Tag: FinOps
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FinOps Tooling, Maturity and the Roadmap That Follows (Cloud FinOps Series, Part 20)
Three organisations bought the same cost platform and got three different outcomes. Here is how to choose FinOps tooling, read the maturity model honestly, and build a twelve month roadmap that ends in decisions rather than dashboards.
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How to Build a FinOps Team and an Operating Model That Holds (Cloud FinOps Series, Part 19)
Tooling does not decide whether a FinOps practice survives. Reporting lines, decision rights and cadence do. A practitioner guide to FinOps team roles, centralised versus hub and spoke structures, sizing, and where to report.
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FinOps Automation With Guardrails, Policy and Infrastructure as Code (Cloud FinOps Series, Part 18)
Alerts tell you money already left. Policy stops it leaving. A practitioner guide to cost guardrails on AWS, Azure and GCP, plus cost checks in the pull request, and where automation goes wrong.
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FinOps for AI and GPU Spend, Tokens and Utilisation (Cloud FinOps Series, Part 17)
A GPU sitting at 30 percent utilisation costs more per useful hour than the provider you rejected for being expensive. Here is how AI spend actually meters, and which levers move it.
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Serverless and Managed Service Cost on AWS, Azure and GCP (Cloud FinOps Series, Part 16)
Two near identical functions, twenty times the cost. Billing granularity, not the published rate, decides what short serverless functions cost, and concurrency moves the number further than any platform choice.
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FinOps Framework Principles, Personas and Phases Explained (Cloud FinOps Series, Part 3)
The FinOps Framework is not a maturity checklist you work through once. It is a set of principles, personas, domains and a three phase loop you run continuously, and knowing which piece to reach for is most of the skill.
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What FinOps Actually Is, and What It Is Not (Cloud FinOps Series, Part 1)
FinOps is not a cost cutting project and it is not a dashboard. Here is the actual definition, the three phases, the six principles, and the one thing to build first.
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watsonx Cost Governance and FinOps, from Resource Units to a Real Budget (IBM Gen AI Series, Part 20)
watsonx charges in Resource Units, capacity unit hours, and a flat instance fee. Here is how those meters add up, and the plan choice that keeps your generative AI bill honest.
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watsonx.ai Pricing, Resource Units, CUH, and the Plan Tiers (IBM Gen AI Series, Part 5)
watsonx.ai bills two meters at once, Capacity Unit Hours for compute and Resource Units for inference. Here is what each of the four SaaS plans costs, and the point where Essentials stops being the cheaper choice.
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Vertex AI Cost Governance and FinOps (Google Cloud Gen AI Series, Part 26)
Read a Vertex AI bill line by line, then cut it with model tiering, context caching, Batch mode, and provisioned throughput judged against a real break-even. With budgets, billing export, and label-based attribution.
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Azure OpenAI Cost Governance and FinOps (Azure Gen AI Series, Part 26)
When a Provisioned Throughput reservation actually beats pay as you go on Azure OpenAI, how to read a bill hidden under Cognitive Services, and the Batch and caching discounts you get for free.
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Amazon Bedrock Cost Governance and FinOps on AWS (AWS Gen AI Series, Part 26)
Bedrock cost is driven by tokens, model choice, and inference tier. Here is how I attribute spend by team, cut it with batch and prompt caching, and put budgets and anomaly alerts around it before the bill surprises anyone.
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Dr Pranay Jha
Dr. Pranay Jha is a Cloud and AI Consultant with 18+ years of experience in hybrid cloud, virtualization, and enterprise infrastructure transformation. He specializes in VMware technologies, multi-cloud strategy, and Generative AI solutions. He holds a PhD in Computer Applications with research focused on Cloud and AI, has published multiple research papers, and has been a VMware vExpert since 2016 and a VMUG Community Leader.
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