The customer faced several challenges as it planned to expand its operations, including:
The existing on-premise ERP system was inadequate for supporting the bandwidthintensive applications planned for future growth.
Significant upfront investment in physical servers, along with ongoing costs for utilities,
security, and maintenance, was proving to be cost-prohibitive.
The complexity of the on-premise infrastructure made it difficult to guarantee efficient
performance across various applications, impacting overall business operations.
TTBS Solution
Recognizing the limitations of the customer’s existing infrastructure, TTBS proposed a
transition to Microsoft Azure to address their specific needs:
Configured Azure to support application servers, database servers, and disaster
recovery systems, aligning with the company’s growth trajectory.
Set-up Azure’s IaaS model to eliminate large CapEx and reduce maintenance expenses,
providing a pay-as-you-go service that scaled with the company’s needs
Ensured quick setup and seamless integration with existing Microsoft products,
facilitating immediate improvements in collaboration and productivity.
Benefits
Enhanced Business Agility: Quick deployment of Azure enabled GNU Steel to adapt rapidly to market demands and operational needs.
Cost Efficiency: Transition to cloud computing significantly reduced the total cost of ownership and operational expenses.
Scalable and Flexible IT Environment: Azure’s scalable infrastructure allowed for easy adjustments in resources to meet growing demands without hardware expansions.
Robust security features of Azure ensured that critical data was well-protected.
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The Microsoft Azure solution provided by TTBS helped the
customer securely access data using ERP from anywhere and
any device. Besides cost savings and increased flexibility, the
solution has created greater opportunities for the customer
to innovate and focus on inventing smarter steels for a
better world. It has given them the tools to drive innovation
and create a data-led, cost-efficient model that they can
build upon in the future.