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Overview
📖 AWS re:Invent 2025 - FinOps+: A New Era of Accelerating Value (COP211)
In this video, Tatum Tummins, Senior Product Manager at Kion, introduces the FinOps Plus framework consisting of three pillars: automated governance, AI-driven capabilities, and beyond public cloud. Drawing from FinOps Foundation survey data showing priorities like reducing waste and managing costs beyond public cloud, she explains how FinOps Plus addresses modern challenges through policy automation, AI-powered efficiency and governance, and expanding visibility across all technology spend including SaaS and data centers. Real-world examples include using AI to create Cloud Custodian policies and reducing budget update processes from 45 minutes to under five minutes, demonstrating how this approach drives better outcomes while scaling FinOps practices.
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Main Part
Introducing FinOps Plus: A Framework for Modern Cloud Financial Management
Good afternoon, everyone. I'm Tatum Tummins, Senior Product Manager at Kion. If you're not familiar with Kion, we're a FinOps and cloud ops enablement tool focusing on automation and governance. Prior to coming over to the vendor side of the space, I spent over 7.5 years at a large healthcare company doing FinOps. I like to say I grew up in the industry in a lot of ways, and I like to share that because I'm passionate about the subject. I'm passionate about helping people get better in their practice, and that's ultimately why I'm here today to talk about FinOps Plus, an effort that I think will help organizations be more successful.
When we look at what we're going to do today, we're going to start with a quick level set of what the FinOps industry has looked like over the last year. That will lead us into the 30,000 foot macro view of what FinOps Plus is. Then I'll spend a few slides getting into the details of what that looks like in action, some examples, and then we'll end with some next steps and takeaways.
To start, it's important we reflect on what the last year has looked like in the industry. For those of you that are familiar with the FinOps Foundation, every year they do a state of the FinOps survey where they ask folks like you all what your challenges and priorities are. In that survey, at the beginning of this year, folks came back and said they have three main priorities right now: reducing waste and optimizing spend, allocation of cloud spend, and trying to get a little bit better at forecasting.
What I found really interesting is when folks were asked what they will care about over the next 12 months, two new things enter. The first is FinOps governance and policy at scale, and the second was managing costs beyond public cloud. Those two things, along with three developments, are shaping the future of FinOps. The first development is the introduction of scopes. The FinOps Foundation introduced this topic, which essentially outlines the different areas of your technology investment that you can and should practice FinOps on. The second is the common billing schema of focus. Version 1.2 was released, and what we're seeing is that practitioners and vendors alike are starting to adopt that schema or at least start to explore what that would look like.
The last piece, and this should be obvious if you've walked around anywhere this week, is that AI is everywhere, and the FinOps industry is no different. When I looked at that survey data and started to have conversations with prospects and customers, I began to package the areas that folks can start to focus on regarding where FinOps is headed. Earlier this year, I met a gentleman, Matt Coffer from Insulate, who is actually sitting right back there. Matt came to us and said that Insulate is looking for really two things. They want to get better visibility into all of their technology spend. They have all these SaaS tools that they want to start bringing in to have a single pane of glass. Matt also said they need to bring more governance and more policy to their FinOps practice.
I thought about the survey data and what Matt was saying, and I started to put this together. What Matt ultimately said, and you can scan that QR code for a full case study, is that they didn't just need FinOps, they needed FinOps Plus. Like any good product manager, I steal good ideas when I see them, and I decided to call this framework FinOps Plus. Ultimately, it's three pillars: automated governance, AI-driven, and beyond public cloud. In a few slides, we'll show some examples of what these look like in practice, but I want to stay high level for a moment and talk about what FinOps Plus is and is not.
It's a modern approach really focused on doing three things: solving challenges a little bit more proactively, driving efficiency, and enabling smarter decisions. What it's really trying to do is take the things that you all are doing today, the same challenges and processes, and make those more successful right now. But what it's really trying to do is set you all up for success for where FinOps is going over the next 12 to 18 months as it evolves.
When we think about what it's not, it is by no means trying to redefine FinOps. These three pillars are meant to apply to the same processes that you're doing today. It's also not trying to add more work to your plate. If anything, it's trying to do the opposite by leaning on automation and leaning on AI in strategic ways. It starts to give you more time back in your day. And then lastly, it's not just for certain maturity levels. There's going to be some things in the next few slides that for some of you may seem too mature or too far-fetched, but I promise, and I'm confident that there's going to be something within at least one of these pillars that you can start to apply to your practice leaving today.
The Three Pillars of FinOps Plus: Automated Governance, AI-Driven Solutions, and Beyond Public Cloud
Let's talk about what these pillars look like in action. The first we're going to talk about is automated governance. I like to start by defining that with three steps: the first is policy.
Policy becomes automation, and automation becomes guardrails. When I talk about what policy means, I'll share some examples that probably apply to all of you. Policy looks like how you want to define waste or what an orphaned resource looks like at your organization. It looks like what your retention policy is for snapshots or storage. It can be what your lights-off policy looks like for your sandbox and dev environments. What time do you shut those off? Are they off on the weekends? Things of that nature. Another simple example is tagging your resources. Tagging is something every FinOps practice does, and it looks a little different everywhere, but the ability to say these are the key value pairs we look for, and then taking that policy and using whether it's a homegrown solution or a tool like Kion and wrapping that up in automation. When that happens, you start to have guardrails, and those guardrails produce outcomes.
The first outcome looks like preventing waste. A simple example is that waste is going to exist at every organization, but the time it takes for a human to intervene, review those opportunities, and then take action 30 or 60 days later means you've had waste during that time period. So the more that you can cut that off at the very beginning, you reduce that waste, and you also start to reduce manual work because every time a human has to go review an opportunity and then decide if they can take action, that takes away human time and the value that they could be providing your organization.
The last piece is really important. It allows you to scale. So as you scale in the cloud, it gets more and more difficult to keep up with all of these manual opportunities to remediate. By defining policy and putting automation in place, you now start to have a scalable process that as you grow, you can still maintain and try to increase value. The second pillar is AI-driven. This is a fun topic, and I'm sure you're already tired of hearing about AI this week, even on the first day. There's a lot that we could get into here today, and there are some use cases in FinOps that the AI we have today may not be the perfect solution for, but what I am confident about is that in three areas, it's providing real exciting value for folks, and those are guidance, efficiency, and governance.
What I mean by guidance to start is what you see on the screen here is Kion's version of an in-app AI assistant. What I want to draw your attention to is that those are prompts on the screen. Why I think that's so critically important is that the cloud is complex, FinOps can be complex, and when you're starting out and you just don't know where to go, or maybe you're just a stakeholder in procurement, finance, or accounting, and you need to find the data you're looking for, AI provides you a more usable way to find that information. When you click on one of these prompts, it starts to provide you additional questions that you might should be asking yourself or highlighting things for next steps. I think the usability piece of AI is going to go a long way in making FinOps a little bit more of a cultural activity at your organizations and not just something that one or two people know what they're doing.
The second piece, and this is probably the most obvious one, we've all experienced this probably personally and professionally. I use ChatGPT for cooking recipes and proofreading emails, and we've probably all had somewhat of an experience like that. But it's not just getting the information a little bit quicker that I want to highlight here, it's also getting tasks done a little bit faster. A great example is an organization that, when they go to update their budgets on a monthly cycle, that process used to take them about 45 minutes to an hour. Now, using AI, that process takes them less than five minutes, because they have it go out and where they have overruns, where they need to adjust their forecast, and in a single prompt actually has the tool go drive and update to that budget automatically instead of doing that over 50, 100 different projects and cost centers. There's a lot there, and if you're interested in more use cases specifically on efficiency, I'd love to talk after this.
The next one is governance, and this is where I'm most excited about, because what I mean here is not governing your AI spend. That is a piece of FinOps, but that is not what this is. This is actually using AI to govern your cloud. What you see on the screen over here is that I asked if it could create an EBS policy to help clean up my unattached volumes. In this particular use case, it's writing this policy in Cloud Custodian language, for those of you that are familiar with Cloud Custodian. What it's done is without any extra detail from me, it's looking at any unattached volumes for over seven days. It's going to take a snapshot of those, and then it's going to delete those EBS volumes. In one prompt, I now can use a tool to go orchestrate that policy and begin cleaning up EBS volumes, and that's just one example, but when you think about it.
When you think about what I was talking about prior with automated governance, AI and automated governance almost play off each other, and there's a lot of power in this because non-technical users who know what they want to achieve but don't know how to write those policies or even where to begin can now lean on AI to do that for them. If you saw the keynote this morning, AWS announced a policy creator for their AI agents to try to prevent and provide guardrails for that.
What they showed is the same concept of asking AI to make a prompt to govern your AI spend, and we've seen a lot of great success here. I'm really excited for where this part of AI and FinOps is going. Then the third pillar is beyond public cloud. I talked about it a little bit under the key developments, but FinOps is expanding to all technology spend, not just your public cloud. It's the idea of taking the same processes and the same practices that you're doing and applying them across your SaaS tool providers, your data center spend, your licensing spend, or even your generative AI spend.
Why that's important is because once you get that initial visibility, you now have this single pane of glass where you're not only looking at your cloud spend, you're looking at your MongoDB spend, your Databricks spend, all in one dashboard. When you have that visibility, you can start to govern that spend and optimize that spend. The last one is critically important: you now make better business decisions because you're not looking at the cost of what a product or an application costs just in the cloud. You're looking at what that cost is holistically, so you have a total cost of ownership and you start to make better decisions on what your application's profitability is.
To summarize what FinOps Plus is, it's trying to drive better outcomes. It's taking those activities that you're already doing today—your reporting, your budgeting, your optimization— and it's doing those through these three pillars. It's applying automated governance to try to prevent waste before it exists. It's using AI in strategic areas to drive efficiency and help you govern your cloud. It's using beyond public cloud to make better decisions and understand your total tech investment.
What it's ultimately trying to do is take that traditional FinOps and bridge it with operational excellence as you scale and grow in the cloud. For next steps, the first is adopt FinOps Plus, and that's vague on purpose because it's going to mean something different to every single one of you here today. If you want to talk more about your use cases or what you found interesting, I'll be over here to the side and would love to chat more. I'll be at the Kion booth the rest of the week.
My hope is whether it's a SaaS tool that you want to bring into your dashboard or it's an idea for a policy that you really think would save a lot of money if you could just figure out a way to automate it, whatever it may be, identify a next step. I encourage you when you leave here today to take action and try to implement that at your organization. The next thing, and I sincerely mean this, is provide feedback to me. This is practitioner customer-driven content. This is not from my brain; it's from the brain of people like Matt back there, and it gets better and more applicable to you all when I hear your use cases.
If any of you have any sort of disagreement with something I shared today, all of that's valuable in refining this content and making it more usable and accessible to everyone. And then lastly, if you found something here interesting and you want to really do a deep dive on any of those use cases, Kion's booth is just right over here at 1555. I would love to talk about this more, show you how it can impact your organization, or talk through use cases that are specific to you. I know you guys could be anywhere this afternoon. You might be headed to a happy hour or whatever it may be.
I genuinely appreciate you giving me 15 minutes, hearing this content myself, and then I think Matt, you're going to come over there too if anybody wants to ask questions and have further conversations. I really appreciate it and I hope you guys have a great rest of re:Invent.
; This article is entirely auto-generated using Amazon Bedrock.
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