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You can deploy on ARM64 servers today across AWS, Google Cloud, Azure, and Hetzner: Graviton, Ampere Axion, Ampere Cobalt, CAX. Pick the chip, pick the cloud, and deploy the stack you already run. There's no feature flag and no waitlist. It's on for every account.

The Digital Operational Resilience Act (DORA) has applied to financial organizations across the EU since January 2025 and is designed to strengthen their ability to withstand operational disruption. What the roundtables revealed was that although these financial organizations had completed extensive DORA planning exercises, this groundwork was not reliably translating into auditable operational control.

AI coding assistants have changed how fast application code gets written. Copilot, Cursor, Claude Code, and agentic tools built on top of them can generate a working feature in minutes. But none of them know your database's history. They don't know that a migration already renamed that column last sprint, that a policy forbids unqualified DELETE statements, or that the target environment has drifted from what your migrations say it should look like.

You know exactly where you want to go in CloudZero. Getting there sometimes takes a moment as you click into the nav, open a menu, scroll a dropdown, find the thing, click again. Every trip back to a familiar spot can take a few steps. Shortcuts remove that friction. Press command+K on Mac or ctrl-K on Windows anywhere in CloudZero, type where you want to go, and hit Enter. That means there’s no clicking through the nav and no scrolling to find what you already know the name of.

In 2025, 85% of organizations increased AI investment, and 91% plan to do the same this year, according to Deloitte. Despite continued spending, however, ROI lags behind, with just 6% seeing payback within one year. While AI use cases tend to have a longer payback period, often in the 2-4 year range, companies can’t afford to keep spending money without some measure of its practical impact both immediately and over time.

AI tokens are the small chunks of text, roughly four characters or three quarters of a word each, that language models read and generate. Every prompt and every response is measured in tokens, and AI providers bill per million of them. That makes the token the base unit of AI spend: 1,000 tokens is about 750 words, and every AI feature you ship is a token meter running.

CloudZero had a full team on the ground at Ai4 in Las Vegas during the first week of August 2026. The team included CTO Erik Peterson, who spoke on a panel about AI cost economics. The same problem surfaced everywhere we went: teams can see what they’re spending, but not whether it’s working. DIY cost tooling that fails time and time again, agent sprawl, and a widening gap between finance and engineering kept coming up throughout the week.

Serving large language models at scale is fundamentally a distributed systems problem. A single GPU, or even a single node, is rarely enough once you need multiple models, multiple replicas, tensor-parallel sharding across GPUs, or high-availability rollouts. Kubernetes solves general container orchestration well, but it has no native concept of a GPU-aware, actor-based compute cluster.

GPU cloud security tends to get discussed as if it's the same problem as general cloud security. It isn't. GPUs sit between processes in ways CPUs don't. Training data passes through them in patterns that create specific exposure. Model weights derived from sensitive data are themselves sensitive material in ways most procurement processes don't recognize. And the multi-tenant nature of public GPU cloud creates failure modes that don't exist in CPU-only environments.