BEZNext
A Smarter Approach to Application Performance Assurance

Companies are considering adopting cloud platforms because of the significant advantages they have in developing new applications faster and decreasing costs with their pay-as-you-go model. It is becoming critically urgent now for many organizations to move workloads to the Cloud to handle spikes in the workload demand caused by coronavirus and requirements to IT to do more with less.

But, migrating to the Cloud comes with two critical challenges.

The first challenge is selecting a cloud and DBMS platform capable of scaling well while meeting rapidly growing business needs. User populations are increasing rapidly because of digital transformation. Meanwhile, data volumes are exploding because of IoT, social media and other trends. With the wrong cloud or data platform it becomes impossible to meet goals for cost; for online performance; or, for the timely delivery of business recommendations.

The “Trial and Error” approach of selecting and managinga Cloud platform for Data Warehouse and Big Data workloads is too risky: it can take far too long and cost much more than expected to find a workable solution.

The second challenge is controlling resource allocation in the Cloud to meet business Service Level Goals (SLG) with the lowest cost. How can you create workload management and resource allocation rules that reflect workload seasonality? How can you optimize performance and continuously meet business SLGs most effectively?

BEZNext addresses these challenges 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.

In an interview with CIOApplications, Boris Zibitsker, CEO of BEZNext, provides an intriguing insight into the company and the solutions they offer.

Please tell our readers about your offerings and how they help BEZNext’s clients to achieve their unique business goals?

Broadly, our performance assurance solutions cover three core areas. The first one is performance engineering, helping companies build and implement new applications with assurance that new applications will perform well.

We apply modelling to evaluate the design and implementation options and select the appropriate platform, as well as optimize workload management rules to meet SLGs for new applications with minimum cost.

The second area of performance assurance is dynamic performance management, where our software automatically determines the most frequent and severe anomalies and their root causes, seasonality, applications availability and balance of resource utilization. Our modelling technology is used to compare the impact of the different performance management and workload management options and recommend the most appropriate solutions.

The third area of performance assurance is strategic capacity planning, which is about meeting business goals for growing workloads and increasing volume of data in a future. Capacity planning recommendations include selecting the appropriate Cloud and optimizing workload management rules to meet SLGs for growing workloads during the next year with lowest cost. It also includes predicting the cost of supporting expected workload and volume of data growth in the Cloud.

How do you help companies make effective decisions about choosing the right cloud platform?

With companies having overwhelming growth in number of users and volume of data, there is always a debate which applications and data are good candidates for shifting to the cloud and which cloud platform is the most appropriate. To solve such a dilemma, we apply our performance assurance solutions. We incorporate modelling and optimization to predict the number and type of instances which will be required. We also predict the cost of running On Prem applications on different Cloud and DBMS platforms, like Redshift, Snowflake and Vantage during next year.

First, we collect and aggregate measurement data into business workloads. Then we perform workload characterization for Data Warehouse, Big Data and Cloud environments. Each workload is characterized by performance, resource utilization and data usage profile for each hour of the day. Then we use modelling topredict the minimum configuration which will be required to meet SLGs, compare the scalability and predict cost of different platforms. This helps our customers decide which workloads are good candidates for moving to the cloud as well as which cloud platform will be able to support SLGs for growing workloads during next year with lowest cost.

What makes BEZNext unique in the marketplace?

What differentiates us from our competitors is the use of automatic workload characterization, modelling and optimization to determine the most appropriate decisions. For example, if the company wants to find the appropriate Cloud and determine the minimum configuration required to meet SLGs with the lowest cost, we apply ML and AI algorithms to automatically determine the seasonality for each workload and optimize resource allocation rules taking advantage of Cloud elasticity and managing resource allocation. By doing so, we are able to find the right solution that will meet SLGs for constantly growing and changing workloads and increasing volume of data.

Performance prediction results set realistic expectations and enable automatic results verification by comparing the actual results with expected.

What does the future hold for your company?

To stay abreast of digital transformation challenges, we are expanding our performance assurance solutions to support new Cloud and DBMS platforms.

We believe performance assurance solutions that incorporate artificial intelligence, modelling and optimization can help companies to make better decisions, reduce uncertainty and risk of performance surprises and make a difference in planning and managing constantly growing and changing workloads in the Cloud.