New workload demands are turning data handling into a system-level design challenge rather than a back-end afterthought.

Enterprise data systems now sit beside ranking, inference and decision pipelines that influence what users see, interact with ...

When flexibility is treated as a foundational design principle rather than an afterthought, it becomes a source of resilience ...

Mydbops announces its strategic focus on Database Reliability Engineering to help SaaS companies improve database ...

Modern control system design is increasingly embracing data-driven methodologies, which bypass the traditional necessity for precise process models by utilising experimental input–output data. This ...

The Uptime Institute’s Tier standard is a globally recognized framework that classifies data centers into four tiers based on their infrastructure’s reliability, redundancy, and fault tolerance. These ...

Rather than positioning sustainability as a branding exercise, MBT’s approach reflects a practical engineering response to a ...

Why it matters: Operating data centers requires a lot of energy, and the enormous amount of water used to cool them is a growing environmental concern. As the expansion of AI data centers exacerbates ...

Microfactories are not just smaller replicas of mega-factories. They operate with radically different assumptions. Data is real-time and transient, not batch-processed. Production is modular, not ...

The rapid escalation of AI/ML workloads—driven by increasingly large language models—is reshaping high-performance computing and AI data center architectures. Real-time inference and large-scale ...

More than 400 million terabytes of digital data are generated every day, according to market researcher Statista, including data created, captured, copied and consumed worldwide. By 2028 the total ...