Operations | Monitoring | ITSM | DevOps | Cloud

If you’re struggling to contain cloud costs in this suddenly volatile AI-fixated environment, it might be time to consider FinOps as an exercise in granular allocation and unit economics, with a focus on outcome.

Modern cloud environments are highly complex and dynamic, with critical services relying on large numbers of ephemeral resources. Ensuring observability coverage across this landscape is essential for troubleshooting, maintaining reliability, optimizing performance, and enforcing security standards. But as environments grow more elaborate and their ownership more dispersed, tracking observability coverage becomes increasingly challenging.

Cloud cost management is a big deal right now. For instance, 58% of organizations say their cloud costs are too high, according to our State of Cloud Cost report. Over the last five years, several other studies have shown that controlling cloud spend is a top cloud computing challenge. There’s more. As AI adoption accelerates, a new challenge has emerged: managing the rapidly growing costs of AI in a scalable and intelligent way.

Enterprise cloud storage solutions require strategic thinking from companies and teams due to the large-scale data that needs to be managed. Aside from managing the storage, other things must also be considered, such as what compliance standards must be met depending on the industry you work in, who has the credentials to access and manage sensitive information, and who will be managing the infrastructure of your cloud.

What’s so attractive about moving to the cloud?

Fall is here again! These headlines might not be as good as a maple-sugar doughnut and a pumpkin-spiced coffee, but they’re excellent news for FinOps practitioners nonetheless (and they won’t put you into a sugar coma).

We’ve seen the same story play out time and time again in numerous SaaS companies: The problem often begins when engineers — with a technical understanding of cloud costs and a deep understanding of how to build robust products — struggle to communicate the actual business impact of their efforts to company leaders.

Learn how to achieve and maintain HIPAA compliance on AWS with this comprehensive guide. Understand the shared responsibility model, essential architectural principles, and a practical checklist to protect PHI and avoid costly compliance violations. Discover how automation can reduce human error and streamline your security posture.

Enterprises are hemorrhaging their cloud budget: respondents in 49% of organizations estimate their cloud spending is wasted due to unchecked provisioning and lack of predictive cost governance. This cost inefficiency stems not just from financial blind spots, but also from operational gaps: poor visibility into network reliability and user experience. Real-time, end-to-end visibility is the foundation of cloud optimization.

Finance and engineering both thrive on efficiency. So when companies realize they’re wasting cloud spend, but aren’t sure where or how, both teams become frustrated. It’s remarkable how common this scenario has become, particularly over the past five years. Before the pandemic, Gartner reported that companies wasted over $14 billion on cloud services. During the cloud adoption surge in 2020, IDG found that 70% of US businesses overspent by as much as 62%.