Advertise on podcast: FinOps in Action

This week's episode of FinOps in Action takes a different shape, with PointFive Co-Founder and Chief Product Officer Gal Ben-David stepping in to host a conversation with Mike Graff, Infrastructure Architecture Director at Dolby Laboratories and a FinOps Ambassador. Mike shares a couple of real cost inefficiencies he's tracked down in the wild, then the conversation opens up into bigger questions about where FinOps is headed from new roles emerging on the engineering side to how AI might change the way teams find and fix waste. It's a grounded, practitioner led episode for anyone trying to close the gap between what engineering builds and what finance sees on the bill.   Here’s what we talked about: Small misconfigurations can hide big costs. A couple of the "craziest" inefficiencies Mike's found weren't exotic, they were simple settings almost anyone could miss, and easy to fix once spotted.Platform tools don't always keep pace with the cloud. Vendors can lag behind what cloud providers already support, and Mike argues teams shouldn't just accept those gaps.Cost optimization and security fight the same uphill battle. Both compete for engineering attention against feature deadlines and both benefit from getting into the conversation earlier.The FinOps role may be split in two. Mike and Gal dig into whether cost efficiency is becoming its own engineering discipline, separate from the finance side of FinOps.You don't need a title to start. Many practitioners begin as a side project, start small, find one win, and let momentum build.Chapters: 00:00 Vendor Security Rant 00:15 Special Episode Setup 01:25 Meet Mike Graff 02:18 Databricks Egress Surprise 05:14 Finding It in Dashboards 06:06 NAT Gateway Routing Trap 08:11 Tooling Gaps and Visibility 10:21 PaaS Transparency and Governance 13:56 Shifting Left With Engineers 22:10 Performance vs Cost Wins 23:30 Gamifying FinOps Scores 24:23 Unit Economics Challenges 25:21 AI for FinOps Tools 26:50 FinOps Agent Vision 27:50 Platform Engineering Link 31:24 Cloud Efficiency Engineer Role 36:25 Getting Started in FinOps 40:16 Community Wrap and Takeaways  🎧 Subscribe for more FinOps leadership conversations → https://www.finopsinaction.com/  Quote of the Show:"It all starts somewhere. It starts with poking into that data transfer dashboard and figuring out what's going on. Just get those wins, chipping away at the low hanging fruit.” - Michael Graff Links: LinkedIn: https://www.linkedin.com/in/michaelegraff/ Website: https://www.dolby.com/ Ways to Tune In: Amazon Music: https://music.amazon.com/podcasts/f25a9d18-c12f-4ee4-93f5-2aa96e509b55 Apple Podcasts: https://podcasts.apple.com/us/podcast/finops-in-action/id1790497808 iHeart Radio: https://iheart.com/podcast/268443483/ Podchaser: https://www.podchaser.com/podcasts/finops-in-action-5958339 Spotify: https://open.spotify.com/show/3IpjMc3qxDXZAjic5Zq21t Substack: https://finopsinaction.substack.com/ Transistor: finopsinaction.com YouTube: https://www.youtube.com/@PointFive_Inc

This episode of FinOps in Action pulls together voices from across the industry, including Pathik Sharma of Google Cloud, Emily Cornock, Kevin Mueller, Zach Johnson, Henrique, Shailaja Beeram, Marit Hughes, and Oliver Milke, all wrestling with the same question: how do you actually manage the cost of AI. Two years ago the idea of "AI for FinOps" got brushed off as premature. Now it sits in the top three priorities in the FinOps Foundation's own survey data, and for good reason. The guests dig into why AI spend is accelerating faster than cloud ever did, why most companies still cannot prove ROI on it, and what it actually looks like to build guardrails without slowing teams down. It is a rapid fire look at where FinOps practice is headed as AI stops being a side experiment and starts becoming the biggest line item on the P&L. Here’s what we talked about: Treat your AI investment like a science experiment. Control your variables, change one thing at a time, and always tie spend back to a measurable business outcome, not just a feeling that things are getting more productive.Token cost is only the tip of the iceberg. Storage, the adaptive storage layer, GPU and TPU compute, and platform hosting all add up, so don't let your team optimize the visible 20% while ignoring the rest.Not all AI actions carry the same risk, so treat them differently. Let AI handle low stakes, non disruptive work like cost allocation labeling on its own, but keep a human in the loop for anything disruptive, like rightsizing a Kubernetes workload during Black Friday.Don't let analysis paralysis become your default setting. Make your best reasonable estimate on AI spend, document your assumptions, and move forward instead of letting fear triple your forecasts.Shift FinOps further left than you think you need to. Get engineering and product involved in AI cost conversations early, because the goal is not command and control, it's giving teams the data to make good decisions themselves.Chapters: 00:00 Welcome to FinOps 00:18 AI Meets FinOps 01:12 Spend Growth Shock 01:40 Tech Pace Explosion 02:28 Making AI Serious 02:52 FinOps DNA for AI 03:29 ROI Reality Check 04:26 Experiment With Controls 05:06 Claims AI Success Story 06:49 Unit Economics Mindset 07:37 Measure Value and Impact 09:27 Enable Not Control 10:19 Link Tools to Outcomes 11:04 Orchestrators Change Costs 11:48 Guardrails and Fact Checks 13:12 Copilot Dashboards to Agents 14:20 Safe Automation Actions 17:16 Managing AI Spend Layers  🎧 Subscribe for more FinOps leadership conversations → https://www.finopsinaction.com/  Quote of the Show: "Think about AI as that eager intern. It can do the work, but you also need to trust, verify, and wait for the manager to give you a nod." – Pathik SharmaConnect with the Guest’s: Emily Cornock: https://www.linkedin.com/in/emilycornock/ Oliver Milke: https://www.linkedin.com/in/oliver-milke/ Kevin Mueller: https://www.linkedin.com/in/kevinmueller/ Marit Hughes: https://www.linkedin.com/in/marit-hughes/ Shailaja Beeram: https://www.linkedin.com/in/shailaja-beeram-82324310a/ Pathik Sharma: https://www.linkedin.com/in/pathik-sharma/ Zach Johnson: https://www.linkedin.com/in/realzachjohnson/ Henrique Amorim: https://www.linkedin.com/in/henriqueamorim/ Ways to Tune In: Amazon Music: https://music.amazon.com/podcasts/f25a9d18-c12f-4ee4-93f5-2aa96e509b55 Apple Podcasts: https://podcasts.apple.com/us/podcast/finops-in-action/id1790497808 iHeart Radio: https://iheart.com/podcast/268443483/ Podchaser: https://www.podchaser.com/podcasts/finops-in-action-5958339 Spotify: https://open.spotify.com/show/3IpjMc3qxDXZAjic5Zq21t Substack: https://finopsinaction.substack.com/ Transistor: finopsinaction.com YouTube: https://www.youtube.com/@PointFive_Inc

What happens when you put the strategic and operational sides of FinOps in the same room? In this episode of FinOps in Action, host Taylor Houck welcomes two guests for the first time on the show, Sean Kennedy, Senior Cloud FinOps Consultant, and Amanda Wagner, Cloud FinOps Consultant, both from Trace3. Sean focuses on presales strategy and partner enablement across Trace3's FinOps practice, while Amanda works directly with a portfolio of customers on the practitioner side. Together they unpack why FinOps never really finishes, how customer maturity changes the conversation, and what the AI cost landscape looks like right now. Here’s what we talked about: FinOps is a cycle, not a destination. There's no finish line, just an ongoing loop of informing, optimizing, and operating that adapts as engineering, pricing, and business needs change.Document your processes before you need them. Repeatable procedures for tagging, showback, and optimization reviews protect your FinOps program from falling apart when key people leave.Meet customers at their maturity level. Don't push budgeting and forecasting on a team that's still working on basic visibility; introduce concepts in bite-sized chunks as they're ready.The biggest wins often come from on-prem-to-cloud transitions. Companies migrating legacy infrastructure and mindsets tend to have the most untapped savings potential, partly because the human resistance to change is as big a factor as the technical work.Clarify what "AI spend" actually means before optimizing it. Seat-based licenses, hyperscaler AI services, GPU infrastructure, and token-based usage are all totally different cost problems that need different strategies.Chapters: 00:00 Welcome to the Show 00:51 Meet Sean and Amanda 01:51 Sean's Role at Trace3 02:41 Amanda's Practitioner Lens 03:18 Myth of Being Done 04:09 Mindset Shift From IT 05:05 FinOps as Org Adoption 06:15 Repeatable Processes Matter 07:09 Core FinOps Processes 08:12 Enterprise vs Commercial Needs 11:10 When Spend Forces FinOps 12:03 Start Early and Build Habits 14:36 Meeting Customers Where They Are 16:32 Who Gains the Most 23:18 AI Expands FinOps Scope 27:56 Forecasting and Optimizing AI 31:44 Closing and Personal Journeys  🎧 Subscribe for more FinOps leadership conversations → https://www.finopsinaction.com/  Quote of the Show: “"I think the myth is that FinOps is something that you finish, right? You don't ever arrive at FinOps." - Amanda WagnerLinks: LinkedIn: https://www.linkedin.com/in/amanda--wagner/LinkedIn: https://www.linkedin.com/in/sean~kennedy/Website: https://www.trace3.com/Ways to Tune In: Amazon Music: https://music.amazon.com/podcasts/f25a9d18-c12f-4ee4-93f5-2aa96e509b55 Apple Podcasts: https://podcasts.apple.com/us/podcast/finops-in-action/id1790497808 iHeart Radio: https://iheart.com/podcast/268443483/ Podchaser: https://www.podchaser.com/podcasts/finops-in-action-5958339 Spotify: https://open.spotify.com/show/3IpjMc3qxDXZAjic5Zq21t Substack: https://finopsinaction.substack.com/ Transistor: finopsinaction.com YouTube: https://www.youtube.com/@PointFive_Inc

What if the biggest mistake your FinOps program makes is skipping the requirements phase entirely? In this episode of FinOps in Action, host Taylor Houck sits down with Piotr Kuczmera, Head of FinOps at ZF Group, to unpack how he built a FinOps practice from scratch at a 150,000 person global enterprise, and why the first question every organization should ask is not "how do we cut costs" but "what exactly do we need?" Piotr shares how a single report request from his manager five years ago turned into a full scale internal FinOps platform, a hub and spoke operating model across 15 to 20 business units, and a team built on the combination of FinOps practitioners and data engineers working side by side. Here is what they covered:  Why FinOps is more than cost savings. Piotr explains that equating FinOps with cost optimization alone leads to failed implementations, and that starting with a clear requirements conversation, like a tailor fitting a suit to the right occasion, is what sets a practice up for long term success. How chargeback became the turning point. When ZF connected individual names to specific budgets and sent real invoices, something clicked. Engineers and budget holders stopped asking about aggregate project spend and started asking "why am I paying this much and how do I reduce it?" The case for building your own platform. ZF evaluated the major third party FinOps tools and walked away. Licensing costs, limited multi-cloud support, and a lack of flexibility in adapting to existing finance and procurement processes all pointed toward a homegrown solution built on native cloud tooling and a BI layer they already owned. The hub and spoke model for FinOps at scale. At the center sits a core team of FinOps consultants and data engineers. In each business unit, a nominated budget owner and a FinOps champion bridge the gap between central strategy and local execution. AI for FinOps, not just FinOps for AI. Piotr is most energized by how AI can automate repetitive FinOps workflows and take recommendations beyond basic CPU and memory parameters to consider commitment connections, usage patterns, and resource families all at once. He also sees FinOps as a function that should open doors for AI adoption, not slow it down. FinOps as connective tissue. Across financial colleagues, engineering teams, and business managers, Piotr sees FinOps as the function responsible for translating the right information to the right persona, not flooding finance with VM data, and not giving engineers a budget variance they cannot act on.Chapters: 00:00 What Every Company Gets Wrong About FinOps  01:27 Meet Piotr Kuczmera  02:14 FinOps Is Not Just Cost Savings  03:30 Building Trust Across Departments  05:00 The FinOps Team Structure at ZF Group  08:00 Hub and Spoke: Champions and Budget Owners  10:00 Scale and Cadence Across 15 to 20 Categories  12:00 Back to the Beginning: One Report at a Time  14:00 Build vs Buy: The Platform Decision  18:00 Why Ownership of Data Changes Everything  21:00 Chargeback as the Accountability Switch  23:00 Translating FinOps Across Personas  25:00 FinOps as Connective Tissue  26:00 AI for FinOps and FinOps for AI  29:00 Treating AI Spend Like Any Other Cloud Service  30:00 What the Well Tailored FinOps Suit Looks Like in One Year  31:00 From Math Degree to FinOps Leader  33:00 Advice for Early Career FinOps Professionals  34:00 Where to Find Piotr Quote of the Show:"Stay humble and don't be afraid of challenges." - Piotr Kuczmera 🎧 Subscribe for more FinOps leadership conversations: https://www.finopsinaction.com/ Links: LinkedIn: https://www.linkedin.com/in/piotr-kuczmera-59b39712a/Website: https://www.zf.com/usa_canada/en/home/home.htmlWays to Tune In: Amazon Music: https://music.amazon.com/podcasts/f25a9d18-c12f-4ee4-93f5-2aa96e509b55 Apple Podcasts: https://podcasts.apple.com/us/podcast/finops-in-action/id1790497808 iHeart Radio: https://iheart.com/podcast/268443483/ Podchaser: https://www.podchaser.com/podcasts/finops-in-action-5958339 Spotify: https://open.spotify.com/show/3IpjMc3qxDXZAjic5Zq21t Substack: https://finopsinaction.substack.com/ Transistor: finopsinaction.com YouTube: https://www.youtube.com/@PointFive_Inc

What if the biggest cloud savings opportunity isn't hidden in your infrastructure, but in the decisions made before the first line of code is written? In this episode of FinOps in Action, Taylor sits down with Ruby Agarwal, VP of Engineering at Avaya, whose responsibilities span engineering, DevOps, DevSecOps, CloudOps, and FinOps. Ruby shares how her team reduced cloud spend by 75% in just two months, why visibility matters more than perfect data, and how cost awareness becomes part of engineering culture rather than a one-time optimization project. They also explore how AI is changing operational decision-making and why the future of FinOps will depend on balancing innovation with discipline. Takeaways: Start with visibility, not spreadsheets of despair. Ruby's team didn't need perfect data to cut 75% of spend, they needed a one-slider view everyone could understand. Skip the 20 page report and focus your team's attention on the handful of buckets driving most of the cost.Cost isn't the enemy, inefficiency is. Turning everything off would bring spending to zero, but that's not the goal. The goal is getting the same performance, reliability, and security for less, not gutting the services delivering value.Build your COGS model before you write code. On Avaya Infinity, Ruby's team defined their cost model before a single line was written, and they publish and measure it every month. Bake cost discipline into the architecture from day one instead of cleaning up after launch.Separate your AI innovation zone from your production zone. Let engineers experiment freely with the most powerful models while building, but production agents don't need the flashiest reasoning model, they need the cheapest one that gets the job done reliably.The skills that carry your career aren't technical. Ruby calls systems thinking, structured decision-making, communication, and connection-building the real differentiators, not soft skills but critical skills. Investing in those early pays off longer than any single technology wave.Chapters: 00:00 Welcome and Guest Intro 01:25 The 75 Percent Story Setup 01:45 Project Context Multi Cloud 02:37 Cataloging Costs and Buckets 03:21 Quick Wins Labs Scheduling 04:15 Storage Cleanup and Tiering 04:30 Dashboards Make It Visible 05:44 Working With Developers 06:50 Culture Tools and Training 08:58 Cross Functional Momentum 10:29 FinOps From Day One 11:21 Avaya Infinity COGS Model 13:37 Who Owns Cost Decisions 15:28 Need Dedicated FinOps 18:00 80 20 Cost Focus 21:08 Cost Fear vs Cloud Value 23:04 Regulated Industry Constraints 26:38 AI Agents and Model Costs 32:53 Future of Operational Intelligence 35:30 Career Advice Beyond Tech 37:36 Giving Back and Mentoring 39:23 Closing Thanks and Wrap  🎧 Subscribe for more FinOps leadership conversations → https://www.finopsinaction.com/  Quote of the Show: “ Your first cloud cost bill will be dependent on what architectural decisions you have made for your projects.” - Ruby Agarwal Links: LinkedIn: https://www.linkedin.com/in/rubyagarwal/Website: https://www.avaya.com/en/Ways to Tune In: Amazon Music: https://music.amazon.com/podcasts/f25a9d18-c12f-4ee4-93f5-2aa96e509b55 Apple Podcasts: https://podcasts.apple.com/us/podcast/finops-in-action/id1790497808 iHeart Radio: https://iheart.com/podcast/268443483/ Podchaser: https://www.podchaser.com/podcasts/finops-in-action-5958339 Spotify: https://open.spotify.com/show/3IpjMc3qxDXZAjic5Zq21t Substack: https://finopsinaction.substack.com/ Transistor: finopsinaction.com YouTube: https://www.youtube.com/@PointFive_Inc

What does agentic FinOps actually look like in practice, and how should practitioners start thinking about it? Taylor Houck sits down with Pathik Sharma, Cloud Cost Optimization Lead at Google Cloud and Cofounder of their Cloud FinOps practice, to talk about how AI is closing the gap between knowing and doing in FinOps. Pathik shares how teams can hand off low risk tasks like tagging and labeling to AI agents while keeping humans in the loop on anything production related, and offers a four bucket framework for evaluating AI ROI: cost efficiency, productivity, differentiation, and revenue. His take for practitioners: embrace the change, learn the tooling, and let AI handle the friction so you can focus on business value. Here’s what we talked about: Don't silo your FinOps practice. Cost optimization doesn't exist in a vacuum. Factor in performance, security, scalability, and capacity from the start, and build tight relationships with platform, SRE, and app teams to get anything done. Use AI agents for the low risk wins first. Start with non-disruptive tasks like tagging and labeling before giving AI autonomy over anything that touches production. Build confidence incrementally. Keep humans in the loop on consequential actions. Have your AI agent create a pull request and route it to the application owner for approval rather than pushing changes directly. The app team still owns uptime. Don't pick your AI model on instinct. Build a golden dataset, define what good looks like, and test models against it. One retail company cut their AI costs from $340K to $17K a month by switching models after running the data. Start from the problem, not the solution. Identify the real friction points your FinOps and engineering teams face, then figure out where AI reduces that friction. Chasing AI for its own sake is how you burn the budget without value.Chapters: 00:46 Meet Pathik Sharma 01:58 AI Makes FinOps Urgent 03:09 From Tinkering To Priority 06:22 Defining Agentic FinOps 06:33 Culture And The Knowing Doing Gap 08:56 Kubernetes Agent Example 10:58 Is It Still FinOps 12:37 Humans In The Loop 13:23 Safe Automation With Tagging 15:07 PR Based Remediation Workflow 18:14 Trustworthy Recommendations First 20:58 Build Trust Incrementally 23:35 Managing AI Spend Beyond Tokens 27:27 FinOps For AI Framework 28:32 Retail Case Study Huge Savings 32:27 ROI Buckets And Closing Advice  🎧 Subscribe for more FinOps leadership conversations → https://www.finopsinaction.com/  Quote of the Show: "Embrace the change that is happening and learn it. FinOps holds keys to the kingdom" - Pathik SharmaLinks: LinkedIn: https://www.linkedin.com/in/pathik-sharma/Website: https://pathiksharma.com/Ways to Tune In: Amazon Music: https://music.amazon.com/podcasts/f25a9d18-c12f-4ee4-93f5-2aa96e509b55 Apple Podcasts: https://podcasts.apple.com/us/podcast/finops-in-action/id1790497808 iHeart Radio: https://iheart.com/podcast/268443483/ Podchaser: https://www.podchaser.com/podcasts/finops-in-action-5958339 Spotify: https://open.spotify.com/show/3IpjMc3qxDXZAjic5Zq21t Substack: https://finopsinaction.substack.com/ Transistor: finopsinaction.com YouTube: https://www.youtube.com/@PointFive_Inc

What if the best FinOps practitioners are the ones who never set out to be FinOps practitioners at all? In this episode of FinOps in Action, host Taylor Houck sits down with Gerard Sanchez, Head of Enterprise Platforms and Cloud Technology at Resolution Life, to unpack what it actually looks like to build a cloud engineering, DevOps, and FinOps practice from absolute zero at a company that was only six months old when he joined. Gerard brings a hardcore infrastructure and networking background to a discipline that too often gets siloed away from engineering, and the results speak for themselves. Here’s what we talked about: Set up automated cost alerts and guardrails from the start. Getting notified about a surprise bill is useful, but building automations that throttle or shut down rogue functions before the cost spiral is where you really want to be. Tagging is non-negotiable. If you can't trace spend back to a specific application or team, you'll never have the visibility to make smart optimization decisions. Shift FinOps left into the architecture and design phase. Catching cost inefficiencies before they deploy is far more effective than trying to optimize them after the fact. Match your cloud services to the actual workload. Before defaulting to high-performance, high-cost infrastructure, pressure-test whether the use case actually demands it. A Toyota Corolla solution often performs just as well as a Bugatti for the average user. Keep humans in the loop as you adopt AI. Even as agentic systems get more capable, building strong permissioning, tagging, and auditability into your AI framework now will save you from costly and chaotic surprises later.Chapters: 00:42 Meeting Gerard Sanchez 01:25 Building from Scratch 02:52 Fast and Good Over Cheap 05:22 The Wake Up Call 07:58 Crawl Walk Run Journey 10:08 Engineering Led FinOps 11:53 Right Sizing Use Cases 14:43 Shifting Left 16:13 AI and Automation 18:46 Agentic AI Architecture 22:12 Trust and Validation 23:45 Managing AI Costs 24:55 The Future of Business 30:31 Building the AI Foundation 32:50 Career Advice 36:58 Closing Thoughts  🎧 Subscribe for more FinOps leadership conversations → https://www.finopsinaction.com/  Quote of the Show: "I think especially for production environments or environments that are super sensitive, there's always gonna be a human in the loop." — Gerard SanchezLinks: LinkedIn: https://www.linkedin.com/in/gerard-r-sanchez/Website: https://www.resolutionlife.com/Ways to Tune In: Amazon Music: https://music.amazon.com/podcasts/f25a9d18-c12f-4ee4-93f5-2aa96e509b55 Apple Podcasts: https://podcasts.apple.com/us/podcast/finops-in-action/id1790497808 iHeart Radio: https://iheart.com/podcast/268443483/ Podchaser: https://www.podchaser.com/podcasts/finops-in-action-5958339 Spotify: https://open.spotify.com/show/3IpjMc3qxDXZAjic5Zq21t Substack: https://finopsinaction.substack.com/ Transistor: finopsinaction.com YouTube: https://www.youtube.com/@PointFive_Inc

What if the biggest driver of cloud waste isn't what shows up in your billing dashboard? In this episode of FinOps in Action, Taylor sits down with Mike Jaco, who spent years at Mastercard running one of the most sophisticated hybrid cost programs in enterprise technology. A unified TBM and FinOps practice covering a multi-billion dollar technology budget, on-prem and public cloud, under a single common taxonomy. Mike's core belief: most large organizations will be hybrid forever, and the industry hasn't caught up to what that actually requires. Here's what they covered: Build a common taxonomy before you do anything else. If your technology teams, product teams, and finance teams are using different languages to describe the same thing, no one is having the right conversation. Get everyone onto one shared structure first and everything else gets easier.Allocate cost down to the product level, not just the business unit. Stopping at the business unit level leaves too much room for ambiguity and not enough room for accountability. The more granular your allocation, the clearer it becomes who owns what and what action to take.Most large organizations will be hybrid forever, so build for it. Regulation, data sovereignty, and steady state workloads mean a full cloud migration is not realistic for most enterprises. Build your measurement framework to cover both worlds under one taxonomy or you are only ever telling half the story.Savings that stay in the team drive more action than savings that disappear. If engineers know that any efficiency they find gets reinvested into their own backlog rather than returned to a central budget, the motivation to optimize shifts completely. Self-funding growth is a more powerful incentive than a cost reduction target.FinOps is a people problem first and a data problem second. When an engineer is not making a change, it is almost never because they want to waste money. They are overloaded, they have competing priorities, or the task does not benefit them. Solve for the people dynamic and the technical changes follow.Chapters: 00:11 Meet Mike Jaco 01:11 Why Hybrid Is Forever 01:38 Regulation Drives Reality 02:55 On Prem vs Cloud Economics 03:28 The Apples to Apples Problem 04:58 Building a Common Taxonomy 06:21 Making Tech Less a Black Box 06:59 Why Allocate to Product Level 07:13 Accountability Creates Action 08:36 TBM vs FinOps Actions 10:21 18 Months vs 3 Months 11:45 Granularity vs Peanut Butter 13:16 Controllable vs Uncontrollable Spend 14:45 Carbon Becomes a Currency 17:11 Cloud Carbon Data Gap 20:39 Cost vs Carbon Tradeoffs 29:54 AI Spend and FinOps Future 37:39 Career Next Steps and Advice 39:47 People First FinOps Lessons 41:22 Where to Find Mike 🎧 Subscribe for more FinOps leadership conversations → https://www.finopsinaction.com/  Quote of the Show: “You can do more with the same budget.” - Mike Jaco Links: LinkedIn: https://www.linkedin.com/in/mike-jaco/ Ways to Tune In: Amazon Music: https://music.amazon.com/podcasts/f25a9d18-c12f-4ee4-93f5-2aa96e509b55 Apple Podcasts: https://podcasts.apple.com/us/podcast/finops-in-action/id1790497808 iHeart Radio: https://iheart.com/podcast/268443483/ Podchaser: https://www.podchaser.com/podcasts/finops-in-action-5958339 Spotify: https://open.spotify.com/show/3IpjMc3qxDXZAjic5Zq21t Substack: https://finopsinaction.substack.com/ Transistor: finopsinaction.com YouTube: https://www.youtube.com/@PointFive_Inc

What if the biggest cost problem in your organization never shows up on your cloud bill? In this episode of FinOps in Action, host Taylor Houck sits down with Kumar Singirikonda, Director of DevOps Engineering at Toyota Financial Services, FinOps Foundation board member, and author of the DevOps Automation Cookbook. Kumar makes the case that FinOps as we know it is only the first chapter, and the next chapter belongs to self-healing systems, AI-driven remediation, and a class of costs that traditional cost reports have never been able to surface. Here is what they covered: The hidden costs that never appear on your dashboard. Track your direct cloud expenses all you want, but your biggest operational costs are invisible. A single 30 minute outage won't change your infrastructure bill, yet it pulls in engineering teams, delays releases, and creates support volume that compounds for days.From cost control to value creation. Stop asking how to reduce cloud spend and start asking how to maximize business value from your engineering investments. When you do that, cost optimization becomes an outcome of operational maturity rather than the goal itself.What a self healing platform actually looks like. When a routing issue triggers a 404 spike, your system should detect the anomaly, correlate it with the recent deployment, invoke a remediation workflow, and execute a rollback in under two minutes without a human touching a keyboard. That is what operational maturity actually looks like in practice.AI is not a silver bullet. A model alone does not create operational intelligence. Connect AI to your observability platforms, automation workflows, and remediation playbooks, and that is where the real value comes from.Chapters: 00:50 Meet Kumar Singarikkonda 01:59 Kumar’s Journey to FinOps 02:33 Hidden Operational Costs 04:41 From Cost Control to Value 06:55 Headcount vs Cloud Bill 07:54 Unknown Costs in Incidents 10:30 Measuring Engineering Efficiency 13:13 Self-Healing Systems Defined 13:39 How Self-Healing Works 16:23 404 Spike Self-Heal Example 20:30 Where AI Fits In 21:07 Agentic Workflows Over Hype 24:21 Engineering Efficiency Discipline 26:49 Building Cost-Aware Culture 29:56 Leadership Lessons at Toyota 32:11 Book Community and Closing 🎧 Subscribe for more FinOps leadership conversations → https://www.finopsinaction.com/  Quote of the Show:"The biggest operational cost problem today is inefficiency rather than infrastructure pricing. Organizations that reduce operational friction unlock far greater long-term value than organizations focused only on reducing the compute spend." - Kumar Singirikonda Links: LinkedIn: https://www.linkedin.com/in/kumarsingirikondaWebsite: https://www.toyota.com/usaBook Link: https://www.amazon.com/DevOps-Automation-Cookbook-Harness-automation/dp/9355519060Ways to Tune In: Amazon Music: https://music.amazon.com/podcasts/f25a9d18-c12f-4ee4-93f5-2aa96e509b55 Apple Podcasts: https://podcasts.apple.com/us/podcast/finops-in-action/id1790497808 iHeart Radio: https://iheart.com/podcast/268443483/ Podchaser: https://www.podchaser.com/podcasts/finops-in-action-5958339 Spotify: https://open.spotify.com/show/3IpjMc3qxDXZAjic5Zq21t Substack: https://finopsinaction.substack.com/ Transistor: finopsinaction.com YouTube: https://www.youtube.com/@PointFive_Inc

Are "bad tagging" and "unused resources" really the problem, or just the symptoms of a bigger one? In this episode of FinOps in Action, I sit down with senior FinOps manager Chitra Jadhav to explore what it truly takes to build a FinOps practice that lasts not just one that generates a list of recommendations nobody acts on. Drawing on eight years of building FinOps programs from the ground up across six or more organizations, Chitra explains how governance, culture, and cross functional collaboration are the real foundations of cloud cost optimization and why FinOps is only as powerful as the trust and authority an organization is willing to give it. From Architecture Review Boards to Production Readiness Reviews, this conversation unpacks how FinOps can embed itself into the engineering lifecycle before waste ever happens, and why the shift to AI spend makes getting those basics right more urgent than ever.   Here’s what we talked about: Why organizational recognition and governance are the prerequisites for any FinOps program to succeedHow to assess FinOps maturity using the FinOps Foundation framework as a starting pointWhy FinOps is a team sport and how to engage finance, engineering, procurement, and application teamsWhat ARBs and Production Readiness Reviews are and how FinOps earns a seat at the tableHow to approach optimization when native cloud provider recommendations run dryThe importance of the FinOps champion model when working across large engineering organizationsChapters: 00:47 Meet Chitra Jadhav 01:56 Why FinOps Matters 03:37 Starting From Scratch 03:52 Maturity Assessment Basics 04:48 Stakeholder Engagement Model 05:56 Where FinOps Reports 07:16 Defining Governance 08:14 FinOps Checkpoints ARB PRR 10:42 What Is an ARB 12:51 Running ARB Without Bloat 16:38 Shift Left to Optimization 18:22 Champion Model and Visibility 21:05 Authority Trust and Culture 25:29 Realistic Goals and Commitments 29:20 Beyond Native Recommendations AI 33:02 AI Spend and Future Wrap  🎧 Subscribe for more FinOps leadership conversations → https://www.finopsinaction.com/  Quote of the Show: "Instead of paying that money and incurring that waste, you are taking some steps proactively by making sure that you are present at these discussions." - Chitra Jadhav Links: LinkedIn: https://www.linkedin.com/in/chitrajadhav/ Website: https://www.rogers.com/ Ways to Tune In: Amazon Music: https://music.amazon.com/podcasts/f25a9d18-c12f-4ee4-93f5-2aa96e509b55 Apple Podcasts: https://podcasts.apple.com/us/podcast/finops-in-action/id1790497808 iHeart Radio: https://iheart.com/podcast/268443483/ Podchaser: https://www.podchaser.com/podcasts/finops-in-action-5958339 Spotify: https://open.spotify.com/show/3IpjMc3qxDXZAjic5Zq21t Substack: https://finopsinaction.substack.com/ Transistor: finopsinaction.com YouTube: https://www.youtube.com/@PointFive_Inc

What if your biggest cloud inefficiency isn’t how much you’re using, but how long your workloads are running? In this special episode of FinOps in Action, PointFive’s Co-Founder and CPO, Gal Ben David sits down with Matan Ben-Ishay, leading FP&A, Engineering, and Cloud Infrastructure at Credit Karma, to unpack a real world cloud efficiency discovery that led to tens of millions of dollars in savings without reducing usage or cutting performance. Matan shares how a simple assumption about “cheaper” CPUs quietly inflated costs, why billing data alone didn’t reveal the problem, and how true FinOps impact only happens when finance and engineering work side by side. We also covered how FinOps wins happen at the intersection of finance, engineering, and product and how understanding accounting concepts is a career advantage in FinOps.   Here’s what we talked about: How a hidden GCP dataflow inefficiency cost tens of millions until Matan sat with engineers and discovered faster CPUs actually cost less per hourWhy rigid governance policies backfire and how flexible guidelines that encourage engineers to evaluate their actual workload needs prevent wasteWhy FinOps professionals need to understand accounting concepts (depreciation, amortization, commitments)The emerging need for cloud efficiency engineers embedded in teams who can bridge the gap between FinOps strategy and hands on optimization workHow running parallel tests of old vs. new approaches proves value to skeptical engineers and turns short-term testing costs into long-term savingsThe structural friction between engineering OKRs (focused on launches and reliability) and cost efficiency, and why engineers should treat cloud spend like any other company resource Chapters: 00:00 FinOps Is Everyone’s Job 00:16 Special Episode Setup 01:27 Meet Matan Ben-Ishay 02:14 The Incentives Mistake 05:12 Speed vs Cost in AI 07:30 How to Motivate Engineers 10:19 Scaling Best Practices Org-Wide 13:27 Where FinOps Should Sit 18:02 Guardrails and Shared Ownership 20:55 Fleet Guardrails Matter 21:38 Hidden Waste Over Time 22:47 Can We Prevent Waste 25:56 Tactical vs Strategic Waste 27:00 FinOps on GCP Reality 29:14 Commitment Forecasting Playbook 32:30 FinOps Parenting Hacks 35:31 Personal Picks and Growth 37:53 Closing and Where to Connect 🎧 Subscribe for more FinOps leadership conversations → https://www.finopsinaction.com/  Quote of the Show: “We need those cloud efficiency engineers in order to understand.” - Matan Ben-IshayLinks: LinkedIn: https://www.linkedin.com/in/matan-ben-ishay/ Website: https://www.creditkarma.com/ Ways to Tune In: Amazon Music: https://music.amazon.com/podcasts/f25a9d18-c12f-4ee4-93f5-2aa96e509b55 Apple Podcasts: https://podcasts.apple.com/us/podcast/finops-in-action/id1790497808 iHeart Radio: https://iheart.com/podcast/268443483/ Podchaser: https://www.podchaser.com/podcasts/finops-in-action-5958339 Spotify: https://open.spotify.com/show/3IpjMc3qxDXZAjic5Zq21t Substack: https://finopsinaction.substack.com/ Transistor: finopsinaction.com YouTube: https://www.youtube.com/@PointFiveCloudCostEfficiency

How do you make cloud data costs transparent and actionable when thousands of users share the same platform? In this episode of FinOps in Action, I sit down with Oliver Milke from TD, who shares how he built a Data FinOps practice from the ground up inside a large financial institution, starting as a team of one and scaling into a dedicated function. Coming from a background in economics and finance, Oliver offers a unique perspective on cloud cost optimization. Rather than focusing solely on infrastructure, his team goes one level deeper: tracking and allocating costs at the data layer, down to individual tables, workloads, and user groups. The conversation explores why traditional FinOps models fall short for shared data platforms, how transparency drives accountability, and what it takes to operationalize cost awareness across thousands of users. Oliver also breaks down the role of education, chargeback, and engineering collaboration in building a sustainable FinOps practice.   Here’s what we talked about: What “Data FinOps” is and how it differs from traditional FinOpsWhy shared data platforms require a fundamentally different cost modelBuilding cost visibility down to the table and workload levelMoving from showback to chargeback and how it shifts user behaviorPlatform vs. workload-level optimization strategiesThe role of education and change management in FinOps successChapters: 00:00 - Data FinOps Origins 00:20 - Show Intro Guest Setup 01:40 - What Is Data FinOps 03:37 - Cloud Migration Spark 05:03 - Finance Mindset Meets Engineering 06:22 - FinOps Hub Cost Transparency 07:59 - Monthly Reviews And Chargeback 10:09 - Optimization Strategy Overview 12:17 - Databricks Efficiency Playbook 17:31 - Spot Instances Adoption 19:45 - Education As A Pillar 23:24 - Building The FinOps Team 25:59 - Advice For New Practitioners 28:06 - AI In FinOps Next Wave 30:55 - Running For Campfire Circle 33:03 - Closing And Where To Connect  🎧 Subscribe for more FinOps leadership conversations → https://www.finopsinaction.com/  Quote of the Show:“We recognized that this cannot be a one-off, but it needs to be a permanent ongoing thing.” - Oliver Milke Links: LinkedIn: https://www.linkedin.com/in/oliver-milke/ Website: https://www.td.com/us/en/personal-banking  Ways to Tune In: Amazon Music: https://music.amazon.com/podcasts/f25a9d18-c12f-4ee4-93f5-2aa96e509b55 Apple Podcasts: https://podcasts.apple.com/us/podcast/finops-in-action/id1790497808 iHeart Radio: https://iheart.com/podcast/268443483/ Podchaser: https://www.podchaser.com/podcasts/finops-in-action-5958339 Spotify: https://open.spotify.com/show/3IpjMc3qxDXZAjic5Zq21t Substack: https://finopsinaction.substack.com/ Transistor: finopsinaction.com YouTube: https://www.youtube.com/@PointFive_Inc

Are “idle resources” really the problem, or just the easiest one to fix? In this episode of FinOps in Action, I sit down with cloud architect and engineer Shailaja Beeram to explore a fundamentally different perspective: cost inefficiencies don’t start in the billing file, but in architectural decisions made long before deployment. Drawing on over 15 years of experience across AWS, Azure, and GCP, Shailaja explains how the way systems are designed, scaled, and evolved over time has a far greater impact on cloud spend than most teams realize. From “zombie” networking resources to overlooked outbound traffic patterns, this conversation unpacks the hidden layers of cloud cost and why FinOps and architecture must converge to solve them.   Here’s what we talked about: Why cloud inefficiencies often stem from architecture and not just unused resourcesHow NAT Gateways and private endpoints quietly drive unnecessary spendWhat “zombie resources” are and how they accumulate over timeWhy background traffic can mask true resource idlenessThe importance of revisiting architectural decisions as systems evolveThe growing convergence of FinOps and cloud architectureChapters: 00:00 - Architecture Drives Cost 00:34 - Meet the Guest Architect 01:46 - When Cost Became the Job 03:04 - Networking Zombie Resources 05:32 - NAT Gateway Design Traps 07:11 - Spotting Hidden Traffic 10:34 - Azure Functions NAT Story 12:30 - Private Endpoints and Drift 16:53 - Shift Left Cost Awareness 19:20 - Balancing Risk and Cost 22:46 - Advice for Both Sides 26:41 - AI Impact on FinOps 27:53 - Volunteering and Closing 30:37 - Outro and Sponsor  🎧 Subscribe for more FinOps leadership conversations → https://www.finopsinaction.com/  Quote of the Show: “FinOps… it doesn’t need to be separated. It should be a part of how you think about the architecture.” - Shailaja BeeramLinks: LinkedIn: https://www.linkedin.com/in/shailaja-beeram-82324310a/ Ways to Tune In: Amazon Music: https://music.amazon.com/podcasts/f25a9d18-c12f-4ee4-93f5-2aa96e509b55 Apple Podcasts: https://podcasts.apple.com/us/podcast/finops-in-action/id1790497808 iHeart Radio: https://iheart.com/podcast/268443483/ Podchaser: https://www.podchaser.com/podcasts/finops-in-action-5958339 Spotify: https://open.spotify.com/show/3IpjMc3qxDXZAjic5Zq21t Substack: https://finopsinaction.substack.com/ Transistor: finopsinaction.com YouTube: https://www.youtube.com/@PointFiveCloudCostEfficiency

Are you actually measuring the value of your cloud spend or just tracking the cost? In this episode of FinOps in Action, I sit down with Kevin Mueller, Principal Architect of Cloud FinOps at Presidio, to unpack one of the most talked-about and most misunderstood concepts in FinOps: unit economics. With over 20 years of experience spanning software engineering, AWS SaaS architecture, and cloud financial management, Kevin shares a grounded, practical perspective on why most organizations struggle to implement unit economics and how to actually get started. The conversation explores the gap between visibility and action, why traditional cost allocation models fall short, and how engineering, product, finance, and sales all benefit when cloud spend is tied directly to business value. Kevin also dives into real-world examples, from optimizing SQL queries and Kubernetes workloads to navigating the growing complexity of AI-driven infrastructure. If you’ve ever wondered how to move beyond dashboards and into meaningful optimization, or how to prove that your cloud investment is truly productive, this episode is for you. Here’s what we talked about: Why most companies still aren’t doing unit economics (and what separates those who do it well)The difference between unit metrics and unit economicsHow to move from high-level allocation to actionable, engineering-driven insightsHow to approach tagging without overcomplicating your systemWhy AI is the next major FinOps challenge (and opportunity)The biggest challenges with shared resources like Kubernetes and what actually drives optimization Chapters: 00:00 - Cloud Cost Tradeoffs 01:31 - Kevin’s FinOps Journey 03:13 - Unit Economics Reality Check 04:18 - Defining Unit Economics 05:46 - How to Implement It 09:26 - Metrics That Drive Action 14:10 - Allocation Products vs Teams 20:26 - Tagging Without Pain 23:02 - Kubernetes Cost Challenges 24:51 - K8s Optimization Basics 26:18 - Architecture Choices with Units 28:04 - AI as Shared Spend 30:13 - Measuring AI Value 32:28 - AI for FinOps Teams 35:41 - Life on the Farm 37:54 - Wrap Up and Where to Connect  🎧 Subscribe for more FinOps leadership conversations → https://www.finopsinaction.com/  Quote of the Show: “It's so easy in FinOps to measure all of this stuff, put it in a dashboard and look at it and feel happy that it's there, but you need to drive towards action.” - Kevin MuellerLinks: LinkedIn: https://www.linkedin.com/in/kevinmueller/ Website: https://www.presidio.com/ Ways to Tune In: Amazon Music: https://music.amazon.com/podcasts/f25a9d18-c12f-4ee4-93f5-2aa96e509b55 Apple Podcasts: https://podcasts.apple.com/us/podcast/finops-in-action/id1790497808 iHeart Radio: https://iheart.com/podcast/268443483/ Podchaser: https://www.podchaser.com/podcasts/finops-in-action-5958339 Spotify: https://open.spotify.com/show/3IpjMc3qxDXZAjic5Zq21t Substack: https://finopsinaction.substack.com/ Transistor: finopsinaction.com YouTube: https://www.youtube.com/@PointFiveCloudCostEfficiency

Why do cloud costs stay high even after you build all the right dashboards? In this episode of FinOps in Action, I sit down with Cristian Magherusan-Stanciu, Founder and Cloud Optimization Specialist at Leaner Cloud. With over 20 years in systems engineering and a background at Nokia, HERE Technologies, and AWS, Cristian built AutoSpotting, an open source tool that has helped more than 10,000 customers save money on EC2. Cristian shared his hard-won framework for turning cloud cost insights into real savings, why automation alone will never be enough, and how AI has multiplied his output as a solo operator by an order of magnitude. We also covered the hidden business context that can turn a routine optimization into a $30K/month win, and why cost avoidance is just as important as cost reduction when your cloud bill keeps growing.   Here’s what we talked about: Dashboards are only half the story and prioritize action over visibility. The biggest gains come to teams that actually implement recommendations, not just track them.Right size incrementally, not aggressively. Cutting a resource by 8x in one step is risky instead halve it, observe, and iterate to avoid introducing performance problems.Match your optimization approach to the application’s needs. Latency sensitive workloads, HA setups, and DR resources may appear wasteful but serve critical purposes and always bring engineering context into the conversation.Look beyond the metric to find the real opportunity. A $30K/month Aurora IO bill pointed to a forgotten database no one needed anymore and the fix wasn’t optimization, it was deletion.Track cost avoidance, not just savings. In high-growth environments, a flat or rising bill can still represent millions saved and measure what you would have paid without the work.AI has changed the game for solo practitioners. Cristian built in weeks what previously took a year or two, enabling him to ship a SaaS product and 30+ optimization tools as a one-person shop. Chapters: 00:00 - Dashboards Don't Save Money 00:19 - Show And Guest Intro 01:47 - Take Action First 04:00 - From Level Zero To Savings 06:08 - Prioritize Engineer Time 07:35 - Automation Without Breaking Things 10:07 - Working With DevOps And Devs 12:05 - When Engineers Push Back 14:17 - Cost Vs Risk And Context 16:09 - Big Wins That Repeat 20:00 - Common Waste Patterns 21:17 - The 30K Database Shutdown 24:19 - Proving Value Amid Growth 31:44 - AI Boosting FinOps Output  🎧 Subscribe for more FinOps leadership conversations → https://www.finopsinaction.com/  Quote of the Show: "In just a few weeks with AI, I built what previously would have taken me a year or two. It's at least an order of magnitude more output per unit of time." - Cristian Magherusan-Stanciu Links: LinkedIn: https://www.linkedin.com/in/cristimagherusan/ Website: https://leanercloud.com/ Website: https://autospotting.io/  Ways to Tune In: Amazon Music: https://music.amazon.com/podcasts/f25a9d18-c12f-4ee4-93f5-2aa96e509b55 Apple Podcasts: https://podcasts.apple.com/us/podcast/finops-in-action/id1790497808 iHeart Radio: https://iheart.com/podcast/268443483/ Podchaser: https://www.podchaser.com/podcasts/finops-in-action-5958339 Spotify: https://open.spotify.com/show/3IpjMc3qxDXZAjic5Zq21t Substack: https://finopsinaction.substack.com/ Transistor: finopsinaction.com YouTube: https://www.youtube.com/@PointFiveCloudCostEfficiency