Operations | Monitoring | ITSM | DevOps | Cloud

The inevitable happened. A while back, Gartner projected that in 2026, 30–50% of all new SaaS product features would use LLM inference. That meant OpenAI-style costs would become a standard part of SaaS COGS. Today, OpenAI has become one of the most operationally significant line items for SaaS companies. But for many teams, this creates an uncomfortable gap. Engineering sees OpenAI as a fast path to innovation.

While traditional cloud storage is the normal method people use to store, share, sync, and back up their files online, there are many other options available to consider, especially if you want quick access to large amounts of data. For this, many teams consider checking an object storage vendor list to choose the right service to meet this need. Object storage is a cloud storage architecture designed to handle large amounts of unstructured data.

In 2025, Oracle shocked the market. Its cloud growth was so aggressive that Oracle’s stock surged, briefly making founder Larry Ellison the world’s richest person. That didn’t happen by accident. Oracle closed fiscal 2025 with $57.4 billion in revenue, mainly driven by cloud services. Oracle Cloud Infrastructure (OCI) grew roughly 50% year over year, driven by enterprise databases, AI workloads, and network-intensive applications migrating from more expensive platforms.

Right now, 48% of organizations say they’re being asked to measure or report on AI-related costs. The problem is that they’re still figuring out how to do it. That was a very telling stat from a recent CloudZero webinar on AI and profitability, and speaks loudly to the reality that many organizations are still struggling to get a grasp on AI spend which our data shows to be rising sharply as a part of total spend in recent months.

Think of a stateful application like a conversation with a barista who remembers your order every time you walk in. They know what you had yesterday, how you like it prepared, and what you’ll probably want next. That memory makes the experience smoother, but it also means that if that barista isn’t around, your experience can break down entirely. A stateless application, on the other hand, is similar to ordering from a self-service kiosk.

We are continually enhancing our offering to support enterprises looking to modernize without the pain of modernization. We partnered with IBM to bring our highly flexible cloud application platform to the IBM Cloud Marketplace to give financial service organizations a cloud option that meets both workload and organizational requirements.

On paper, Gemini pricing looks straightforward. You pay per token. Input tokens cost one amount, output tokens cost another, and different models come with different rates. But once Gemini is wired into a production SaaS product, that simplicity disappears. Fast. That’s because token usage compounds across context, retrieval, and output — not across requests. The same “API call” can cost pennies in one feature and dollars in another.