ScaleOps Labs Ltd., creator of a fully automated, cloud-native resource orchestration platform for Kubernetes deployments, said today it has closed on a hefty $58 million Series B round of funding, just 11 months after finalizing its Series A round.

High-profile Silicon Valley-based investor Lightspeed Venture Partners led the latest round, which saw participation from existing backers NFX and Glilot Capital Partners, plus a new investor, Picture Capital. It brings ScaleOps’ total amount raised to $80 million, the company said.

ScaleOps is the creator of a cloud resource management platform that can help enterprises to achieve substantial cost savings of up to 80% on their Kubernetes application deployments.

Kubernetes is an open-source container orchestration tool that’s used to power the vast majority of modern, cloud-based applications in use today. It’s used to manage the hundreds or even thousands of containers that host the modular components of these apps, and enables developers to update them on a continuous basis, ensuring they can add new functionality almost as fast as they can innovate. However, while Kubernetes is designed to scale DevOps, it struggles to scale itself up.

Kubernetes configuration woes

According to ScaleOps, Kubernetes’ scalability problems are related to the complex and tedious process of managing Kubernetes environments. The problem is that the Kubernetes configurations that detail aspects such as container sizing and scaling thresholds are largely static, whereas consumption and demand is more dynamic, as it fluctuates in real-time.

The static nature of Kubernetes configurations forces engineering teams to adjust the cloud resources consumed by each application manually, in order to avoid under- or over-provisioning the resources they consume. This can be a troublesome, delicate balancing act, because their apps will experience performance issues if they have too few resources, and ballooning costs if the resources devoted to it are more than it needs.

Considering that many organizations are running hundreds, if not thousands of applications at once, the infrastructure costs can escalate by thousands of dollars per hour if engineering teams don’t keep a watchful eye on their resource consumption patterns.

Engineers can do this manually, but they end up spending countless hours trying to monitor and predict demand, tweaking configuration files and so on. And as their applications scale, teams can quickly become so overwhelmed that they have no time to do anything else.

Automation to the rescue

ScaleOps provides engineering teams with a much better way to handle resource management, automating the process with AI. Using its platform, they have a way to run Kubernetes workloads and manage their configurations on autopilot, automatically adjusting the settings based on demand.

The software ensures that each app always has the optimal level of resources available, so they can run without performance problems, while keeping a lid on costs. The software is versatile, and can be integrated with cloud platforms like Amazon Web Services, Microsoft Azure and Google Cloud, as well as on-premises application environments.

ScaleOps said today it has seen rapid growth of its platform over the last year, as more companies come to realize the benefits its configuration automation software provides. New customers added since its previous funding round include Fortune 100 firms such as Wiz Inc., Cato Networks Inc. and SentinelOne Inc.

“We realized that no one in the market was solving the problem; they were just providing visibility and bringing awareness to it. The process of resource allocation was still completely broken,” said ScaleOps co-founder and Chief Executive Yodar Shafrir. “The only way to solve the problem was to provide a solution that would seamlessly automate cloud resource management in real-time.”

New features accelerate cost savings

Alongside the new funding, ScaleOps is boosting its platform with two new capabilities, including artificial intelligence-powered predictive scaling in real-time, and intelligent pod placement. Together, these new features can deliver up to 50% additional cloud cost savings while boosting application performance, the company said.

The AI-powered predictive scaling feature is designed to predict application loads in real time and scale the resources made available to the pods that support them, so they have just the right amount. Meanwhile, the intelligent pod placement feature helps to further optimize resource allocation by taking into consideration application constraints and cluster status. By doing this, it can optimize the number of active nodes needed by each application.

Lightspeed Venture Partners’ David Gussarsky said he sees ScaleOps as the clear category leader in terms of cloud resource management, tackling one of the most critical challenges in cloud-native application environments. “With organizations facing pressure to control cloud costs while also improving performance, ScaleOps’ automation is a breakthrough, and their rapid growth this past year underscores the critical need they are fulfilling in the market,” he said.

Image: ScaleOps