NetApp

GumGum, a company that uses artificial intelligence to determine the context of a webpage and match targeted ads, faced a significant challenge in managing its computing infrastructure. The company's proprietary AI services required a large volume of computing infrastructure with variable demand. While AWS cloud was a solution, the costs were high, especially for AI workloads using GPU instances. The company's success led to rapidly increasing costs in line with the demands on their highly scalable infrastructure. The demands were cyclical, with ad serving varying throughout the year. At peak times, GumGum's Ad Server application received over 18 million requests per minute, requiring more than 130 AWS virtual machines to be provisioned. The company's costs grew to around $120k per month for EC2 on just one of their four Ad Server data centers. GumGum needed a solution that would help them use spot instances, save money, be easy for limited staff to use, and guarantee uptime.

Mellanox Technologies, a multinational supplier of computer technology networking products, was facing challenges with its testing, research, and design infrastructure. The company, with multiple manufacturing sites worldwide, needed an infrastructure that was engineered for integration, easy data sharing, scalability, and unified support. The existing system was not providing the performance and reliability required to accelerate product innovation. Mellanox also needed to reduce the time to market for its products, including adapters, switches, software, cables, and silicon products for markets such as high-performance computing. The company was in search of a unified solution that was reliable, scalable, and cost-effective.

ITOCHU Techno-Solutions (CTC) operates the Technical Solution Center (TSC), a comprehensive facility that allows client companies to evaluate and verify systems to be introduced using actual equipment. It is Japan's largest verification facility for a multi-vendor environment and offers full technical support from experienced engineers. In recent years, the TSC has seen a significant increase in the number of AI/deep learning verification projects, and opportunities to verify data and service integrations between the TSC system and public cloud services like AWS, Microsoft Azure, and Google Cloud Platform. This growing need for verification of hybrid cloud and AI/deep learning drove CTC to create a new verification environment, AI_LAB, in late 2018. AI_LAB was designed to verify large-scale AI utilization and to build learning models. However, the challenge was to establish a system that could handle the advanced verification requirements of AI/deep learning.

In the digital era, businesses are striving to deploy high-quality experiences faster to succeed. The acceleration of technology innovation and the aspiration to adopt digital business models present challenges for organizations to meet their business needs. Managing multicloud environments has been a significant challenge for many customers due to different consoles, teams, and skills required to realize the benefits of these clouds. Business leaders are mandating their IT departments to consolidate IT infrastructure to save energy costs, host more applications, share resources across different departments, and enhance security. These requirements often translate into fewer data centers and consolidated server, networking, and storage resources that can host multiple applications shared by multiple departments.

Unistar LC, a leading ICT provider in Slovenia, was facing a challenge in facilitating customer access to the cloud. The company had developed more than 10 brands, including Unistar PRO.cloud for hosted and managed IT services, but needed a scalable, cost-efficient, and reliable platform to enhance this offering. Despite being a NetApp partner for over a decade, Unistar LC was uncertain about choosing NetApp solutions. The company needed to ensure that the chosen solution would provide the best value for money, a quick return on investment, and compliance with Slovenia’s strict data protection regulation. Additionally, Slovenia's data protection laws do not allow personal data to leave the European Union or even the country in some cases, which ruled out the option of connecting to an Amazon or a Microsoft cloud.

SAP was looking to launch its HANA Enterprise Cloud (HEC), a preeminent infrastructure-as-a-service (IaaS) solution. The challenge was to find an infrastructure partner that could deliver significant improvements in processing speed, product time to market, and security that SAP customers were expecting. SAP needed a solution that would allow its customers to quickly, easily, and inexpensively run and support SAP HANA applications. Furthermore, the solution needed to be flexible enough to respond quickly to platform changes or technology innovations. SAP also wanted to streamline its customers' cloud adoption by eliminating the need for them to purchase or manage extra storage infrastructure.

GumGum, a company that uses artificial intelligence to determine the context of a webpage and match targeted ads, faced a significant challenge in managing its computing infrastructure. The company's proprietary AI services required a large volume of computing infrastructure with variable demand. While AWS cloud was a solution, the costs were high, especially for AI workloads using GPU instances. The company's success led to rapidly increasing costs in line with the demands on their highly scalable infrastructure. The demands were cyclical, with ad serving varying throughout the year. At peak times, GumGum's Ad Server application received over 18 million requests per minute, requiring more than 130 AWS virtual machines to be provisioned. The company's costs grew to around $120k per month for EC2 on just one of their four Ad Server data centers. GumGum needed a solution that would help them use spot instances, save money, be easy for limited staff to use, and guarantee uptime.

Mellanox Technologies, a multinational supplier of computer technology networking products, was facing challenges with its testing, research, and design infrastructure. The company, with multiple manufacturing sites worldwide, needed an infrastructure that was engineered for integration, easy data sharing, scalability, and unified support. The existing system was not providing the performance and reliability required to accelerate product innovation. Mellanox also needed to reduce the time to market for its products, including adapters, switches, software, cables, and silicon products for markets such as high-performance computing. The company was in search of a unified solution that was reliable, scalable, and cost-effective.

ITOCHU Techno-Solutions (CTC) operates the Technical Solution Center (TSC), a comprehensive facility that allows client companies to evaluate and verify systems to be introduced using actual equipment. It is Japan's largest verification facility for a multi-vendor environment and offers full technical support from experienced engineers. In recent years, the TSC has seen a significant increase in the number of AI/deep learning verification projects, and opportunities to verify data and service integrations between the TSC system and public cloud services like AWS, Microsoft Azure, and Google Cloud Platform. This growing need for verification of hybrid cloud and AI/deep learning drove CTC to create a new verification environment, AI_LAB, in late 2018. AI_LAB was designed to verify large-scale AI utilization and to build learning models. However, the challenge was to establish a system that could handle the advanced verification requirements of AI/deep learning.