The vast majority of companies work with more than one IaaS provider and operate hybrid cloud environments (public and private clouds), so they need expense management strategies and cost-reduction solutions that bridge that complexity. This is especially true given the pricing and subscription changes to VMware’s private cloud service offerings. Now more than ever, VMware clients need to use a data-driven strategy, knowing whether it’s more cost effective to place workloads in their private or public cloud architectures. In this article we unpack the most critical capabilities for hybrid-cloud cost cutting.
The Importance of Data Normalization in Reducing Hybrid Cloud Costs
The FinOps Framework has become the go-to strategy for curbing IaaS costs as it offers a framework for traditional cost-cutting tactics like rate optimization and usage optimization. However, in multi-cloud architectures, special attention should be given to data normalization and the AI tools of experts in hybrid-cloud expense management.
Every major IaaS provider uses different pricing models, presents cost and usage data in different ways with different billing constructs, and has varied discounting models. Apples-to-apples price comparisons are impossible without the work of data normalization to help dissolve this sea of inconsistencies. When you don’t have the unit price or the ability to compare across all vendors, cost optimization can only happen in silos (based on each individual IaaS solution or cloud service provider). So, you’re missing the bigger picture. You can’t see which provider, solution, or money-saving strategy is best for you.
Data normalization is the key prerequisite. For instance, it allows IT leaders to:
- Identify financial tipping points, knowing when it’s more cost effective to use a public versus private cloud strategy. This is also helpful in designing workload placement policies.
- Compare instance pausing schedules, testing different scenarios to see when you should put idle resources on hold and how much you’ll save across multiple vendors, including the savings from each individual provider.
The need for data normalization explains why industry analysts tout the FinOps FOCUS cloud data standardization as a new frontier in cloud expense management. FOCUS stands for FinOps Cost and Usage Specification, and it’s a project that aims to standardize the presentation and handling of cloud cost data across all vendors and across the industry.
But while major hyperscalers (and Tangoe) are adopting FOCUS data standards, this is only step one. You still need to collect and analyze all those normalized data feeds from each IaaS provider and then apply machine learning and advanced analytics to arrive at cost-saving insights quickly. That’s where AI comes in.
Use AI to Double Your Savings for Hybrid-Cloud FinOps Programs
A CIO.com study shows companies that activate their FinOps model using AI are 53% more likely to report a savings of greater than >20%. Whereas those who don’t leverage AI save less than <10%. Plus, companies seeking that bird’s-eye view across hybrid clouds will also need to work with their private cloud providers too to capture on-premise costs – or find a FinOps platform that does.
Third-party FinOps solutions (also known as cloud expense management platforms) work best because they are purpose-built for today’s complex environments. Studies show optimizing a multi-cloud, hybrid-cloud estate requires more than just native tools (i.e. vendor dashboards) and home-built software.
What Makes this Approach Effective?
The Ability to Make Accurate Comparisons Comes from Unit Economics
The ability to choose is negated when you cannot arrive at the unit economics necessary for making accurate comparisons across services. This approach dissolves the sea of data inconsistencies from each provider. Under the FOCUS standards, compliant vendors and their cloud data will all “speak the same language.”
Unified Management Reveals a World of New Insights
With the birds-eye view of consumption, new themes emerge giving way to new ways to save. Software platforms work with a variety of public and private cloud providers to break down silos and unify analysis, evaluating multi-cloud costs and usage data all in one place.
AI Shortens Your Time to Success
AI, machine learning, and advanced analytics accelerate time-to-insights and therefore time-to-savings. AI can both make money-saving recommendations and act on your behalf in an instant, going so far as to implement changes to the IaaS platform and configurations for you. Gartner refers to this as “automated remediation,” calling for all Cloud Financial Management solutions to provide these features as standard with every offering. Tangoe leads the industry in this capability. See how.
Ready to manage your hybrid cloud costs with one platform and one provider? Talk to Tangoe.