Tech’s Never-Ending Swing: Centralized or Decentralized Computing?
As technology swings between centralized and decentralized computing, enterprises must adapt to shifts driven by data gravity, cost, and control.
In this issue, Randy Bias, VP of Open Source Strategy & Technology at Mirantis, shares insights on the rise of edge computing, AI workloads, and the evolving IT landscape.
What's Brewing: Highlights
Expert’s Insights by Randy, VP Open Source Strategy & Technology at Mirantis
? TL;DR:?
Technology trends cycle between centralized and decentralized computing. Understanding these shifts—driven by data gravity, cost, and control—helps businesses optimize their infrastructure strategies.
?? Insight:
Public cloud growth is slowing as enterprises move beyond initial "lift and shift" strategies. Many are reassessing cloud adoption due to unexpected complexities and rising costs. Enterprise IT has evolved from costly and inefficient to more agile and cost-effective, with organizations strategically balancing cloud, on-prem, and edge infrastructure.
The conversation is shifting from data sovereignty to data gravity—where large datasets naturally attract applications and services. This influences infrastructure decisions, ensuring performance, compliance, and cost efficiency.
As a result, edge computing is gaining traction as businesses prioritize real-time data processing. Bringing computation closer to the data source reduces latency, optimizes bandwidth, and enhances AI-driven workloads.
High-performance computing, once exclusive to supercomputers, is now mainstream. Enterprises are leveraging it for AI, data-intensive applications, and large-scale innovation, making advanced computing power an essential part of modern business strategies.
?? Key Takeaway: Understanding the shift between centralized and decentralized computing can help businesses align their infrastructure strategies with evolving technological landscapes.
Fresh Batch: New & Noteworthy
Organizations are struggling with Kubernetes sprawl and AI workload management. Open source offers a path forward with unified management, standardized deployments, and better observability.
Understanding Edge Computing vs. Cloud AI is key for enterprises adopting AI. This article explores their benefits, limitations, and costs—helping businesses find the right balance for AI workloads.
Is platform engineering at a crossroads? Will it fulfill its promise or fade away? At State of Open Con, a panel weighed what's ahead for the movement.
In 2025, AI, sustainability, and hybrid IT will reshape digital infrastructure, with edge computing emerging as a key pillar. Here are predictions for AI-driven data center trends that will shape edge AI deployments to meet businesses' evolving needs.
In AI, governing and onboarding models is key to ensuring safety, performance, and compliance. A hybrid approach using VMs and containers, orchestrated by Kubernetes, enables secure testing and scalable deployment.
Our Latest & Greatest
In a recent interview with TFiR, Stephen Frassetti, Field CTO at Mirantis, shares his 2025 predictions, noting that organizations are recognizing the value of flexibility in their technology stacks.
As businesses evolve, the shift toward composable platforms is accelerating—giving enterprises the freedom to integrate best-of-breed solutions, avoid vendor lock-in, and adapt to ever-changing demands.
At the same time, AI adoption is poised for a major shift in 2025, especially at the edge, where real-time processing and decision-making will redefine how enterprises deploy and manage intelligent workloads.
Watch the full interview to hear Stephen’s insights on AI, composable platforms, and the future of enterprise IT.
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