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FinOps adoption over the past four years rivals nearly any IT trend in the last 25 years, driven by the need for financial accountability in expanding cloud environments.

As multicloud and AI grow, CloudOps teams must balance innovation with efficiency. Generative AI accelerates FinOps maturity while strong governance ensures accountability and maximizes cloud value.

Read why Kion’s FinOps+ platform stands out for its comprehensive visibility and advanced automation capabilities.

What an event we just had. I started FinOps Weekly a year ago, and now here we are:

Great announcements we’ve been holding for months.

Amazing sessions directly from the community.

Thought leadership insights for 2026 clarity.

For those who want to re-watch it on demand, link below and on the image.

Already thinking about next year’s edition and how to make it even better.

Thanks everyone for making it possible.

P.S. Talks splitted per day, find them using the timestamps.

P.S.2 Splitted talks will be uploaded in the coming weeks. Wanted to give you the recordings ASAP as you deserve them!

Cut Microsoft licensing costs by modifying vCPU options on EC2 Windows Server and SQL Server instances. Disable hyperthreading to halve vCPU counts while keeping memory and IOPS intact—an r7i.8xlarge drops from 32 to 16 vCPUs, cutting licensing bills in half.

EC2 Capacity Manager is now GA, providing a single dashboard to monitor On‑Demand, Spot, and Capacity Reservations across accounts and Regions. Get consolidated visibility, drill‑downs, and actionable optimization workflows at no extra cost.

AWS Marketplace now supports purchase order line numbers on invoices, mapping charges to specific PO lines for cleaner reconciliation and faster invoice processing across finance teams.

Customer Carbon Footprint Tool expanded to include Scope 3 emissions (upstream fuels, IT hardware, buildings) with recalculated historical data back to January 2022, offering auditable sustainability metrics tied to cost decisions.

Read All AWS Updates

Azure Storage Discovery is GA with Copilot integration. Ask natural‑language questions about storage growth and savings potential, get visualizations in minutes, and surface actionable optimization items across Blob and Data Lake Storage subscriptions.

Read All Azure Updates

GKE Inference Quickstart integrates with Gemini CLI to generate manifests and provide cost/performance recommendations for LLM inference. Compare accelerators, benchmark tokens/s, and calculate cost per token to make data‑driven tradeoffs on GPU spend.

Read All GCP Updates

This doesn’t stop! Looking forward to have you all the 13th of November to explore the Hybrid FinOps.

Discover how FinOps 2.0 strategies deliver comprehensive optimization across your entire technology portfolio.

You'll Learn How To:

Achieve total cost visibility across data centers, multi-cloud, SaaS, and AI infrastructure

Optimize the complete technology stack with unified intelligence and automation

Break down silos between FinOps, ITAM, procurement, and engineering teams

Jeremy Chaplin, Gerhard Behr & Victor Garcia

Most companies using AI right now are not thinking about token costs. But these costs are growing quickly, and the companies that figure this out first will have a big edge over others.

In AI systems, you don't pay for computer power or storage space like before. You pay for tokens. Every time you send text to an AI model, you pay for input tokens. Here’s how cloud cost management can be applied to token management:

Most companies should start by measuring token use right now. Track which features use tokens, which users, which prompts, and which models. Without this information, you can't make things better.

Then try small changes: make prompts shorter, test cheaper models, save common answers. Small fixes often give big results. After that, set up rules: create budgets, warnings, and limits so spending stays under control.

Token cost management will become as important to company leaders as cloud costs did before, as AI spending grows.

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We explore how to build a strong FinOps culture, overcome cloud cost optimization challenges, track progress with actionable KPIs, leverage observability, and apply AI to drive smarter cloud financial operations with expert insights from Amit Kinha

Learn how DoiT can help you with your AI costs

The author follows four made-up companies to show different ways of predicting costs. The main point is simple: predicting isn't about being right every time. It's about keeping everyone on the same page, from the people writing code to the people managing money. The article breaks down several big ideas:

Smart Tools Are Getting Better

Companies now use AI to spot patterns in their spending. One company improved their guessing from being off by 5% to only 3%. The computer learns things like "Mondays cost more because marketing runs ads" and stops treating normal events like weird problems.

Time Creates Problems

There's a weird gap between two types of cost tracking. Showback gives you numbers every day so engineers can see what they're spending right now. Chargeback comes from accounting and takes 30 to 60 days to finalize.

Putting Money Where Your Mouth Is

Predictions only matter when you commit real money. That's where reservations come in. You can reserve computer power for when you need it, or you can lock in lower prices by promising to use a certain amount.

Making It a Team Sport

The companies that do this well don't leave it to one person. They create regular meetings where engineers explain usage, product teams share growth plans, and finance sets budget limits.

The Real Payoff

Companies that build good prediction systems see clear results. Forecast errors drop by 35%. Finance teams close their books twice as fast. Waste from unused reservations falls by 30%.

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One of the biggest problems in FinOps is getting engineers and finance teams to understand each other. The issue goes deeper than just tools and reports. It comes down to how people think about money.

This is where mental accounting matters. Mental accounting means people treat money differently based on which category or bucket it belongs to, even though money is money no matter where it sits.

People split their budgets into different groups, set aside specific amounts, or feel strongly about certain types of spending. These mental divisions seem to make sense, but they can lead to choices that don't actually make economic sense.

FinOps is not just about showing people the numbers. It's about helping finance and engineering understand each other. But shared language is only the start. You can agree on the words and still disagree on what they mean. Real alignment needs shared understanding, not just shared vocabulary.

Understanding mental accounting helps you see the different, often hidden, ways that finance and engineering teams think about value, spending priorities, and costs.

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A new open source tool called FOCUS MCP Server lets you talk to your cloud billing data in plain English instead of writing complex database queries.

The tool works with FOCUS, which is a standard way to organize cloud billing information. FOCUS makes cost data look the same whether you use Amazon Web Services, Microsoft Azure, or Google Cloud. This means you can compare costs across different cloud providers without getting confused by different formats.

You can run it using Docker, which makes setup simple. Just point it to where your billing data lives, either on your computer or in cloud storage like Amazon S3. The tool uses DuckDB to process large amounts of billing data quickly.

The server also helps you learn about your billing data. You can ask it to explain what different columns mean or show you what information is available. Each query includes links back to official FOCUS documentation so you can learn more.

For developers, the code is available on GitHub and can be customized. The project supports multiple versions of the FOCUS standard and works with AWS credential systems for secure access to cloud storage.

Read More

Behavioural FinOps Master

Alison & Dan did a wonderful presentation in the summit. It’s in my favourite lists. She’s an experience FinOps expert that understand the people’s role on this.

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