The basic architecture of technology in enterprises is seeing a paradigm shift. The constant need for artificial intelligence has highlighted the inherent limitations of traditional cloud computing. This has given rise to a new breed of cloud computing service providers: neo clouds. These are specialized, alternative clouds meant to provide high-performance computing capabilities. Neo clouds are changing the way business enterprises, especially those involved in complex Configure, Price, Quote, and Optimize (CPQO) processes, can access computing capabilities.
Neo clouds: An industry perspective
Neo clouds are defined as a new breed of cloud computing service providers. These clouds provide high-performance computing capabilities in the form of GPU-as-a-Service (GPUaaS), especially for artificial intelligence. Neo clouds are different from hyperscalers such as Amazon Web Services (AWS), Microsoft Azure, and Google Cloud. They provide massive parallel processing capabilities required by machine learning, deep learning, and data analytics.
The key characteristics that define neo clouds in a professional environment are:
GPU-native architecture: They have infrastructure designed with powerful, and in many cases, latest generation GPUs (NVIDIA H100, etc.) at their core, with high-speed interconnects such as NV Link and InfiniBand to ensure maximum performance with zero bottlenecks.
AI-optimized stack: They provide pre-configured, containerized stacks that can run popular ML frameworks such as PyTorch, TensorFlow, and Hugging Face, making it much easier for DevOps to do their tasks quickly.
Flexible and cost-effective models: Neo clouds have a transparent billing structure, with pay-per-use or job-based billing, making them much cheaper to operate compared to traditional cloud infrastructure, with reports of up to 66% cost savings in certain tasks, especially in comparison to traditional cloud billing models based on instance uptime, etc.
Sovereignty and compliance: Many neo clouds have been designed to accommodate regional sovereignty and compliance requirements, such as GDPR, which is critical for industries that have high regulatory requirements, such as finance or healthcare. The prominent players in this space are CoreWeave, Lambda, Crusoe Cloud, etc.
Strategic rationale: Why neo clouds exist
Neo clouds are an evolutionary response to changes in technology and market trends that have developed over time. They exist because of the following:
Hyperscaler capacity pinch: The sudden growth of generative AI created an unprecedented demand for the best GPUs that the large cloud providers couldn’t fulfill at first.
Performance issues: Traditional cloud environments are heavily virtualized and heavily invested in CPU performance, resulting in latency issues for high-parallel, computationally intense tasks. Neo clouds bypass these problems entirely.
Narrower focus, sharper execution: Hyperscalers try to cater to every IT requirement, while neo clouds are laser-focused on the AI market.
Risk management and vendor diversity: Companies are increasingly adopting multi-cloud strategies because of the fear of vendor lock-in. Neo clouds are strategic partners of the hyperscalers, providing an alternative critical mass of compute resources.
Enterprise leverage and CPQO context, reimagined in a free-flowing style
Companies are integrating neo clouds with their existing hybrid infrastructures, allowing this hybrid engine to power their next-gen compute for targeted AI workloads, while their traditional infrastructures remain ready to support their day-to-day needs.
As for configure, price, quote, and optimize solutions, neo clouds provide the power plants to propel the next generation of AI-driven innovation:
Optimization and pricing: CPQO utilizes complex simulation to provide detailed product configuration and dynamic pricing. With on-demand high-performance computing from neo-cloud-high-performance GPUs, real-time optimization and faster, more competitive quotes become a reality.
Advanced analytics: With CPQO now leveraging large language models and other ML models, it is now able to tap into deeper analytics with the support of neo clouds.
AI features: As CPQO continues to evolve with new features and capabilities, including those that are now AI-driven, neo clouds can support new demands for AI computing.
Strategic flexibility: Neo cloud’s GPU-as-a-Service feature offers the potential to move away from traditional CapEx models to a new, innovative, and flexible OpEx model.
Given their flexibility and formidable computing capabilities, neo clouds represent the next big step in cloud evolution and are of strategic relevance to enterprise operations of the future.