Operations | Monitoring | ITSM | DevOps | Cloud

I’ve previously covered how eG Innovations AIOps-powered monitoring benefits those working with Digital Workspaces or leveraging APM; today, I’ll cover how those same AI-powered capabilities benefit those supporting cloud hosted architectures and workloads.

Most SaaS companies aren’t spending too much on AI. They’re just completely screwing up how they price it. You feel the budget pressure. The OpenAI and Anthropic bills keep climbing. Finance is starting to twitch. So the instinct is to cut. Trim back experiments. Cap usage. Beg your team to “optimize.” You can’t cost-cut your way out of a pricing failure though. And most of the time, that’s all this is — a pricing failure.

When you’re a global leader in AI-assisted hiring, speed matters. Not just in matching candidates to jobs, but in making the engineering and financial decisions that keep your platform running efficiently. For HireVue, fragmented infrastructure, manual processes, and sprawling spreadsheets turned cloud cost management into a time-consuming spelunking expedition.

Serverless platforms like Azure Functions and Azure Container Apps make it easier to scale your applications without managing infrastructure. But successful serverless apps require thoughtful planning. They must be designed to account for cold starts, unpredictable scaling behavior, and ephemeral compute lifecycles, all while ensuring secure data handling and end-to-end observability across highly distributed components.

Although container-related technology existed before 2013, Docker revolutionized and propelled it into the mainstream. Using Docker, developers could automatically create containers from application source code, share libraries, and reuse containers. Docker enables you to track container image versions, roll back to an earlier iteration, and track who built a specific one. You can even upload only the deltas between two versions.

If you want to align green awareness with bottom-line impact, start by looking at your cloud waste. Not just as a budget problem, but also as wasted energy, because that’s exactly what it is. AI, especially, is a mounting factor. Deloitte’s Tech Trends 2025 report highlights the growing energy demands of large AI models, warning that electricity use in data centers could soon rival that of entire nations like Sweden or Germany.

Since launching Civo AI, we have been working on creating a secure, scalable, and easy-to-manage private AI solution. We are excited to announce that we have officially launched FlexCore AI Private Cloud, a sovereign AI cloud solution designed for businesses demanding data sovereignty without sacrificing innovation. Deploy your AI-ready private cloud by contacting our team today >