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.

We are excited to announce the release of SSIS components Data Flow Components version 4.0, an update that delivers expanded compatibility with the latest development tools and database platforms. Version 4.0 introduces full support for Visual Studio 2026 and Visual Studio 2026 Insiders, ensuring developers can seamlessly adopt Microsoft’s newest IDE while continuing to work with familiar workflows.

So as software engineers using AI coding assistants, we’re quickly learning of a new anti-pattern: Hallucinated Success. You give your agent (e.g. Claude via terminal or various IDE code assistants) the command “refactor the billing controller.” The agent happily complies, churning out nice clean code. The agent even goes so far as to write a new unit test suite that passes at 100%. You integrate it. Your test suites pass. Your production code breaks. Why?

There usually isn’t a hard and fast rule about who should be on-call. Teams often look for criteria like seniority, experience, or expertise. While those factors certainly help, they might matter less than you think. It is often more useful to look at whether your processes are ready. When incident responses rely on memory and intuition rather than documentation, even experienced engineers can struggle. They might handle things through internal knowledge that isn’t available to everyone else.

Megaport On-ramp as a Service is the fastest way for service providers to offer secure, private connectivity to mission-critical applications, and it’s now available. Considered the gold standard, private connectivity is the superior way to reach enterprise applications, storage services, or security services. But for most service providers, offering a private on-ramp for customers to connect to isn’t straightforward.

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.