Solutions

BEZNext Performance Assurance Solutions for Data Warehouse and Big Data Applications On Prem and in the Cloud

BEZNext addresses challenges of selecting and managing Cloud environments by offering performance assurance solutions for Big Data, Data Warehouses, and Cloud applications. By leveraging Machine Learning and AI algorithms, Queueing Network Models and optimization technology, the company helps customers in different industries select an appropriate Cloud platform and proactively manage Data Warehouse and Big Data applications performance. BEZNext software and services help clients compare performance and scalability, and predict cost to support expected increase in number of users and volume of data.

BEZNext offers Performance Assurance software and services for Big Data and Data Warehouse applications residing On Prem and Cloud

By leveraging Machine Learning and AI algorithms, Queueing Network Models and Optimization technology, the company helps customers in different industries optimize On Prem performance, select an appropriate Cloud platform and proactively manage Data Warehouse and Big Data environments to meet growing business demands with lowest cost

BEZNext Performance Assurance solutions cover three core areas

Performance Engineering

Helping companies in building and implementing new applications that scale and satisfy SLGs with lowest cost

Dynamic Performance Management

Implementing proactive performance management and workload management optimization

Strategic Capacity Planning

Planning IT infrastructure to support growing business demand at lowest cost

Performance Engineering

Our Performance Engineering Solutions Incorporating Modeling and Optimization provide value during DevOps to

Application developers

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Operations

BEZNext Dynamic Performance Management

Our software and services optimize Performance and Workload Management for Data Warehouse and Big Data Applications in Production On Prem and Cloud environments

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BEZNext Capacity Planning

software incorporates modeling and optimization. It is used to compare options and recommend the most appropriate platforms and configuration required to meet SLGs for growing Data Warehouse and Big Data workloads in production On Prem and Cloud environments. It addresses the challenges:

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