Eliminating unexpected cloud costs: FinOps strategies for enterprises

Enterprises seeking to thrive in an innovation-centric economy are capitalizing on multi-cloud strategies to leverage unique cloud services. These services help accelerate initiatives supporting AI, data processing, and other pursuits, such as driving compute to the edge.

That’s all well and good – until the CIO gets the bill.

In a survey of more than 1,000 global IT decision makers conducted by Forrester Research with HashiCorp, 94% of respondents said their organization was currently paying for avoidable cloud expenses.¹

Meanwhile IDC’s Archana Venkatraman, Research Director, Cloud Data Management, Europe, adds: “While cloud adoption has accelerated, cloud governance and control mechanisms haven’t kept pace. As a result, up to 30% of cloud spend is categorized as ‘waste’ spend.”²

Examples of cloud cost surprises

Even inside the controlled environment of an enterprise’s datacenter, it’s not always easy for IT staffers to keep track of resource utilization. Now imagine the challenge of tracking usage from dozens of engineers in a multi-cloud environment where each service provider has its own tooling, processes, and procedures. Being able to bring all that data into a single view is extremely difficult.

Here are the top three cloud cost surprises that CIOs are likely to encounter.

• Unused resources: Over time, cloud environments inevitably sprawl, leading to unused storage volumes, idle databases and zombie test instances.





• Modernization: Businesses are slow to adopt newer instance types which offer 20% or more efficiency gains due to lack of visibility and understanding of the upgrade path. Given the hundreds of instance types, it’s easy to understand why.





• Anomalies: The biggest cloud cost surprise is the one that comes out of nowhere – an unexpected spike that could be caused by a variety of factors – misconfigurations, orphaned instances, runaway crypto-mining malware, or unauthorized deployments.

Enter FinOps

FinOps has become the de facto way in which enterprises manage cloud cost uncertainties, typically with machine learning used to help deliver insights to DevOps, CloudOps and the C-Suite. What’s more, FinOps provides a common language between the developers, infrastructure and business leaders to help show Return on Invetsment per project or set of services.

A disciplined FinOps practice, coupled with tools like OpsNow, helps in three ways:

1. FinOps tools can discover unused or orphaned resources and enable organizations to “rightsize” their cloud deployments.





2. Through the use of anomaly detection, FinOps provides an early warning system that alerts IT teams to usage spikes and budget overruns before they get out of control.





3. Cloud environments are constantly changing, so FinOps is never done; it’s an ongoing process that can help organizations optimize their cloud spend over time, do a better job of budgeting and forecasting, as well as avoid those billing surprises.

The OpsNow approach

There are many options for FinOps ranging from developing tools in-house to purchasing FinOps platforms. Managing your own platform and tooling presents  CIOs with investment and ongoing maintenance challenges.  In the fast moving world of the cloud that is a risk many prefer to not pursue.

OpsNow offers a different take and allows you to deploy without the investment nor maintenance.  Coupled with its methodologies and metrics you have a way to monitor and track your success.  

OpsNow, a spinoff from Bespin Global, provides  a SaaS platform which utilizes a “shared savings”  model – customers only pay a small percentage based on actual savings and are free to utilize the breadth of capabilities at no cost otherwise.

The OpsNow platform provides a single pane of glass across multi-cloud environments to identify unused resources, recommend capacity adjustments, provide AI insight for optimization, and provide no-risk cost savings from their AutoSavings tool which best even  the multi-year commitments offered from the clouds.

Advanced cost analytics and machine learning also ensure this technology can support a more efficient approach to cloud spend, which ensures IT leaders can innovate without worrying about unexpected costs. The automation is one aspect, but the ability to closely model true usage and ensure the coverage and utilization are closely aligned to the forecast is where the savings typically add up. 

Begin your journey to better cloud cost efficiency

² IDC, IDC Blog, The Era of FinOps: Focus is Shifting from Cloud Features to Cloud Value, February 2023