Global Cloud Environment: Data Analysis and Management Workload - Computer Measurement Group

Global Cloud Environment: Data Analysis and Management Workload

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Global Cloud Environment: Data Analysis and Management Workload

Often IT companies are facing with multiple challenges in case if they decide to create globally distributed cloud based environment, like well-known problem of big data, including storing client accounts in a database, protocoling user activity in the logs, transferring real time dataflow, processing big data analytics, etc.

The session addresses the challenges of a digital cloud environment when it comes to a global scalability with a big amount of remote servers and unsecure public cloud, such as Amazon. The goal of the study is to work out the approach for evaluating the reasonable system capacity under heavy workload. For that purpose, Zabbix monitoring solution is used and business metrics are applied in relation to existing system ones. Prediction data model is proposed to compute the future forecast of the user activity based on the collected historical statistics and verify whether capacity adjustment is possible or not. The results of capacity planning are implemented at Genesys International Telecommunications Company. System analysis of the production environment indicated the possibility to downscale the capacity of certain virtual servers, which allowed saving the annual operational cost by $3,500 (50%) for each affected server.

Takeaways:

  • Workload Management in Public Cloud
  • Monitoring System and Prediction Models
  • Architecture Models and Cyber Security Issues

INTERVIEW:

 

About The Speakers:

Dmitry Shchemelinin is a VP SRE & NOC at RingCentral. He is an innovative, highly accomplished manager with proven success in restructuring and optimizing technical operations within start-up and high-growth environments as well as in supporting huge infrastructures of international companies in SaaS and Telecommunications area. A-player with excellent topgrading experience. Background includes supporting company goals by automation IT systems operations and deployment processes, innovations and integrations, acquisitions and managing large SRE & DevOps teams across geographies and time zones.

Mikhail Buinevich is a Doctor of Science and a Professor at Saint-Petersburg University of State Fire Service of EMERCOM of Russia.

 

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