In the early days of SaaS companies, most engineering and cloud operations teams weren’t tasked with monitoring or optimizing cloud costs. In fact, it would have been unlikely for these teams to care about cloud cost optimization at all, let alone take measures to fix issues and look for opportunities. Today, SaaS companies that want to secure a competitive foothold and ensure long-term success have to care about cloud costs.

Teams and organizations are leveraging Kubernetes to build platforms supporting their digital transformational efforts. A Kubernetes-based platform provides cloud-native architecture benefits such as automation, elasticity, resilience, and abstraction of the underlying infrastructure.

The efficiency, flexibility and strategic value of cloud computing are driving organizations to deploy cloud-based solutions at rapid pace. Fortune Business Insights predicts the global cloud computing market will experience annual growth of nearly 18% through 2028. As the cloud becomes one of the most expensive resources for modern organizations, cloud financial management, or FinOps, has become a critical initiative.

Setting FinOps KPIs helps keep your whole organization aligned toward the same financial goals. However, it takes more than simply setting a broad, company-wide financial goal and turning every employee loose to work on that goal without more specific directions. It’s far better to come up with realistic and achievable goals tailored toward each person or team that will be responsible for them. That’s because KPIs should ideally be focused around the typical persona of each team.

Public cloud can deliver significant business value across infrastructure cost savings, team productivity, service elasticity, and DevOps agility. Yet, up to 70% of organizations are regularly overshooting their cloud budgets, minimizing the gap between cloud costs and the revenue cloud investments can drive.

Cloud cost anomalies are unpredicted variations (typically increases) in cloud spending that are larger than expected based on historical patterns. Misconfiguration, unused resources, malicious activity or overambitious projects are some of the reasons for unexpected anomalies in cloud costs. Even the smallest of incidents can add up over time leading to cost overruns and bill shock.