Operations | Monitoring | ITSM | DevOps | Cloud

Container security has finally gone mainstream. When Docker announced hardened container images in late 2025, complete with minimal attack surfaces, non-root defaults, continuous CVE scanning, and automated updates, the response was enthusiastic. For teams managing their own infrastructure, this was a real step forward. Secure-by-default containers are no longer niche or expensive. They are expected.

January 15, 2026 – Canonical, the publisher of Ubuntu and provider of open source security, support, and services, announced today that it is a launch partner for the AWS European Sovereign Cloud, a new independent cloud for Europe, with Ubuntu and Ubuntu Pro now available. Canonical’s Ubuntu Pro delivers a securely designed, stable, and enterprise-ready foundation for open source innovation while providing customers with the same security, availability, and performance they expect from AWS.

Choosing between AWS and OCI is a common decision for organizations moving workloads to the cloud. Both Amazon Web Services and Oracle Cloud Infrastructure offer global infrastructure, robust security, and broad service portfolios. On paper, the platforms can look interchangeable. They are not. AWS and Oracle Cloud differ in pricing, compute models, storage options, networking, and managed services. These differences affect scalability, reliability, and day-to-day operations.

Stop paying for undead infrastructure that eats 30% of your cloud budget. Learn how to identify these hidden monsters and reinvest that waste back into innovation.

Welcome to January’s Cloud Economics Pulse, CloudZero’s monthly look at cloud spend as AI moves from vibe to prod. And this related news flash — AI spend keeps hitting new highs. pilots to production. In last month’s Pulse, we explored the compounding effect of AI becoming part of everyday cloud operations. This month, we see that pattern harden into year-end results.

API metrics have long been a core part of building and operating reliable SaaS products. Teams track the likes of request volume, latency, and uptime to ensure APIs perform as expected under load. First: API cost intelligence metrics measure how API usage translates into cloud, AI, and third-party spend — and attribute that cost to customers, features, workflows, and teams so SaaS businesses can protect margins as usage scales. But today, the API metrics that matter most go beyond performance.

Cloud spending has shifted from an IT afterthought to a strategic performance lever. As organizations head into 2026, many IT teams are rethinking how they use, govern, and optimize cloud resources, not just how much they consume. Enterprises, startups, and MSPs are entering an efficiency-first era, fueled by multi-cloud adoption, distributed architectures, and a growing need to balance performance with predictable budgets. The question is no longer: How much are we spending?

AWS storage is often a top choice for enterprises due to its reliability and power to store large amounts of data for easy access. However, businesses may find it difficult to navigate and understand S3 storage costs, having to manage different storage classes, data transfer fees, and potential hidden charges. Without fully understanding AWS S3 storage costs, the pricing structure can become overwhelming and cost companies more than initially intended.

OpenAI doesn’t bill per feature, per customer, or per transaction. It bills per token, across multiple models, with usage patterns that can change by the hour. As a result, two API calls that support the same feature can have very different costs. Without a clear way to translate token-level pricing into something product, engineering, and finance teams can reason about, AI spend becomes difficult to forecast and harder to control.