Seeing spending in real time might increase or decrease cloud utilization for enterprises. In what cases will finops recommend a return to traditional systems? A 2022 study carried out by TechTarget’s Enterprise Strategy Group found that 62% of firms use third-party cloud-cost estimation tools. This included software to compare potential costs of different public cloud providers. The impact of these finops tools was clear in the study. Just under half (49%) reported that finops tools have led their organizations to reconsider their first choice for cloud for at least one workload, selecting a different cloud vendor for workload deployment. Perhaps the era of choosing a single cloud provider is over. What was most interesting to me is that hardware suppliers all have pay-as-you-go purchase models for the physical systems they sell (aka hardware as a service). The report showed that these hardware vendors were also affected by the data finops systems present. Almost half of the organizations in the study (43%) elected to modernize their on-premises infrastructure rather than place workloads and data sets on public clouds. Many are reporting that in some cases, the data from finops tools led to decisions to select traditional hardware platforms in enterprise data centers as more cost-effective than public clouds. Until finops programs were established, most of the people selecting platforms, cloud and not cloud, for net-new or existing application workloads made decisions without fully understanding the costs. Information, in this case, cost estimation data, is your friend if you’re looking to make smart architectural decisions. We’ve covered the reasons for repatriation. In many cases, traditional hardware platforms are much more cost-effective than public cloud platforms for some data storage and application processing requirements. The finops tools are pointing that out. In many instances, as seen in the report, IT management is pushing application deployments to any lower-cost options, which could be on premises. The danger here is that cost data may not be the only metric you should consider. The platform’s evolution may also affect its cost-effectiveness. You could end up spending less on an on-premises deployment and operation initially but might have to move eventually if that platform fails to evolve with the market, the latest operational tools, security, etc. Another aspect is the selection of public cloud providers. The report also showed that companies used finops information to pick the providers that were more cost-effective. This speaks to the growth of multicloud and the fact that most enterprises use more than a single provider. They have a choice in platforms, such as storage and compute. Even non-commodity platforms and services that may be unique to a specific cloud provider, such as artificial intelligence, serverless, and analytics, are tracked in terms of their costs and benefits. As public cloud providers approach feature synchronization, meaning that many of their services are very much the same, price will be used more as a key metric for service selection. Overall, this is a good trend. Many enterprises are spending too much on cloud services and have little idea of the value being returned to the business and the total cost of ownership for each platform option. Finops is finally putting the information in the hands of those who can get the most out of it and hopefully drive better decisions. We just need to be careful to consider the longer-term impacts of these decisions, which may eliminate any short-term gain. Related content analysis Generative AI won’t fix cloud migration You’ve probably heard how generative AI will solve all cloud migration problems. It’s not that simple. Generative AI could actually make it harder and more costly. By David Linthicum Jul 12, 2024 5 mins Generative AI Artificial Intelligence Cloud Computing analysis All the brilliance of AI on minimalist platforms Buy all the processing and storage you can or go with a minimum viable platform? AI developers and designers are dividing into two camps. By David Linthicum Jul 09, 2024 5 mins Generative AI Cloud Architecture Artificial Intelligence analysis The next 10 years for cloud computing Despite AI's explosive growth, the industry still needs to face facts that customers are unhappy about costs and vendor lock-in. By David Linthicum Jul 05, 2024 5 mins Amazon Web Services Google Cloud Platform Microsoft Azure analysis Serverless cloud technology fades away Serverless was a big deal for a hot minute, but now it seems old-fashioned, even though its basic elements, agility and scalability, are still relevant. By David Linthicum Jul 02, 2024 4 mins Serverless Computing Cloud Computing Software Development Resources Videos