Operations | Monitoring | ITSM | DevOps | Cloud

Google SecOps (formerly Chronicle) is widely used for large-scale security analytics, long-term telemetry retention, and detection across diverse environments. Its Unified Data Model (UDM) enables correlation across sources and supports analytics that operate over long time horizons. To take full advantage of these capabilities, security data must arrive in a consistent and well-structured UDM format. In practice, this is rarely the case.

Stop writing fragile scripts. Discover how top enterprises use Kubernetes Management Platforms to automate governance (Policy-as-Code), scale ephemeral environments, and enforce FinOps with Spot Instances.

Enterprises operating at cloud scale today face a growing reality: managing infrastructure performance and cost in silos no longer works. Kubernetes, multi cloud environments, and GPU accelerated workloads deliver immense agility and capability, but they also introduce complexity that outpaces traditional monitoring and cost governance approaches.

When you move past daily rotations but find anything longer than a week feels too stretched out, you often end up choosing between weekly and split-week rotations. Weekly rotations give you a full seven days before handing off. Split-week rotations break that time into smaller chunks like 2-day, 3-day, or 4-day shifts. Each approach creates a different rhythm for your team. This guide compares both patterns across three key criteria.

AI is the new frontier for FinOps maturity. It introduces fresh spend patterns and new opportunities for value. As GPUs, inference, and retraining reshape costs, FinOps maturity grows through visibility, forecasting, and shared mindset about how these workloads drive business impact. In this 2025 post, I gave my guidelines for implementing AI tagging to give business context and clarity to vague AI invoices. Now, I’m sharing the next level up: how to drive FinOps in AI with AI.

When Anthony Leung talks about FinOps, he’s speaking from operating at real scale — not theory. As VP of Engineering Platforms and Security Research at Forcepoint, he led a transformation that cut cloud spend in half while improving availability, and built a culture where engineers own their economics.