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IBM Acquires Kubecost

IBM announced the acquisition of Kubecost, a Kubernetes cost monitoring and optimization software company.

With this acquisition, IBM is showcasing its commitment to the growth of FinOps, both by setting the pace for innovation, as well as strategically bringing leading technologies together. The addition of Kubecost to IBM’s FinOps solutions deepens our commitment to FinOps teams, DevOps teams, and the open-source community as a whole.

Following IBM’s recent acquisition of Apptio in 2023, the addition of Kubecost adds best-in-class container cost management to the IBM FinOps Suite. IBM’s FinOps suite combines IBM Cloudability’s FinOps capabilities and IBM Turbonomic’s AI-automated cloud performance optimization integrations in one solution to give teams the ability to inform, optimize and operate cloud investments regardless of where their workloads are hosted. In fact, IBM Cloudability was recently named a leader in the report, The Forrester Wave™: Cloud Cost Management and Optimization, Q3 2024. The need to combine Kubernetes and cloud cost monitoring, financial business insights and cloud optimization into a comprehensive solution can benefit practitioners wherever they are in their journey.

Kubecost delivers real-time cost visibility and insights needed to not only understand infrastructure spend, but intelligently reduce spend and avoid over-provisioning within Kubernetes environments. With direct integrations into the Kubernetes and cloud billing APIs, FinOps teams can get a comprehensive view of their workloads to optimize cloud spend and prevent resource-based outages. This deeper view into Kubernetes workload optimization becomes easier with Kubecost.

Today's announcement is another example of IBM strengthening its automation portfolio through a mix of organic innovation like IBM Concert and strategic acquisitions like Apptio, Turbonomic, Instana, NS1 and Pliant – all which help organizations reduce complexity and increase control of organizations’ IT environments.

Founded in 2019, Kubecost is based in San Francisco, CA and is led by Co-founder & CEO, Webb Brown and Co-founder & CTO, Ajay Tripathy.

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IBM Acquires Kubecost

IBM announced the acquisition of Kubecost, a Kubernetes cost monitoring and optimization software company.

With this acquisition, IBM is showcasing its commitment to the growth of FinOps, both by setting the pace for innovation, as well as strategically bringing leading technologies together. The addition of Kubecost to IBM’s FinOps solutions deepens our commitment to FinOps teams, DevOps teams, and the open-source community as a whole.

Following IBM’s recent acquisition of Apptio in 2023, the addition of Kubecost adds best-in-class container cost management to the IBM FinOps Suite. IBM’s FinOps suite combines IBM Cloudability’s FinOps capabilities and IBM Turbonomic’s AI-automated cloud performance optimization integrations in one solution to give teams the ability to inform, optimize and operate cloud investments regardless of where their workloads are hosted. In fact, IBM Cloudability was recently named a leader in the report, The Forrester Wave™: Cloud Cost Management and Optimization, Q3 2024. The need to combine Kubernetes and cloud cost monitoring, financial business insights and cloud optimization into a comprehensive solution can benefit practitioners wherever they are in their journey.

Kubecost delivers real-time cost visibility and insights needed to not only understand infrastructure spend, but intelligently reduce spend and avoid over-provisioning within Kubernetes environments. With direct integrations into the Kubernetes and cloud billing APIs, FinOps teams can get a comprehensive view of their workloads to optimize cloud spend and prevent resource-based outages. This deeper view into Kubernetes workload optimization becomes easier with Kubecost.

Today's announcement is another example of IBM strengthening its automation portfolio through a mix of organic innovation like IBM Concert and strategic acquisitions like Apptio, Turbonomic, Instana, NS1 and Pliant – all which help organizations reduce complexity and increase control of organizations’ IT environments.

Founded in 2019, Kubecost is based in San Francisco, CA and is led by Co-founder & CEO, Webb Brown and Co-founder & CTO, Ajay Tripathy.

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64% of enterprise networking teams use internally developed software or scripts for network automation, but 61% of those teams spend six or more hours per week debugging and maintaining them, according to From Scripts to Platforms: Why Homegrown Tools Dominate Network Automation and How Vendors Can Help, my latest EMA report ...

Cloud computing has transformed how we build and scale software, but it has also quietly introduced one of the most persistent challenges in modern IT: cost visibility and control ... So why, after more than a decade of cloud adoption, are cloud costs still spiraling out of control? The answer lies not in tooling but in culture ...

CEOs are committed to advancing AI solutions across their organization even as they face challenges from accelerating technology adoption, according to the IBM CEO Study. The survey revealed that executive respondents expect the growth rate of AI investments to more than double in the next two years, and 61% confirm they are actively adopting AI agents today and preparing to implement them at scale ...

Image
IBM

 

A major architectural shift is underway across enterprise networks, according to a new global study from Cisco. As AI assistants, agents, and data-driven workloads reshape how work gets done, they're creating faster, more dynamic, more latency-sensitive, and more complex network traffic. Combined with the ubiquity of connected devices, 24/7 uptime demands, and intensifying security threats, these shifts are driving infrastructure to adapt and evolve ...

Image
Cisco

The development of banking apps was supposed to provide users with convenience, control and piece of mind. However, for thousands of Halifax customers recently, a major mobile outage caused the exact opposite, leaving customers unable to check balances, or pay bills, sparking widespread frustration. This wasn't an isolated incident ... So why are these failures still happening? ...

Cyber threats are growing more sophisticated every day, and at their forefront are zero-day vulnerabilities. These elusive security gaps are exploited before a fix becomes available, making them among the most dangerous threats in today's digital landscape ... This guide will explore what these vulnerabilities are, how they work, why they pose such a significant threat, and how modern organizations can stay protected ...

The prevention of data center outages continues to be a strategic priority for data center owners and operators. Infrastructure equipment has improved, but the complexity of modern architectures and evolving external threats presents new risks that operators must actively manage, according to the Data Center Outage Analysis 2025 from Uptime Institute ...

As observability engineers, we navigate a sea of telemetry daily. We instrument our applications, configure collectors, and build dashboards, all in pursuit of understanding our complex distributed systems. Yet, amidst this flood of data, a critical question often remains unspoken, or at best, answered by gut feeling: "Is our telemetry actually good?" ... We're inviting you to participate in shaping a foundational element for better observability: the Instrumentation Score ...

We're inching ever closer toward a long-held goal: technology infrastructure that is so automated that it can protect itself. But as IT leaders aggressively employ automation across our enterprises, we need to continuously reassess what AI is ready to manage autonomously and what can not yet be trusted to algorithms ...

Much like a traditional factory turns raw materials into finished products, the AI factory turns vast datasets into actionable business outcomes through advanced models, inferences, and automation. From the earliest data inputs to the final token output, this process must be reliable, repeatable, and scalable. That requires industrializing the way AI is developed, deployed, and managed ...