The workshop will take place at the annual meeting of the SPEC RG Predictive Data Analytics Working Group at the ICPE 2022 on the 11th of April 2022 at 7pm CEST.
The following is planned to be our program schedule:
|19:00||Gathering and welcome (André Bauer, Uni Würzburg)|
|19:05||Keynote: Modeling and optimization expand results of load testing and benchmarking (Boris Zibitsker PhD, CEO BEZNext)|
|19:35||Questions and discussion regarding the keynote|
|19:50||Introduction of the SPEC RG Predictive Data Analytics (André Bauer, Uni Würzburg)|
All times are based on CEST.
KEYNOTE: Modeling and optimization expand results of load testing and benchmarking
By Boris Zibitsker PhD, CEO BEZNext, email@example.com
For most organizations, the journey to the cloud is well underway. Unfortunately, many cloud migration decisions do not have realistic performance and financial expectations, leading to unwelcome performance and financial surprises.
Many organizations rely on Load Testing, TPC benchmarks, and customized Proof of Concept tests to evaluate options, including selecting the right cloud data platform, migrating to the cloud, organizing dynamic capacity management, and optimizing DevOps decisions.
Benchmark tests provide a lot of valuable information; however, after spending a lot of time and effort, organizations can’t find the answer to critical business questions like:
- What minimum configuration and budget are needed to continuously meet the business service level goals on different cloud platforms?
- How to organize data load in the cloud to finish data load during the acceptable batch window?
- How to select the right cloud platform during the DevOps process before new application deployment?
- How to predict the power consumption and carbon footprint by cloud data platforms after migration for a specific business workload in the cloud?
Our unique approach includes:
- Automated and continuous, closed-loop Performance and Financial Governance
- A combination of Iterative Queueing Network Modeling and Gradient optimization for evaluation options and setting realistic expectations
- Automated verification of performance and financial results.