What's new in Cloud FinOps?

Send us a textIn this episode of What's New in Cloud FinOps, Stephen Old and Frank Contrepois talk about the latest in cloud computing in May 2025. They focus on Azure, AWS, and GCP. They share their experiences at FinOps X (FOX) and discuss new features and public previews. They also explore topics like database innovations, cost management, AI integration, and sustainability in cloud services. Their conversation shows how cloud technology is evolving and why it's important to stay updated on new developments.Link to some videos from MicrosoftMicrosoft Cost Management—Overview in the Azure portal     Microsoft Cost Management—Cost Analysis in the Azure portal (part 1)Microsoft Cost Management—Cost Analysis in the Azure portal (part 2)Microsoft Cost Management—Creating Budgets and AlertsMicrosoft Cost Management—Exporting your Cost Data with Scheduled ExportsManage Azure OpenAI Service Provisioned Reservations

Send us a textApril 2025 news. A lot of news for you, dear listener, from Google, AWS and AzureTakeaway by the aiThe FinOps News podcast targets hardcore FinOps enthusiasts.Conflict can lead to better team dynamics and outcomes.Azure's VM hibernation feature offers cost-efficient workload management.Amazon EC2 introduces high-performance storage optimized instances.Bare metal instances provide significant performance improvements.Prompt optimization in Amazon Bedrock enhances AI model performance.AWS Database Migration Service now supports automatic storage scaling.Cloud gaming may benefit from new GPU instance offerings.The importance of feedback in improving cloud services is emphasized.The podcast aims to provide in-depth insights into cloud technology. Amazon S3 has significantly reduced its storage and request prices.Google Cloud's FinOps Hub 2.0 offers new tools for cost management.GKE now provides insights to optimize resource requests and limits.Azure AKS cost recommendations help identify savings opportunities.Google Cloud's backup services now support DB2 databases.Amazon Redshift introduces serverless reservations for cost predictability.AWS CodeBuild enhancements allow for better resource configuration.Microsoft Cost Management has improved export functionalities.Microsoft Copilot in Azure offers tailored prompts for cost analysis.Azure Static Web Apps will discontinue dedicated pricing plans.

Send us a textIn this episode, Frank and Stephen talk with Udam about the changing world of FinOps. They focus on the challenges organizations face in managing cloud costs and data accuracy. Udam shares insights from his vast experience in the field. He highlights the need for data standardization, the role of data engineering, and ongoing investment in FinOps practices. The conversation also explores innovative solutions like Stitcher AI, which aim to simplify data management and improve decision-making in financial operations. The speakers dive into the complexities of FinOps, stressing the need to understand fully loaded costs. They discuss engaging teams in cost allocation and the importance of contextualized data for informed decisions. They address issues in traditional cost management and how new tools can democratize access to financial insights. These tools help organizations of all sizes optimize cloud spending and boost operational efficiency.Sound Bites"We don't keep any of the data.""We have to be really accurate with our costs.""You cost double your salary to the company""Cost allocation is hugely important for FinOps""FinOps has to be a bi-directional interaction"

Send us a textIn this episode of What's New in Cloud Phenops, Stephen Old and Frank discuss the latest updates in cloud computing, focusing on Azure, Google Cloud, and AWS. They cover the retirement of certain Azure virtual machines, the introduction of serverless GPUs, and the benefits of Amazon Bedrock for cost transparency. The conversation also touches on new features for Azure databases, insights from a Forrester study on Spanner, and the importance of calculating AI costs. Additionally, they discuss licensing changes for Amazon FSX, tiered storage for Spanner, and the deprecation of the AWS connector to Azure. The episode concludes with a look at sustainability efforts and upcoming events in the cloud computing space.takeawaysServerless GPUs enable on-demand AI workloads with automatic scaling.Amazon Bedrock introduces real-time cost transparency for custom models.Physical snapshots for Azure databases enhance backup flexibility.Forrester study shows significant ROI with Spanner.Understanding AI costs on Google Cloud is crucial for budgeting.Amazon FSX for NetApp removes SnapLock licensing fees.Tiered storage for Spanner optimizes cost and performance.AWS connector to Azure is deprecated, focusing on native solutions.Azure OpenAI service offers discounts for provisioned reservations.

Send us a textIn this conversation, Amit Saar shares his journey from software engineering at Microsoft to founding OpenOps. He focuses on the challenges and solutions in FinOps. He highlights the need for automation, accountability, and balancing innovation with governance in managing cloud costs. Amit points out the fatigue that engineering managers face due to overwhelming demands. He stresses the need for better tools and practices to streamline FinOps processes. The discussion also covers the challenges of automating FinOps, the role of no-code platforms, and the importance of community engagement through open sourcing.Topics include the fragmentation of systems in enterprises and the advantages of a no-code approach for automation. Amit discusses monetization strategies for sustaining an open-source model. The conversation wraps up with practical advice on getting started with OpenOps.

Send us a textIn this episode, Stephen Old and Frank Contrepois discuss the latest updates in cloud FinOps. With news from AWS, Google and Azure, including enhanced computing capabilities, database updates, and pricing changes.For once there are also some sustainability news. That makes me happy!

Send us a textWe discussed the challenges of working with time series data, particularly in the context of machine learning and AI, highlighting the complexity and the need for automation in feature engineering. The importance of balancing accuracy and complexity in model creation was emphasized, with a focus on avoiding overfitting and ensuring models remain effective in real-world applications. The potential integration of business context data, such as sales data, with cloud consumption data to enhance anomaly detection and forecasting models was proposed. The discussion touched on the economic value of anomaly detection, with a focus on proving that early detection can lead to significant cost savings. The target audience for the anomaly detection system was identified as FinOps managers, who would use the system to manage cloud-related financial topics and coordinate with engineers to address anomalies. 

Send us a textJanuary 2025 FinOps news.Instances/Computehttps://cloud.google.com/blog/products/compute/announcing-smaller-machine-types-for-a3-high-vms - The A3 Ultra machine type is available in the following region and zone: St. Ghislain, Belgium, Europe - europe-west1-bhttps://cloud.google.com/blog/products/compute/first-google-axion-processor-c4a-now-ga-with-titanium-ssd - Google Axion Processor-based C4A VMs with Titanium SSD are now generally available. Part of our general-purpose machine family, these instances come with up to 6 TiB of Titanium SSD disks. Titanium SSD is our latest generation of Local SSD. It uses Titanium I/O offload processing and offers enhanced SSD security, performance, and management.Compute Engine - Generally available: Managed instance groups (MIGs) let you create pools of suspended and stopped virtual machine (VM) instances. You can manually suspend and stop VMs in a MIG to save on costs, or use suspended and stopped pools to speed up scale out operations of your MIG. For more information, see About suspending and stopping VMs in a MIG.Data/DBs/AIAzure OpenAI provisioned reservations (June - but not sure we mentioned it)With the introduction of 1-month and 1-year Provisioned Reservations, businesses that commit to using Azure OpenAI on a scale can enjoy substantial discounts compared to the standard pay-as-you-go pricing. You can manage these reservations in Cost analysis in the same way as any other reservation.For further details on how to purchase and manage these reservations, please refer to the article below: Save costs with Microsoft Azure OpenAI Service Provisioned Reservations  Storagehttps://aws.amazon.com/about-aws/whats-new/2025/01/amazon-s3-metadata-generally-available Generally available: Azure NetApp Files now supports minimum volume size of 50 GiB.Generally Available: Azure Files provisioned v2 billing model for HDD (Standard) - (Added to Roadmap 8th Jan 2025 - but released in October 24) The provisioned v2 model for Azure Files HDD (standard) pairs predictability of total cost of ownership with flexibility, allowing you to create a file share that meets your exact storage and performance requirements. Provisioned v2 shares enable independent provisioning of storage, IOPS, and throughput. In addition to predictable pricing and flexible provisioning, provisioned v2 also enables increased scale and performance, up to 256 TiB, 50,000 IOPS, and 5 GiB/sec of throughput; and per share monitoring. Provisioned v2 is generally available in a subset of regions. For the current list of available regions, see provisioned v2 availability.Visibility (Billing conductor - Tags - cost categories)New fields for cost allocation (Enterprise Agreement customers)You can use different le

Send us a textIn this chat, Frank, Stephen, and Anthony share their thoughts on how cloud computing and AI have evolved from 2024 to 2025. They discuss the growth in the GPU market and how views on cloud versus on-premises solutions have changed. They also talk about the quality and performance of AI models and consider the environmental impact of AI. The group highlights the need for specialized AI models and the efficiency of the hardware used in AI applications. They wrap up with some insights into future trends in cloud instances and pricing.In their chat, the speakers look at how AMD and Intel processors perform. They also discuss the future of ARM and Graviton technologies. Finally, they touch on the shifting world of cloud computing. They examine the competition among major cloud providers, such as AWS and Microsoft. They also highlight how important it is to be transparent in cloud operations, especially when comparing European and American providers. Here are the key takeaways.The GPU market saw a significant increase in providers in 2024.Many organisations are reconsidering their cloud strategies due to pricing and privacy concerns over AI.AI adoption is still in its early stages for many companies.Quality of AI models has plateaued, with a few major players dominating the market.Training models in the cloud may not be the best solution for everyone.Specialised AI models are becoming increasingly important.The environmental impact of AI and cloud computing is a growing concern.Efficiency in hardware usage is crucial for AI applications.Transparency in cloud provider operations varies significantly between vendors.The cloud market is stabilizing, with slower growth rates observed.Energy consumption and cost are critical factors.Benchmarking is essential for understanding cloud performance.The competitive landscape among cloud providers is shifting, with pricing diverging.

Send us a textA little late, but as they say, better late than never. You can provide feedback, ideas, proposals for interviews at send us an email at podcast@finopsguys.co.ukHave a fantastic 2025 and January