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BEZNext Hands-On Workshop

Hybrid Multi-Cloud Performance and
Financial Optimization

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We invite you

to join BEZNext workshop

If you are evaluating options of migrating your Data Warehouse workloads to the cloud and are concerned with the cloud data platform selection, optimizing cloud migration decisions, organizing dynamic performance and financial management of your Data Warehouse workloads, optimizing DevOps decisions and predicting the electrical power and carbon footprint in a Hybrid Multi-Cloud environment,

THIS WORKSHOP IS FOR YOU! 

WHAT YOU WILL LEARN

During the workshop, you will learn: The methodology and technology of the Hybrid Multi-Cloud performance and financial (FinOps) decisions optimization.
The workshop includes
Lectures
Exercises
Quizzes
Calendar
The workshop duration is three weeks,
with 3 hours of instructor-led lectures
and exercises per week.
IT Leaders, Architects, DBAs, Developers and Operations involved in Cloud Selection, Migration, Capacity management, and DevOps will benefit from attending this hands-on workshop.
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​During the exercises, you will use our modeling technology.

You can use our measurement data or data collected in your environment.

​If you want to use measurement data collected in your environment, we offer several options:

Computer Programming

Install our software in your environment and collect customer measurement on-prem and cloud data platforms

Data Processing

Access your measurement data by our tools from our AWS cloud environment

Data on a Touch Pad

You can collect the measurement data and export it to our lab using our scripts

Person Analyzing Data

You can provide measurement data extracted using other tools

Why is it critically important?


Organizations in virtually every industry are moving Data Warehouse and Big Data Hadoop workloads to Cloud Data Platforms.

Clouds have practically infinite capacity, but organizations do not have unlimited budgets. Unfortunately, they often select the Cloud Data Platform before fully understanding the“character” of their business workloads. If done without considering the workloads’ performance, resource utilization and data usage profiles, their service level goals (SLGs), and without realistic performance and financial expectations, that early decision can cost organizations millions in wasted spending in years to come.


BEZNext modeling and optimization engines use the results of the workload characterization, expected workload and volume of data growth to predict the minimum configuration, carbon footprint and budget needed to meet SLGs for all workloads on each cloud data platform before making the financial commitment.


In addition, BEZNext provides cloud migration decision optimization, organizing dynamic capacity management, and detecting the anomalies, root causes and seasonality changes for all workloads. Dynamic capacity management generates proactive recommendations on how to meet SLGs with the lowest cost.