What's new in Cloud FinOps?

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In this episode of What’s New in Cloud FinOps / September 2026 Cloud FinOps News, Frank Contrepois and Stephen Old review updates across AWS, Google Cloud, Microsoft, Oracle, Alibaba Cloud, and the wider cloud financial management ecosystem.

Compute and infrastructure

AWS Elastic Beanstalk cluster mode lets multiple applications share pooled EKS-backed infrastructure. This can reduce per-application costs as deployments grow, although the underlying EKS Auto Mode resources remain chargeable.

Bedrock AgentCore Runtime v2 now bills for actual memory usage instead of retaining a session’s peak allocation until it ends. Billing closer to consumption reduces the financial impact of temporary spikes.

AWS Lambda adds Graviton5-powered EC2 support through Lambda managed instances, including C9g, C9gd, M9g, and M9gd. The hosts distinguish better price performance from lower unit prices: savings may require resizing workloads to exploit faster hardware.

Amazon EC2 T8i burstable instances use sixth-generation Intel Xeon processors and offer improved price performance over T3. Nano, micro, small, and medium sizes target small websites, test environments, and lightweight workloads, with smaller sizes eligible for the free tier.

Amazon RDS adds AMD-based M8a instances using fifth-generation AMD EPYC processors. The hosts compare these with Graviton, noting that managed databases can make processor changes easier than migrating self-managed applications.

AWS Direct Connect introduces flat-rate pricing for 10/100 Gbps connections across five geographic scopes. It removes data transfer out charges within the selected tier and includes an optional redundant port pair at no extra cost. Large data movers gain greater predictability alongside potential savings.

CloudFront Flat Rate Plans become programmable through APIs and infrastructure as code, including subscriptions, upgrades, downgrades, and cancellations, with optional paid-plan approvals. This supports automated governance of CDN, DDoS protection, DNS, logging, and edge compute bundles without usage-based overages.

Amazon WorkSpaces adds NVIDIA Blackwell GPUs through G7 graphics instances. These offer up to 2.2 times G6 performance, 32 GB GPU memory per GPU, and 2.67 times faster bandwidth. Configurations span 1–8 GPUs, 8–192 vCPUs, and 32–768 GB memory. Initial availability in Ohio and Oregon targets CAD, 3D, visualisation, editing, and AI-assisted design.

Lambda also adds direct read configuration for S3 File High Performance Storage and standard buckets, helping optimise throughput and latency for data-intensive serverless workloads.

Google Cloud Run Jobs introduces deferred execution in preview. Non-urgent jobs can wait up to 12 hours for reduced pricing, offering savings where execution timing is flexible, including batch AI workloads.

Billing, chargeback, and visibility

AWS Billing Conductor adds custom rate and usage-tier pricing configurations, supporting more granular internal chargeback across services, teams, products, and business units.

AWS Billing and Cost Management dashboards gain anomaly widgets, bringing detected anomalies into views alongside budgets, cost efficiency, Savings Plans, and Reserved Instance utilisation.

The hosts examine proportional RI and Savings Plans chargeback. Centrally purchased commitments can be difficult to allocate fairly. AWS guidance combines Glue, Athena, Lambda, SSM Parameter Store, Billing Conductor, and EventBridge Scheduler to distribute realised savings proportionally across accounts.

The new ListBillingViewSegments API exposes historical billing context, including payer/member relationships, Billing Conductor groups, and whether billable or pro forma rates applied. This matters when accounts move: using today’s structure to interpret past spending can distort attribution, reconciliation, and audits.

AWS also publishes guidance on understanding Enterprise Support charges through billing APIs, including monthly totals, calculation rules, and account-level breakdowns. Stephen highlights the historical difficulty of allocating support costs across multiple payer accounts.

Google Cloud introduces an Incentives page for spend-based milestone credits, ramp incentives, Rapid Migration and Modernization Program credits, discounts, and other conditional incentives. It replaces the Spend-based Milestones tab for customers with custom pricing contracts.

Amazon Q gains payment capabilities to investigate overdue balances, identify failed payments and their causes, and resolve issues within a console conversation, potentially reducing manual reconciliation.

AI economics and tokenomics

An Oracle Cloud Infrastructure GenAI update from 23 September enables automatic routing of on-demand inference across approved regions. Initially focused on capacity resilience, routing profiles could eventually help balance cost, capacity, latency, and availability.

AWS and OpenAI Bedrock Managed Agents are in preview, with no additional Managed Agents charge beyond underlying AWS resources. Pricing may change at general availability, making this a FinOps watch item.

Google Cloud extends Gemini Enterprise overage controls to all invoiced cloud billing accounts and introduces session and memory bank compute metering for the Gemini Agent Platform.

From 2 November 2026, new Microsoft 365 Copilot business licences purchased through CSPs will have usage-based billing enabled by default. Seat licences can therefore expose organisations to variable charges for experiences including Copilot, Work IQ APIs, and GitHub Copilot-related capabilities.

Stephen sees this as a convergence of FinOps and IT Asset Management: licence optimisation alone is insufficient when subscriptions unlock pay-as-you-go usage. Microsoft’s FinOps for AI approach connects everyday subscriptions and advanced consumption-based capabilities with business outcomes.

AWS’s “Getting Started with Tokenomics” blog frames AI financial management around visibility and attribution, optimisation, governance, and value/ROI. The hosts welcome the focus on value rather than assuming fewer tokens always means a better result.

The discussion of Claude Sonnet 5.5, available through AWS Bedrock and Google Cloud, reinforces the shift from cost per token to cost per task. A higher-priced model may deliver a cheaper outcome through fewer tool calls, fewer interactions, faster completion, or less human intervention.

Stephen recommends “The Economics of Agent Optimization: Context Engineering for Enterprise AI Agents”, exploring how context windows affect costs and how organisations decide what agents can access. He also highlights Steve Sweetman’s Microsoft blog on agent governance, observability, spending limits, model and provider policies, budgets, and ROI.

Alibaba Cloud introduces dedicated cache-hit pricing below the corresponding input token price. Token counts alone cannot explain effective costs: cache status, context length, processing priority, and execution mode also matter.

The episode cites Reuters reports from 24 and 29 September about Anthropic reportedly signing a seven-year, $11.6 billion cloud agreement and anticipating at least $518 billion in AI infrastructure obligations over a decade, around 80% binding regardless of usage. The hosts explore the risks of long-term, largely non-cancellable capacity commitments in a fast-changing market.

Automation and governance

An AWS Cloud Financial Management blog from 10 September outlines four levels of autonomous FinOps. The discussion shifts from whether AI can find savings to which changes organisations will permit it to make. Recommendations, approvals, assisted action, and autonomous remediation carry different operational and financial risks.

An AWS Budgets pattern from 1 September combines Budgets, Identity Center, IAM, and Lambda as an automatic cost circuit breaker. The hosts discuss warnings at 80–90% and stronger intervention at 120%, potentially including hard stops or cheaper models, while protecting legitimate work.

An AWS case study reports $825,000 in annual recurring savings from a four-day FinOps Experience-Based Acceleration, with a path to $1.4 million. Actions included RDS rightsizing, Graviton migrations, EC2 optimisation, removing idle replicas and non-production instances, and improving RI/Savings Plans coverage. The emphasis is on scaling implementation across thousands of accounts.

Oracle’s Sovereign AI eight-layer blueprint by Ravi Tulapati covers infrastructure, GPU orchestration, trusted model supply chains, inference optimisation, managed GenAI services, security and governance, enterprise data grounding, and agent lifecycle operations. The hosts consider it useful beyond Oracle environments.

Storage, compliance, and sustainability

Amazon S3 Object Lock adds event-based variable retention. Objects can remain on hold until an event, such as a contract closing or an audit completing, triggers the required retention period. This can reduce unnecessary over-retention while supporting compliance. Stephen encourages direct discussions with risk and compliance teams instead of assuming every dataset needs maximum retention.

Google Cloud’s Storage Intelligence Advisor reached general availability on 10 September. Stephen argues that storage optimisation often begins with identifying data and its owners. Centralised intelligence can reveal where lifecycle policies and governance need attention.

Google Cloud Carbon Footprint methodology version 17, released on 15 September, updates Scope 1 and Scope 3 allocation factors using 2026 environmental report data. The hosts note that GreenOps baselines and

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Recorded on 30 September 2026, this episode of "What’s New in Cloud FinOps" brings together Frank Contrepois and Stephen Old for a comprehensive roundup of the latest developments across AWS, Google Cloud, Oracle Cloud Infrastructure (OCI), and Alibaba Cloud. With a significant focus on the rapidly evolving world of Generative AI cost management, sustainability, and cloud governance, this instalment was recorded live from the GreenIO Conference foyer in London. Expect a lively, candid flow with real-time analysis.

Generative AI & Machine Learning Cost Control

The episode kicks off with major updates for Amazon Bedrock, SageMaker, and other cloud AI offerings.

• Amazon Bedrock Agent Core Payments (GA): A key discussion point is that agents can now autonomously discover, access, and pay for paid APIs and content. This presents a major governance challenge, risking unmanaged spend and fragmented cost visibility. The hosts stress the need for spending caps, approval workflows, per-agent budgets, and unified cost aggregation.
• Amazon Bedrock Cost Allocation & Anomaly Detection: Bedrock now supports IAM principal cost allocation, allowing organisations to track usage back to specific users and roles in the CUR. Additionally, AWS Cost Anomaly Detection now covers third-party Foundation Models like Anthropic's Claude.
• Bedrock Pricing (OpenAI GPT-5.6): Promotional pricing is available at $4/million input tokens and $20/million output tokens (a claimed 20-33% reduction), valid through at least 21 November 2026.
• Amazon SageMaker: A new guided, low-code/no-code path in SageMaker Studio simplifies finding cost-effective inference configurations for custom models.
• Google Cloud BigQuery: Introduced preview monitoring for data agent performance, latency, and conversation costs through Google Cloud observability.
• Oracle Cloud Infrastructure (OCI): August's AI update expanded hardware choices and on-demand inference for Cohere and Meta models.
• Calculating AI ROI: Frank highlights an AWS article by Adam Richter on presenting AI return on investment. Steve recalls a previous podcast with Adam discussing a Cornell "levelised cost of AI" study, emphasising the need for measurable value.
• From AI Pilots to Production: The hosts discuss how many AI pilots run too long without a clear "exit to value" plan. Frank’s workshops focus on defining proof-of-value criteria and graduation paths to production. Research shows 59% of organisations report increased AI spend wastage, while only 31% have accurate visibility.

Commitments, Pricing Models & The New "SAM" Challenge

A clear trend is the application of traditional cloud commitment models to AI services, creating new challenges where FinOps and Software Asset Management (SAM) collide.

• Google Cloud: Introduced flexible, spend-based Savings Plans for Gemini Enterprise (10% for one year, 20% for three years) and a forthcoming "deferred execution" option offering up to a 50% discount for non-urgent jobs.
• Alibaba Cloud: Launched AI Savings Plans for Model Studio on 28 August 2026, with discounts up to 47%. They also introduced batch inference pricing at a 50% discount.
• The FinOps/SAM Collision: Models like Gemini Enterprise and Azure Copilot Studio blend per-user subscriptions with pay-as-you-go agent workloads. This creates a challenge in determining who owns which piece of the cost and how credits and commitments apply across teams.

Hidden Risks & Governance Gaps

• Third-Party AI EULAs: Stephen highlights a critical risk: when a user accepts the End-User License Agreement (EULA) for a third-party model (e.g., Anthropic on Bedrock), they could be binding their entire organisation to the provider's standard terms without legal or procurement oversight.
• Intellectual Property Risk: Frank points to a recent HBR article discussing how the "how" of AI usage—the prompts and methods—may not be protected, potentially exposing valuable IP.

Cloud Infrastructure & Cost Management Updates

• AWS Compute:
  • R9g/R9gd instances (Graviton 4): AWS claims up to 25% better compute, but Frank's analysis shows an 8-25% price uplift. FinOps takeaway: benchmark workloads before migrating.
  • ECS fractional GPU scheduling: ECS now supports fractional GPU allocations on EC2 g6f, ideal for right-sizing smaller ML/AI workloads and improving utilisation.
  • ElastiCache on Graviton 4: Offers ~40% higher throughput and ~31% better price-performance, but with higher memory costs.
• AWS Database & Analytics:
  • Aurora Serverless: Can now scale to 12 ACU in ~1 second, reducing the need for high steady baselines, but requiring guardrails to prevent cost spikes.
  • RDS for SQL Server BYOM: "Bring Your Own Media" is extended to more regions, requiring careful audit documentation.
  • Oracle AI Database on AWS Exascale: Oracle Exadata DB Services now generally available via AWS, signalling evolving multi-cloud coexistence.
  • AWS Glue 6.0 GA: A ~30% price reduction and runtime upgrades (Spark 4.1, Python 3.13) offer immediate savings opportunities.
  • AWS Glue Data Quality: Anomaly detection is now free with an improved "observation mode".
  • Amazon Kinesis: Can now deliver data directly to S3 in Iceberg format, potentially lowering delivery and query costs.
• AWS Billing & Lambda:
  • AWS Data Exports: Now supports SQL-based row filtering at the source to create pre-filtered reports.
  • AWS Billing Managed Dashboards: An official, pre-configured version of the popular open-source Cost Intelligence Dashboards.
  • AWS Lambda: Recursive loop detection is now available in all commercial regions, reducing the risk of runaway bills.
• Google Cloud:
  • BigQuery: Offers cost-effective cross-cloud connections (preview) but restricts Graph processing to Enterprise/Enterprise Plus editions.
  • Billing Reports: A new "originating products" filter helps trace costs back to their source.
  • Semantic Tags: A preview feature to automatically propagate application context to resources for better cost allocation.
  • Storage Rapid Cache: Now allows selective ingest filtering to reduce expenditure.
• Oracle Cloud Infrastructure (OCI):
  • Autoscaling for Red Hat OpenShift: New capability driven by licensing alignment with Red Hat/IBM.
  • Service Limits: OCI has streamlined the service limit increase experience in the console.

Sustainability Updates

• New Availability Zones: New zones in London (EU-West-2D) and Las Vegas seem focused on AI training, raising questions about sustainability trade-offs.
• Google Cloud Carbon Methodology: A refresh offers more granular certificates and hourly electricity matching for better precision.
• Green Software Foundation: The "Beyond Watts" paper encourages evaluating environmental impact beyond just electricity consumption.

Productivity AI

• Amazon Q for Microsoft 365: Now generally available for Excel, Word, etc., bringing AI into daily workflows but raising data governance questions.

Referenced Resources & Links

• Frank’s instance price/performance comparison tool: https://aws.frankcontrepois.com/comparisons/

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July Episode — What's New in Cloud FinOps

Episode Summary
In this July episode of What's New in Cloud FinOps, Frank and SteveO cover a packed set of cloud and AI cost-management updates across AWS, Azure, Google Cloud, Oracle, Alibaba, and OpenAI. The conversation focuses on how cloud vendors are changing pricing models, improving observability, and adding new ways to optimize compute, storage, and AI workloads.

The standout theme is that AI and cloud economics are becoming more dynamic: pricing is shifting by usage pattern, time of day, workload type, and capacity model. The hosts also dig into how organizations can use these changes to improve governance, control costs, and make smarter architecture decisions.

Top Topics Covered

• AWS EKS and ECS GPU management fee reductions
• Amazon CloudWatch intelligent tiering for logs
• Amazon S3 removing the 30-day minimum for storage class transitions
• AWS Billing and Cost Management adding a cost efficiency widget
• AWS Data Exports adding standardized Bedrock metadata
• AWS Lambda publishing logs for managed capacity providers
• Azure reservation exchange changes and legacy VM RI renewals
• Alibaba Cloud time-of-day pricing for frontier AI models
• Alibaba model routing reference architecture
• OpenAI GPT model price cuts and Bedrock matching those rates
• Oracle bringing Gemini models into OCI
• Google Data Stream free tier for CDC writes
• Amazon OpenSearch Service optimized for log analytics
• Microsoft Marketplace single-click SaaS purchases
• AWS sustainability dashboard adding water withdrawal data

Key Takeaways
AI pricing is getting more sophisticated.

Providers are increasingly using variable pricing, off-peak discounts, and routing strategies to steer usage and improve margins.
Cloud optimisation is moving deeper into the platform.

Vendors are surfacing more native tools for cost visibility, efficiency scoring, and policy-driven automation.
Storage and logging are becoming more cost-aware.

New features in S3, CloudWatch, and OpenSearch help teams store more data for less while keeping observability usable.
Governance and procurement remain critical.

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Title: What's New in Cloud FinOps - June 2026

Hosts: Frank Contrepois and SteveO

Summary

In this episode, Frank and SteveO navigate through the latest cloud offerings and AI advancements, revealing how these updates impact performance, costs, and operational strategies across Azure, AWS, and AI applications. Stay tuned for insights into new VM generations, cost management tools, and cutting-edge AI features.

Key Topics:

• Azure's new Cobalt 200V and 100V VMs deliver up to 50% better CPU performance
• Introduction of AWS's Metal 48XL/96XL and enhanced EC2 instances with sixth-generation Intel Xeon
• Latest AWS Graviton 5 processors offering up to 25% better compute performance
• Enhanced Amazon EC2 G7 instances powered by Nvidia RTX Pro 4500
• AWS Cost Management updates, including automatic cost anomaly investigations and new billing tools
• AWS's support for region-agnostic throughput reservations in Azure
• The rise of AI and automation in cost optimization: new tools, models, and use cases
• Cloud vendors' announcements on energy-efficient storage, reserved pricing, and billing analysis tools

Timestamps:
00:00 - Cloud news roundup: performance boosts in Azure VM series
00:20 - Azure's new Cobalt 200V VMs: performance and AI workload optimization
01:32 - AWS launches Metal 48XL/96XL: CPU advancements and network enhancements
02:50 - Introduction of AWS M9G/M9GD instances with AWS Graviton 5 processors
04:36 - AWS's latest EC2 G7 instances with Nvidia RTX GPUs for AI and visual workloads
05:43 - Cost efficiency improvements with new pricing models and snapshot billing
09:28 - Redshift advances with manual snapshot cost reductions
10:12 - AI models on Bedrock: GPT 5.5, Codex, and OpenAI integrations
12:24 - Innovations in cloud billing: cost explorer, cost anomaly detection, and billing account tools
13:00 - Cost & Usage Report 2.0 enhances S3, Athena, and Redshift integration
14:23 - Google Cloud billing updates: report export improvements and new filtering options
15:19 - AWS's right-sizing and resource optimization enhancements
16:12 - Cost explorer AI integrations and automated cost investigations
17:10 - New AI-powered tools for cost anomaly root-cause analysis
18:16 - Multi-project billing views and resource management in AWS
19:04 - Advanced export configurations to streamline billing data handling
20:06 - Google Cloud's spot VM real-time availability features
21:36 - Enhanced tagging, resource management, and API capabilities in AWS and Google Cloud
24:11 - Azure's VM retirements, storage, and reservation updates
26:15 - Redshift's new upfront pricing options for reserved instances
27:35 - Global provisioned throughput reservations now regional in Azure for flexibility
28:44 - Storage charges optimizations and vector query cost reductions on S3
30:10 - Using finops.frankcontrepois.com for AI-driven FinOps
34:08 - The importance of separating AI from automation in cloud efficiency strategies
36:17 - Resources like the Phoenix Project and The Goal for understanding process optimization and AI impact
37:34 - Support for new resource types and idle recommendation expansion in AWS Compute Optimizer
38:50 - Cost and performance insights into specific resource wastage
39:16 - AWS's State of Cost Efficiency Report: benchmarking and industry insights
40:52 - AWS FinOps agents preview: automated cost and anomaly management workflows
42:23 - Programmatic savings plan management and AWS workload optimization
43:47 - Cost attribution and telemetry for large language models (LLMs) on Bedrock
44:10 - AWS WAF's new AI traffic monetization capabilities for API access control
45:45 - Azure Cosmos DB's new cost estimator tool for pre-provisioning modeling
46:52 - Top three news picks: upcoming cloud innovations and AI advances
47:35 - The growing role of FinOps and AI operational tools in cloud cost management

Resources:
FinOps tool
The Phoenix Project
The Goal by Eliyahu M. Goldratt

Connect with the Hosts:
Frank - LinkedIn
SteveO - LinkedIn

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Summary: In this episode, Frank and SteveO discuss the latest updates in cloud technology for May 2026. They cover AWS's new multi-cloud connectivity with Oracle Cloud Infrastructure, the general availability of Amazon EC2 M3 Ultra Mac instances, and Microsoft's release of V7 VMs powered by Intel Xeon processors. The hosts also delve into Amazon Bedrock's expanded support for request-level usage attribution and service quotas, as well as AWS Marketplace's new programmatic procurement capabilities. The episode wraps up with insights from the FinOps X conference and a discussion on cost management strategies in cloud services.

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What's New in Cloud FinOps: May 2026 Monthly Recap

In this combined monthly recap for May 2026, Frank Contrepois and Stephen Old dive into a vast array of updates across AWS, Google Cloud, and Azure, with a special focus on the evolving landscape of AI FinOps, hybrid cloud challenges, and a barrage of storage news.

The Expanding Scope of FinOps: From Data Centre to AI

The discussion opens by exploring the expansion of FinOps beyond the public cloud to encompass on-premise data centres, software, AI, and sustainability. A central theme is the application of the FinOps Open Cost and Usage Specification (FOCUS) to on-premise environments. Stephen shares firsthand experience transposing software data into FOCUS to create a converged platform, highlighting the fundamental data challenges, from ingesting contract data to managing the high velocity of cloud data.

The conversation then shifts to the burgeoning role of AI, noting its inclusion alongside SaaS and professional services in the modern FinOps scope. This introduces new forecasting challenges, as traditional 18-month budget cycles clash with the rapid pace of weekly AI model releases.

A critical point is also raised regarding sustainability. The hosts discuss Amazon's board rejecting a shareholder proposal for detailed climate disclosures, which poses a significant challenge for companies needing granular data for CSRD and SEC compliance.

Major Cloud Updates: April 2026

AI & FinOps Visibility:

A major theme is the improvement in attributing AI spend. A game-changing update from AWS means Bedrock API calls now automatically record the IAM identity (user or role) of the caller directly into CUR 2.0 and Cost Explorer. This eliminates the complex need to reconcile CloudTrail logs to determine who is driving Bedrock costs.

Similarly, Amazon Q is now embedded in the AWS Cost Explorer, allowing users to ask natural language questions about their spending (e.g., "Why did my RDS costs spike last month?"). This conversational analysis approach comes with a free tier of 50 queries per month.

On the Google Cloud side, a new billing overview widget for Gemini and Vertex AI spend is now in preview. Google is also introducing a "FinOps Explainability Agent," an autonomous AI agent to investigate AI cost drivers, and "Spend Caps" (Private Preview) for services like AI Studio and Vertex AI, which provide crucial cost control by pausing API traffic when a budget is hit.

For those managing GPU workloads, Amazon ECS managed instances now support NVIDIA GPU metrics in CloudWatch Container Insights, enabling real-time visibility into GPU utilisation and health to optimise expensive accelerated computing.

Cost & Usage Reporting (CUR) Enhancements:

There are hints of a potential enhancement to AWS CUR 2.0, which could see new columns added to directly link API calls with costs, revolutionising cost allocation. AWS has also introduced:

• Scheduled Email Delivery for Billing Dashboards: Securely send reports to stakeholders without console access.
• Billing Conductor Pass-Through Plan: Simplifies centralised billing for billing transfer users.
• Cost Optimization Hub CSV Downloads: Easily export savings recommendations.
• Find out how to leverage CUR for security: "Identifying security risks using AWS cost and usage report data"

Compute & Database Innovations:

• AWS: Released a wave of 8th Generation Intel Instances (C8i, M8i, R8i and network-optimised versions) powered by custom 6th Gen Xeon processors. EC2 Capacity Manager also now supports tag-based dimensions, allowing for more granular capacity optimisation. Amazon Aurora Serverless now boasts up to 30% better performance and, crucially, scales down to zero, a cost-effective option for unpredictable agentic AI workloads.
• Google Cloud: At Google Cloud Next, they announced both ends of the performance spectrum. The 8th Generation TPUs (v8t for training, v8i for inference) offer massive scale and performance-per-dollar improvements. In a move to democratise access, Google also made fractional GPUs (1/2, 1/4, or 1/8) on the G4 series generally available, a game-changer for cost-effectively running smaller workloads. The GKE workload recommender is also now integrated into the FinOps Hub.
• Azure: Now supports NVIDIA's powerful H100 and H200 GPUs on Azure Red Hat OpenShift (ARO) for large-scale AI/HPC workloads. For database users, the GA of Premium SSD v2 for Azure Database for PostgreSQL promises significantly higher IOPS and better price-performance.

A Deep Dive into Azure Storage:

The episode covers an "overload" of Azure storage updates with significant FinOps implications:

• Minimum Billable Object Size: From 1st July 2026 for new accounts (and 2027 for all), objects smaller than 128KB in cool, cold, and archive tiers will be billed as if they are 128KB.
• Smart Tier for Azure Blob & ADLS (GA): To mitigate the above, this feature automatically tiers data based on access patterns but introduces a monitoring fee for objects over 128KB, creating a new optimisation puzzle.
• Azure NetApp Files (ANF) Ransomware Protection: Now GA and included as part of the service at no extra charge.

Finally, the hosts tackle "The Big Silence on Memory Prices," noting that despite DDR memory prices soaring 300-400% from mid-2025 lows, the hyperscalers have remained silent, absorbing the cost and making it difficult for smaller providers to compete.

Explore the official announcements:

• AI Bill of Materials Whitepaper: www.wiz.io/go/ai-security/ai-bill-of-materials
• AWS Article on Amazon Q: https://aws.amazon.com/blogs/aws-cloud-financial-management/transforming-finops-with-the-latest-amazon-q-cost-capabilities/ 

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This month, Frank Contrepois and Steven Old interview Yasmin Rajabi.

A few weeks ago, we picked a topic. Then, just five minutes before recording, we all changed our minds. In the end, we didn’t discuss any of the planned subjects and went with the flow. And what an amazing flow it was!

This is one of the best interviews we've ever done. It was engaging, sparked memories, and created new content for all FinOps practitioners listening.

Yasmin will need to return soon so we can try to discuss a set topic... or not.

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Frank and Stephen discuss the latest updates in cloud technology, focusing on AWS and Azure. They cover topics like EC2 Fleet's new interruptible capacity reservation, Azure pricing challenges, and the retirement of certain virtual machine sizes. They also explore the benefits of Google's TPU 7x for AI training and the introduction of AWS's Sustainability Console for carbon emission tracking. The conversation touches on the importance of risk management in business decisions and the evolving landscape of cloud billing and sustainability.

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In this episode of What’s New in Cloud FinOps?, Frank and Stephen break down the latest shifts in cloud usage, pricing, and governance so you don’t have to read the release notes from vendor blog posts.

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This episode covers the latest updates in cloud computing, including AWS Spot Interruption metrics, new EC2 instances, Azure and GCP enhancements, and cost management innovations. Perfect for cloud professionals seeking actionable insights and industry trends.
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Key topics:

• AWS Spot Interruption Metrics
• New EC2 Memory-Optimized Instances
• Azure and GCP Cloud Enhancements
• Cost Management and Optimization Strategies
• Capacity Constraints and AI Impact