ProsperOps

Visibility is where good FinOps starts. It is not where it ends. A lot of teams have invested heavily in dashboards, tagging taxonomies, and allocation reports. They can tell the CFO exactly which service drove last month's cost spike. Yet, the bill is still high. We published a piece on why this keeps happening, and the distinction it draws is worth internalizing: visibility tools read billing APIs. They surface problems. Most vendors stop there because read access is low-risk and write access carries real financial consequences if something goes wrong. That is a reasonable engineering boundary. But it means 𝘁𝗵𝗲 𝗿𝗲𝗽𝗼𝗿𝘁𝗶𝗻𝗴 𝗹𝗮𝘆𝗲𝗿 𝗰𝗮𝗻 𝗼𝗻𝗹𝘆 𝘁𝗲𝗹𝗹 𝘆𝗼𝘂 𝘄𝗵𝗮𝘁 𝗵𝗮𝗽𝗽𝗲𝗻𝗲𝗱, 𝗻𝗼𝘁 𝗰𝗵𝗮𝗻𝗴𝗲 𝗶𝘁. Worth reading if your team is spending more time analyzing the bill than improving it. 👉 https://bit.ly/4xh1Zmy #FinOps #CloudCostOptimization #CloudFinOps #ProsperOps

If you are evaluating a VM migration on Google Cloud, on-demand hourly rate is the wrong place to start. Read on👇 We built a 𝗳𝗿𝗲𝗲 𝗚𝗼𝗼𝗴𝗹𝗲 𝗩𝗠 𝗣𝗿𝗶𝗰𝗲 𝗖𝗼𝗺𝗽𝗮𝗿𝗶𝘀𝗼𝗻 𝘁𝗼𝗼𝗹 that lets you compare price-performance across machine families, generations, regions, and custom configurations in one place, including discount eligibility and commitment impact. Worth bookmarking before your next sizing conversation. Try it free: https://bit.ly/4xmCrVc #GoogleCloud #PlatformEngineering #FinOps #ProsperOps 🖖

In our 𝟮𝟬𝟮𝟲 𝗔𝘇𝘂𝗿𝗲 𝗖𝗼𝗺𝗽𝘂𝘁𝗲 𝗥𝗮𝘁𝗲 𝗢𝗽𝘁𝗶𝗺𝗶𝘇𝗮𝘁𝗶𝗼𝗻 𝗜𝗻𝘀𝗶𝗴𝗵𝘁𝘀 𝗥𝗲𝗽𝗼𝗿𝘁, we also looked at the allocation of different types of commitments and terms in organizations’ portfolios: 3-year commitments now make up a larger share of Azure compute portfolios. •  Average 3-year Reservation allocation: 𝟰𝟰% → 𝟰𝟵% of commitment spend. •  Average 3-year Savings Plan allocation: 𝟭𝟱% → 𝟮𝟬% Longer terms carry better discounts, but lock organizations into usage assumptions for years. The shift raises the stakes for matching commitments to usage. Without automation and the right strategy, rate optimization can be time-consuming and error-prone. 👉 Full report: https://bit.ly/4bIcfw3 #FinOps #Azure #CloudCommitments #RiskManagement #ProsperOps

Most FinOps practitioners didn't set out to manage three clouds. One team adopted AWS early, another spun up Azure for AI, someone chose GCP for analytics. Now a single product runs across all three and the CFO wants to know what it cost last quarter. 🤯 That question is harder to answer than it sounds, so we published a thorough breakdown of exactly why. A few standouts:  • Strong tagging within each cloud still leaves you with three separate billing silos. It tells you where costs are. It does not tell you who owns the egress charge when a dataset crosses a cloud boundary  • A single user transaction can touch storage in AWS, AI processing in Azure, and analytics in GCP, each billed differently, with no clean way to attribute the cost to one team  • Commitment instruments across the three providers do not map cleanly onto each other, which forces manual reconciliation every time workloads shift What's the takeaway? The highest cost of manual multi-cloud commitment management is often not the missed discount rate. 𝗜𝘁 𝗶𝘀 𝘁𝗵𝗲 𝘁𝗶𝗺𝗲 𝘆𝗼𝘂𝗿 𝗯𝗲𝘀𝘁 𝗙𝗶𝗻𝗢𝗽𝘀 𝗽𝗿𝗮𝗰𝘁𝗶𝘁𝗶𝗼𝗻𝗲𝗿𝘀 𝗮𝗿𝗲 𝘀𝗽𝗲𝗻𝗱𝗶𝗻𝗴 𝗼𝗻 𝗿𝗲𝗽𝗲𝘁𝗶𝘁𝗶𝘃𝗲 𝗿𝗲𝗰𝗼𝗻𝗰𝗶𝗹𝗶𝗮𝘁𝗶𝗼𝗻 𝘄𝗼𝗿𝗸 𝗶𝗻𝘀𝘁𝗲𝗮𝗱 𝗼𝗳 𝗳𝗼𝗿𝗲𝗰𝗮𝘀𝘁𝗶𝗻𝗴, 𝗮𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲 𝗿𝗲𝘃𝗶𝗲𝘄𝘀, 𝗼𝗿 𝘂𝗻𝗶𝘁 𝗲𝗰𝗼𝗻𝗼𝗺𝗶𝗰𝘀 𝗺𝗼𝗱𝗲𝗹𝗶𝗻𝗴. 👉 Read more: https://bit.ly/4xrac7W #FinOps #MultiCloud #CloudCostOptimization #ProsperOps

We're #hiring a new Cloud Billing & Optimization Specialist in United States. Apply today or share this post with your network.

We recently published our 𝟮𝟬𝟮𝟲 𝗔𝘇𝘂𝗿𝗲 𝗖𝗼𝗺𝗽𝘂𝘁𝗲 𝗥𝗮𝘁𝗲 𝗢𝗽𝘁𝗶𝗺𝗶𝘇𝗮𝘁𝗶𝗼𝗻 𝗜𝗻𝘀𝗶𝗴𝗵𝘁𝘀 𝗥𝗲𝗽𝗼𝗿𝘁, and here's one of eight key observations from the data: 𝗔𝘇𝘂𝗿𝗲 𝗼𝗿𝗴𝗮𝗻𝗶𝘇𝗮𝘁𝗶𝗼𝗻𝘀 𝗮𝗿𝗲 𝗹𝗲𝗮𝗻𝗶𝗻𝗴 𝗳𝘂𝗿𝘁𝗵𝗲𝗿 𝗶𝗻𝘁𝗼 𝗥𝗲𝘀𝗲𝗿𝘃𝗮𝘁𝗶𝗼𝗻𝘀 — 𝗮𝗻𝗱 𝗹𝗼𝗻𝗴𝗲𝗿 𝘁𝗲𝗿𝗺𝘀. •  📈 Rising: 3-year and 1-year VM Reservations, then 3-year Savings Plans. •  📉 Declining: 1-year Savings Plans and 1-year App Service Reservations. What does this mean? 𝗢𝗿𝗴𝗮𝗻𝗶𝘇𝗮𝘁𝗶𝗼𝗻𝘀 𝗮𝗽𝗽𝗲𝗮𝗿 𝘁𝗼 𝗯𝗲 𝗽𝗿𝗶𝗼𝗿𝗶𝘁𝗶𝘇𝗶𝗻𝗴 𝗱𝗲𝗲𝗽𝗲𝗿 𝗱𝗶𝘀𝗰𝗼𝘂𝗻𝘁𝘀 𝗳𝗿𝗼𝗺 𝗹𝗼𝗻𝗴𝗲𝗿 𝗰𝗼𝗺𝗺𝗶𝘁𝗺𝗲𝗻𝘁𝘀 — 𝗮 𝘁𝗿𝗮𝗱𝗲-𝗼𝗳𝗳 𝘄𝗶𝘁𝗵 𝗵𝗶𝗴𝗵𝗲𝗿 𝗰𝗼𝗺𝗺𝗶𝘁𝗺𝗲𝗻𝘁 𝗿𝗶𝘀𝗸, covered later in the report. Read more: https://bit.ly/4yX2aW2 #FinOps #Azure #ReservedInstances #CloudCostManagement #ProsperOps

If your Google Cloud estate is still on N1 or N2, the case for moving to N4 has gotten harder to ignore. 👇 The newer machine families deliver more throughput per vCPU and per GB of RAM. For the right workloads, that means running the same compute on fewer, smaller instances. But the commitment side of the equation is where many teams leave additional savings on the table. N4 and N4D open up resource-based CUDs, which on stable, predictable workloads can add roughly 9% in savings on top of what spend-based Flex CUDs deliver. The catch is timing! 😖 Locking in resource-based CUDs before the new fleet stabilizes creates lock-in risk. The better approach is to build coverage gradually as usage patterns settle, and let automation handle the ongoing rebalancing. We put together a practical migration guide covering performance benchmarking, licensing considerations, storage efficiency, AMD compatibility checks for N4D, and how to sequence your commitment strategy through the transition. 🔗: https://bit.ly/4pWVcMz #GoogleCloud #PlatformEngineering #FinOps #ProsperOps

🗓️ Microsoft is ending Azure Reservation exchanges — and it's worth understanding why and what it means for you. Our 𝗖𝗼-𝗳𝗼𝘂𝗻𝗱𝗲𝗿 & 𝗖𝗵𝗶𝗲𝗳 𝗣𝗿𝗼𝗱𝘂𝗰𝘁 𝗢𝗳𝗳𝗶𝗰𝗲𝗿 Erik Carlin wrote an in-depth breakdown that covers everything you need to know about this change. 🔎 He discusses why Microsoft is doing this, objectively analyzes implications on savings and flexibility, and details some practical next steps. 🤖 𝗦𝗲𝗲 𝗼𝘂𝗿 𝗽𝗲𝗿𝘀𝗽𝗲𝗰𝘁𝗶𝘃𝗲: https://bit.ly/4gjFKXr #FinOps #Azure #Reservations #Exchanges #Endoflife #SavingsPlans #ProsperOps

In our recently published 𝟮𝟬𝟮𝟲 𝗔𝘇𝘂𝗿𝗲 𝗖𝗼𝗺𝗽𝘂𝘁𝗲 𝗥𝗮𝘁𝗲 𝗢𝗽𝘁𝗶𝗺𝗶𝘇𝗮𝘁𝗶𝗼𝗻 𝗜𝗻𝘀𝗶𝗴𝗵𝘁𝘀 𝗥𝗲𝗽𝗼𝗿𝘁, we also looked at usage of commitments: Fewer organizations are going uncommitted on Azure compute. 𝟴𝟰% of billing scopes used Reservations and/or Savings Plans in H1 2026, up from 𝟳𝟲%. •  Both RIs and SPs: 𝟯𝟲% → 𝟰𝟭% •  RI-only: 𝟯𝟰% → 𝟯𝟲% •  SP-only: 𝟲% → 𝟳% Details: https://bit.ly/4w59yvv #FinOps #Azure #CloudCommitments #ReservedInstances #SavingsPlans #ProsperOps

Roughly 𝟴𝟱% of the Google Cloud instances we manage are still running on N1, N2, or N2D. That is a meaningful optimization gap, and it runs deeper than most teams realize. Migrating to N4 or N4D is not just a performance upgrade. It is also a 𝗱𝗶𝘀𝗰𝗼𝘂𝗻𝘁 𝘂𝗻𝗹𝗼𝗰𝗸. Stable N4 workloads become eligible for resource-based CUDs, which on a 3-year term can deliver roughly 𝟵% more in savings compared to spend-based Flex CUDs. 𝗕𝗲𝘁𝘁𝗲𝗿 𝗽𝗿𝗶𝗰𝗲-𝗽𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝗻𝗰𝗲 𝗽𝗲𝗿 𝗰𝗼𝗿𝗲, 𝗯𝗲𝘁𝘁𝗲𝗿 𝗿𝗮𝘁𝗲𝘀 𝗼𝗻 𝘁𝗵𝗮𝘁 𝘂𝘀𝗮𝗴𝗲. The blog covers what to actually evaluate before you migrate:    • Workload benchmarking  • Licensing implications  • Regional availability  • Storage efficiency Plus, how to sequence commitment coverage as the new fleet stabilizes. One tool worth bookmarking: we built a free 𝗚𝗼𝗼𝗴𝗹𝗲 𝗩𝗠 𝗣𝗿𝗶𝗰𝗲 𝗖𝗼𝗺𝗽𝗮𝗿𝗶𝘀𝗼𝗻 𝘁𝗼𝗼𝗹 to help you compare price-performance across regions, machine families, and custom configurations before you commit.🔗: https://bit.ly/4yWzxbc Read the full guide: https://bit.ly/454PgYj #GoogleCloud #PlatformEngineering #FinOps #VMModernization #ProsperOps