Operations | Monitoring | ITSM | DevOps | Cloud

The benefits of observability are clear: deep visibility into system health, faster troubleshooting, and improved reliability (to name a few). But what’s equally clear is that, as organizations scale and evolve their observability strategies, they need a way to tap into these benefits without runaway costs. According to Grafana Labs’ 2025 Observability Survey, 74% of respondents say cost is a top priority for selecting tools.

In July 2024, CrowdStrike — one of the world’s top cybersecurity companies — shipped a minor configuration update to its Windows security product. Within minutes, airlines, banks, hospitals, and retailers worldwide began crashing. The update wasn’t new code. It was a routine content file that slipped through with a bug in its safety checks. When Windows machines loaded it, the agent hit an out-of-bounds memory error and crashed. Devices blue-screened and got stuck in reboot loops.

Cloud computing offers several undeniable benefits to businesses. Some of the biggest ones are agility, cost savings, data recovery, and developing new apps and services to meet changing customer needs. Despite these benefits, the cloud can be complex, demand specialized skills, and require companies to follow up-to-date cloud security best practices. Why?

Engineering teams need to deliver reliable, secure, and high-performing applications, all while keeping costs under control. But engineers often lack visibility into cloud cost data, relying on finance-driven reports that they receive only after the billing cycle closes. Without daily cost insights alongside observability data, they don’t know until it’s too late that an infrastructure change caused a significant cost increase.

From the time I joined CloudZero almost two years ago, one thing was unmistakably clear: the team here had built the most powerful cost allocation engine in the FinOps industry. It was also clear that this power came with something of a tradeoff. While engineers and technical FinOps practitioners loved what our YAML-based CostFormation engine could do, the experience wasn’t always simple for non-technical people getting their hands on the product for the first time.

Your CFO just asked why cloud costs jumped 40% last quarter. You pull up your dashboards, confident in your tagging strategy, until you realize 30% of your spend is labeled ‘unallocated’. This is the moment every FinOps team dreads. It reveals a hidden complexity that even mature organizations struggle with: the challenge of accurately allocating cloud costs in a way that’s both granular enough to be actionable and trusted enough to drive decisions.

The obituary for the data center was written too soon. While the cloud dominates today’s IT headlines, traditional infrastructure hasn’t disappeared. It is evolving. Enterprises still rely on data centers for control, compliance, and reliability. However, they are increasingly needing the agility, scalability, and cost visibility that the cloud promises. Cloud managed data center services are bridging this gap.

Nearly every industry today uses AWS for different services. Developers, cloud architects, DevOps engineers, and IT teams all use it to provision servers, databases, and storage. However, doing this service by service and then wiring them together can get messy. That’s where AWS CloudFormation comes in to save time, enforce consistency, and lower the risk of misconfigurations. But beyond simplifying infrastructure management, one big question remains: at what cost?

Today, we’re making CloudZero even better with the launch of Dimension Studio, a major evolution in how CloudZero customers create and manage Dimensions — customizable “lenses” that allocate cloud and AI spend to relevant categories like products, features, teams, or customers, without relying on resource tags. At CloudZero, our mission has always been to help organizations make sense of their cloud and AI spend.