Maryanne Baines has spent the last few years in the trenches of GPU-as-a-service—scoping clusters, negotiating power and land, and watching customers pivot from desperate capacity grabs to deliberate platform choices. In this conversation, she unpacks why the “rent-a-GPU” play is fragile, how
Modern cloud‑native stacks promised a faster release tempo and elastic scaling, yet the price of that progress surfaced in an unexpected place: the network where every new microservice, job, and ephemeral pod becomes another moving part to route, secure, and observe without downtime under pressure.
In the fast-evolving landscape of technology, Salesforce, a titan in customer relationship management (CRM) software, finds itself at a critical juncture where groundbreaking advancements in artificial intelligence (AI) collide with lingering uncertainties in cloud computing demand. As businesses
In today's fast-paced digital landscape, businesses are increasingly turning to multi-cloud environments to drive innovation, scalability, and flexibility, utilizing platforms such as AWS, Azure, and Google Cloud to meet diverse operational needs. However, with these advantages comes a significant
Imagine a world where the boundaries of traditional education are shattered, where students and educators are no longer tied to physical classrooms or outdated systems, and where learning can happen at any moment, in any place, with just the tap of a screen. Cloud-based Learning Management Systems
I'm thrilled to sit down with Maryanne Baines, a renowned authority in cloud technology. With her extensive experience evaluating cloud providers, their tech stacks, and how their solutions apply across various industries, Maryanne offers unparalleled insights into the rapidly evolving cloud
