A global logistics leader faced a pivotal challenge in executing a large-scale lift and shift cloud migration critical for expanding operations. Amid rapid business growth, the company confronted two major roadblocks: a significant shortfall in specialized cloud migration expertise and an immediate need for additional staffing to maintain operational momentum. This shortage threatened to stall the largest IT project in the company’s history, risking project delays that could impact its competitive edge and growth.
In response, they brought on Ambient Consulting to be a strategic partner, quickly aligning with the company’s goals and operational cadence. Ambient played a crucial role in helping the client maintain project velocity, effectively addressing the staff shortfall with a handpicked team of over 20 subject matter experts in a matter of days.
This team was instrumental in developing a sophisticated testing lab for load simulation and system optimization, all while ensuring that day-to-day operations continued unhindered. By integrating advanced Machine Learning components into the Azure cloud infrastructure and enhancing legacy systems, Ambient’s partnership bridged the expertise gap and propelled the migration project forward without sacrificing operational speed or quality.
The partnership with Ambient swiftly propelled the cloud migration project to completion, surpassing expectations by finishing ahead of schedule and under budget. This initiative boosted the company’s infrastructure and market agility, significantly improving service delivery and competitive standing.
Acknowledging Ambient's critical role, the executive team noted, "Their assistance was pivotal in enhancing our market speed by providing top-notch tech talent, streamlining our cloud operations, and sharpening our focus on strategic objectives." After the original project’s completion, the client offered several Ambient consultants full-time positions to navigate the complexities of AKS and Azure as the company moves toward more streamlined and efficient deployments.
