arXiv:2606.31470v1 Announce Type: new Abstract: Cloud virtual machines are often overprovisioned, creating avoidable cost and operational inefficiency. We present CLOUDADV, an interactive engineer-facing advisory system for cloud instance sizing under workload drift. The system combines zero-shot time-series forecasting with bounded recommendation generation across day-, week-, and month-scale planning horizons. For each query, CLOUDADV constructs a structured decision context from historical utilization, forecast summaries, current VM metadata, candidate instance options, pricing, and explici
The increasing complexity and cost of cloud infrastructure, coupled with advancements in zero-shot AI models, propel the need for more efficient resource management solutions to counteract overprovisioning.
This development addresses a critical economic inefficiency in cloud computing, enabling organizations to significantly reduce operational costs and improve resource utilization, directly impacting profitability and sustainability.
Cloud resource allocation shifts from reactive overprovisioning to proactive, AI-driven optimization, providing engineers with precise, decision-aligned advisories for instance sizing under dynamic workloads.
- · Cloud users (enterprises)
- · Cloud optimization software providers
- · AI/ML model developers
- · FinOps professionals
- · Cloud infrastructure providers (from reduced overprovisioning)
- · Manual IT operations teams
Enterprises will see substantial cost savings and efficiency gains in their cloud infrastructure spending.
Increased adoption of such AI-driven tools will put pressure on cloud providers to offer more granular billing or risk losing revenue to more efficient resource utilization.
The widespread implementation of advanced decision systems for infrastructure could accelerate the 'lights-out' automation of IT operations, reducing human intervention.
This signal links to a primary source. Continuum Brief monitors and indexes it as part of the live intelligence stream — we do not republish source content.
Read at arXiv cs.AI