platforms and observability solutions. It also enables fast time-to-value with one-click deployment and continuous, automated Kubernetes resource optimization.

The Latest

For many B2B and B2C enterprise brands, technology isn't a core strength. Relying on overly complex architectures (like those that follow a pure MACH doctrine) has been flagged by industry leaders as a source of operational slowdown, creating bottlenecks that limit agility in volatile market conditions ...

FinOps champions crucial cross-departmental collaboration, uniting business, finance, technology and engineering leaders to demystify cloud expenses. Yet, too often, critical cost issues are softened into mere "recommendations" or "insights" — easy to ignore. But what if we adopted security's battle-tested strategy and reframed these as the urgent risks they truly are, demanding immediate action? ...

Two in three IT professionals now cite growing complexity as their top challenge — an urgent signal that the modernization curve may be getting too steep, according to the Rising to the Challenge survey from Checkmk ...

While IT leaders are becoming more comfortable and adept at balancing workloads across on-premises, colocation data centers and the public cloud, there's a key component missing: connectivity, according to the 2025 State of the Data Center Report from CoreSite ...

A perfect storm is brewing in cybersecurity — certificate lifespans shrinking to just 47 days while quantum computing threatens today's encryption. Organizations must embrace ephemeral trust and crypto-agility to survive this dual challenge ...

In MEAN TIME TO INSIGHT Episode 14, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses hybrid multi-cloud network observability... 

While companies adopt AI at a record pace, they also face the challenge of finding a smart and scalable way to manage its rapidly growing costs. This requires balancing the massive possibilities inherent in AI with the need to control cloud costs, aim for long-term profitability and optimize spending ...

Telecommunications is expanding at an unprecedented pace ... But progress brings complexity. As WanAware's 2025 Telecom Observability Benchmark Report reveals, many operators are discovering that modernization requires more than physical build outs and CapEx — it also demands the tools and insights to manage, secure, and optimize this fast-growing infrastructure in real time ...

As businesses increasingly rely on high-performance applications to deliver seamless user experiences, the demand for fast, reliable, and scalable data storage systems has never been greater. Redis — an open-source, in-memory data structure store — has emerged as a popular choice for use cases ranging from caching to real-time analytics. But with great performance comes the need for vigilant monitoring ...

Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...