Observability, modeling and control

A new approach to cloud cost optimization and performance control

BEZNext's innovative methods and software deliver a groundbreaking systems approach to optimizing costs and controlling the performance of your applications in a Hybrid Multi-Cloud environment.

Performance and cost

Each business application has a unique performance, resource utilization, data usage, and cost profile. Businesses rely on IT to consistently meet performance service level goals (SLG) for business applications. The challenge arises as the number of active users and volume of data processed fluctuate, changing resource demands and affecting performance and cost. Meeting application SLGs in the cloud is no easy task.

Application response time has a non-linear relationship with resource utilization. As the number of users and the volume of data increase, resource utilization grows. Once it reaches a certain threshold, response time increases exponentially, affecting the performance and cost.

Optimizing cost and performance for fast-growing Generative AI (GenAI) applications powered by large language models (LLMs) presents even greater challenges. Organizations relying on FinOps technology or conducting LLM benchmark tests can evaluate the performance of simple and complex AI requests, they fall short of determining the most suitable cloud data platform, the minimum configuration, or the budget required to train, maintain, and run AI applications while satisfying SLGs.

As a result, cloud infrastructure selection and workload management decisions in Hybrid Multi-Cloud AI environments are often made with uncertainty, carrying a high risk of performance and financial surprises.

BEZNext's software and services are specifically designed to tackle these complex challenges. We simplify the planning and management of your intricate cloud AI environment, empowering you to optimize costs, maintain performance targets, and reduce risks.