RapidScale Launches Infrastructure Intelligence Practice Amid Supply Chain Volatility — Rapid Scale LLC

Event summary

RapidScale launched its Infrastructure Intelligence practice on July 8, 2026 to address pricing volatility and supply chain disruptions in IT planning.
88% of technology leaders surveyed reported experiencing at least one disruption from extended lead times, pricing changes, or capacity events in the first half of 2026.
The new practice integrates five existing solution areas to improve cost visibility, optimize resource deployment, and reduce planning risk across cloud, on-premises, and hybrid environments.
Only 12% of organizations reported no meaningful change to operations and planning over the last 90 days, with most IT leaders managing pricing increases (59%), delivery delays (48%), and capacity challenges (34%).
RapidScale surveyed 300 technology leaders, identifying key trends including stretching existing infrastructure and concerns about long-term impacts on tech roadmap planning and budget predictability.

The big picture

RapidScale's new practice responds to a broader industry trend of rising costs and extended delivery timelines, forcing technology and finance leaders to rethink long-term planning. The global memory and storage supply chain's cautious adaptation to spiking demand highlights the need for agile, fact-based infrastructure decision-making. RapidScale's approach aims to align infrastructure decisions with business priorities, addressing interconnected challenges beyond isolated technology issues.

What we're watching

Supply Chain Constraints: How long manufacturing facilities will take to alleviate strain (2-5 years) and the ongoing priority of adapting to structural shifts in the memory and storage supply chain.
Project Prioritization: Whether organizations can sustain shifting workloads across existing infrastructure without delaying critical projects, given that only 26% are canceling or delaying projects.
AI Implementation: The pace at which supply chain constraints could impact the ability of organizations to implement and execute AI initiatives, with nearly half (46%) of respondents flagging this concern.