Operations | Monitoring | ITSM | DevOps | Cloud

A year ago, the sentence “I just deployed an app on GitHub” wouldn’t have made sense coming from me. I’m the VP of People at CloudZero; code deployments and I were not close friends. That’s changed. In this AI era, non-engineers are building, and I think that’s a genuinely good thing. But only if it’s tied to something that matters.

If you run Claude through LiteLLM, some of that spend is probably going uncounted – and you can’t see it, precisely because the data isn’t there. Routing through a gateway is messier than it looks: LiteLLM alone can carry Claude several ways – the OpenAI-compatible endpoint, and the Anthropic pass-through proxy that the native SDK and Claude Code use – and each path describes the same call differently.

We rebuilt docs.cloudzero.com from the ground up. The result is a documentation site organized around what you’re trying to accomplish rather than feature names and jargon.

Cloud cost optimization has become a critical priority in 2026. What starts as a manageable $5,000 monthly cloud bill can quickly grow to $50,000 within a few quarters, often without any major change in workload. If you lead an engineering or infrastructure team, this probably sounds familiar. You may have already seen costs rise faster than expected or struggled to explain sudden spikes in cloud spend. The challenge today goes beyond just rising numbers.

On June 18, OpenAI gave ChatGPT Enterprise admins new credit usage analytics and spend controls. It’s a single view of credit consumption broken down by user, product, and model, default workspace budgets, per-group limits, and a Cost API for pulling the data into their own systems. Two days earlier, Microsoft shipped Copilot Cowork with spending limits, budget allocation, usage alerts, and user-level caps. This is a step in the right direction.

Customer lifetime value (CLV) is the total revenue a business expects from a single customer over the entire relationship, minus the costs of serving them. The standard SaaS CLV formula: Average Revenue Per Account x Gross Margin % / Monthly Churn Rate. For a $500/month customer with 75% gross margin and 5% churn: CLV = $7,500. That number can swing materially once AI spend per customer is built into gross margin, something many SaaS companies still don't do.

Point A: 1835. Andrew Carnegie is born in a weaver’s cottage in Dunfermline, Scotland. The cottage has one main room, which the Carnegies share with another family. Point B: 1901. Andrew Carnegie becomes the richest man in the world when Carnegie Steel Company wins the Iron vs. Steel industrialists’ war, and he sells the company to J.P. Morgan for the modern equivalent of $450 billion.

The Anthropic Enterprise connector pulls per-user Claude Enterprise cost and usage into CloudZero, so you can allocate Claude spend to the teams that drove it.

At Datadog, our broad Kubernetes footprint amplifies the significance of a familiar autoscaling tradeoff: Overprovisioning wastes cloud spend, while underprovisioning threatens reliability. We built Datadog Kubernetes Autoscaling (DKA) to help teams rightsize their workloads by generating intelligent resource recommendations and automating multidimensional workload scaling. Across Datadog, adopting DKA has eliminated more than $3 million in annualized idle compute costs while reducing reliability risks.

The core of ROI is visibility. If you can clearly see … 1. What it costs to produce the thing you make, and 2. How much money it makes you … then calculating ROI is easy. But with AI, as with the cloud before it, getting that visibility is extremely challenging. Why? Because the cost data associated with each is inherently chaotic.