Discover how Kubernetes is evolving to support AI/ML workloads in this interview with John Platt, CTO at StormForge (now part of CloudBolt) on KubeFM’s podcast series.

This episode will cover:

• Notable new Kubernetes tools, such as in-place pod resizing for smoother workload rightsizing, EKS Auto Mode to streamline node management, and NOS for simplifying GPU virtualization.
• The growing adoption of Kubernetes as the preferred platform for AI/ML workloads, delivering substantial cost savings (up to 90%) over managed services like OpenAI, along with enhanced scalability and flexibility.
• Key obstacles to running AI on Kubernetes, including managing GPU drivers, ensuring CUDA version compatibility, and accommodating very large models that may exceed tens of gigabytes.
   

Hear from Craig Hinkley, CEO of CloudBolt, and John Platt, CTO of StormForge, on how combining CloudBolt’s award-winning FinOps platform with StormForge’s machine learning technology addresses one of the most significant pain points for enterprises today.

As Kubernetes adoption accelerates, organizations face mounting challenges with cost management, resource utilization, and performance optimization. According to recent research by the Cloud Native Computing Foundation (CNCF), Kubernetes has driven up cloud spend for 49% of organizations, with 70% citing overspend directly related to workload overprovisioning.

CloudBolt’s acquisition of StormForge brings together two complementary technologies to create a comprehensive solution that addresses these challenges head-on. This solution brief explores how this integrated platform closes the FinOps loop for Kubernetes, enabling businesses to inform, optimize, and operate with unprecedented efficiency.

Automation has become essential to keeping up with today’s fast-paced cloud environment. Manual FinOps processes create bottlenecks, delay decisions, and limit your team’s ability to drive true business value. But moving from manual workflows to full automation requires a strategic approach.

Watch this exclusive webinar where CloudBolt experts William Norton, Kyle Campos, and Ryan Wrenn will walk you through a framework for scaling FinOps automation maturity. This session will cover the five core pillars of automation, guiding you through practical steps to build an automation strategy that can scale with your cloud needs.

What You Will Gain:

1. A Framework for FinOps Automation Maturity: Discover the five essential pillars of automation maturity—from process integration to value creation—and understand how they drive efficiency and scalability in FinOps.
2. Actionable Steps for Each Maturity Stage: Get practical recommendations for moving from Crawl to Walk to Run across each pillar. Learn actionable steps to overcome common obstacles and accelerate automation maturity within your team.
3. Insights on Reducing Manual Processes: Explore real-world strategies for eliminating time-consuming manual tasks, enhancing collaboration, and making FinOps operations more agile and data-driven.
4. Metrics that Matter: Learn which KPIs and metrics are essential for measuring the success of your automation efforts and understanding their impact on business outcomes.

As a FinOps leader, you’re likely seeing the mad dash toward AI across industries—from automating workflows to cutting operational costs, AI is being pursued at full throttle. But while AI’s potential is undeniable, diving in without a readiness strategy can lead to costly missteps and missed opportunities.

In fact, a recent McKinsey survey found that only about 10% of companies realized significant returns on their AI investments in 2024, underscoring the importance of a thoughtful approach. That’s why we created the Ready to Run: A Guide to Assessing AI Readiness for FinOps ebook—to help your FinOps team set the stage for meaningful, lasting impact. This comprehensive resource provides actionable insights, assessment tools, and a structured framework for building a clear, strategic roadmap to AI success.

Building a Foundation: The Three Readiness Categories for AI

To achieve successful AI adoption in FinOps, it’s crucial to first assess your FinOps practice’s readiness across three readiness categories: Value, Data, and Operational Readiness. We get into much more detail in our Ready to Run ebook, but here’s an overview of each category as well as some sample questions (the full assessment framework is available for download):

Value Readiness: AI investments must align closely with your strategic goals. This means clearly defining the purpose behind your AI initiatives and identifying the specific areas where AI can create measurable impact. Teams that establish this “why” are far more likely to see meaningful returns on their investment.

Sample questions:

• Have we clearly defined the problems AI will solve and their potential impact on our business?
• Are there specific outcomes or KPIs we aim to achieve with AI in FinOps?
• Does AI offer advantages over simpler, non-AI solutions for our current challenges?

Data Readiness: AI is only as effective as the data fueling it. High-quality, accessible, and consistent data is essential for producing reliable insights and predictions. Assessing your data’s readiness is a key step toward ensuring your AI initiatives can operate smoothly and produce actionable outcomes.

Sample Questions:

• Do we have access to all necessary data sources, and are they consistent and reliable?
• Is our data clean, organized, and normalized across sources?
• Do we have sufficient historical data to train AI models effectively and generate meaningful insights?

Operational Readiness: Even the best AI models need a supportive operational environment. This includes having the right team skill sets, infrastructure, and processes in place to manage AI effectively. Operational readiness equips your FinOps team to scale and sustain AI-driven practices over time.

Sample Questions:

• Does our team have the AI/ML expertise required to oversee these initiatives?
• Are our technical environments, like development and testing, ready to support AI workloads?
• Do we have a clear plan for maintenance, support, and training to ensure long-term success?

Ready to Run: A Guide to Assessing AI Readiness for FinOps

AI is the next evolution in cloud cost management—don’t let your organization fall behind.

Get the ebook

What Comes After Your AI Readiness Assessment?

Once you’ve completed a full AI readiness assessment, you’ll have a clear picture of where your FinOps team stands. So, what’s next? Well, there are a few options you can take, depending on your results. 

If your team is fully ready: Congratulations—your team has a solid foundation for AI adoption! This means you have every confidence to present your business case to stakeholders in the organization.

If you identify gaps in readiness: You may feel overwhelmed by what you’re missing, but rest assured, there are still ways to move forward with what you have. Depending on the gaps, consider the following steps:

• For Value gaps: Revisit your AI goals and clarify the specific problems AI will address within FinOps. Consider engaging stakeholders to ensure alignment with organizational priorities and define success metrics that justify the investment.
• For Data gaps: Focus on enhancing data quality, consistency, and accessibility. This could mean normalizing data across platforms or implementing data governance practices to support reliable insights.
• For Operational gaps: Invest in skills development or consider building a dedicated AI team or Center of Excellence (CoE) to centralize expertise and best practices. Preparing your operational environment now will pay off as AI initiatives scale.

There’s also one more thing you can do to overcome your technical hurdles:

• Partner with third-party vendors: Instead of tackling every issue individually, consider working with a vendor that has already developed AI solutions tailored to FinOps needs. Partnering with experienced providers allows you to skip the line, significantly decreasing time-to-value and gaining immediate access to best-in-class expertise. This approach can accelerate scalability and ensure that your team can focus on strategic goals rather than technical hurdles.

Your Path to AI-Driven FinOps Success

Assessing AI readiness is a crucial first step for any FinOps team aiming to unlock the potential of more intelligent, data-driven operations. 

Whether it’s aligning AI with strategic goals, preparing data for reliable insights, or building a supportive operational environment, setting up these foundations can make all the difference.

If you’re ready to make AI a cornerstone of your cloud management strategy, our Ready to Run: A Guide to Assessing AI Readiness for FinOps ebook provides a complete framework to assess readiness, make informed decisions, and set your team up for AI success.

Download the Ready to Run ebook today and start your FinOps AI journey with confidence!

In a landscape where IT budgets are barely outpacing inflation, CIOs and CFOs are under immense pressure to deliver more with less. Join CIO Dive and CFO Dive for an exclusive webinar, where we’ll explore how cutting-edge AI and automation technologies can underpin FinOps practices and accelerate results. Discover how forward-thinking organizations are adopting automation and AI for FinOps delivery to overcome technology talent shortages and budget constraints and ultimately meet the expected value from their enterprise’s technology investments.

Key Topics Include:

1. The Evolution of FinOps: Discover how FinOps has progressed from basic cost visibility to a strategic driver of cloud ROI. We’ll explore the limitations of traditional approaches and introduce the game-changing potential of Augmented FinOps.
2. Closing the “Insight to Action” Gap: Learn how CloudBolt’s innovative Augmented FinOps platform leverages AI/ML-informed insights and intelligent automation to streamline cloud lifecycle optimization. We’ll showcase real-world examples of how organizations are placing value at the center of every cloud decision.
3. The Power of a Unified Cloud Fabric: Explore how treating diverse cloud resources as a single fabric can simplify management, enhance visibility, and drive better decision-making across public and private cloud environments.
4. Automation and AI: The Future of FinOps: Dive into how proactive and reactive intelligent automation is revolutionizing cloud cost management, from workload placement to continuous optimization.

Join Kyle Campos (CTO), and Ryan Wrenn (VP of AI/ML), as they recap what they saw and heard and FinOps X Europe 2024.

Earlier this year we promised a new way of approaching FinOps, and today we deliver on that promise. Hear from Craig Hinkley, CEO of CloudBolt, as he discusses the new CloudBolt Platform and how it is the bedrock of the vision for Augmented FinOps we set out in January.