Predictive Analysis of Storage Health and Performance for Heterogeneous Environment

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Publish Date: 
Wednesday, September 23, 2020
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The modern data centre is an incredibly complex system having heterogeneous devices. Keeping that complex system up and running is difficult enough without accounting for potential problems that might arise in the future. Fortunately, the last several years have seen significant improvements in predictive analytics. But the challenges are around monitoring, managing and predicting events in an IT infrastructure. This session is to give a case study of how "telemetry" and "anomaly detection" can be put together to solve data centre predictive analysis problems using available open source solutions, especially for a heterogeneous environment with different vendor storages or application clients The data and discussion are based on the actual development and experiments on open source projects under SODA Foundation. We explore the various requirements on heterogeneous storage health and monitoring requirements (like different clients, different predictive algos, different storages, different visualizations and more)

Learning Objectives

Learn open source telemetry and analytics solutions,SODA foundation and its role in unifying hetrogeniuos platforms in to a single pane,ML algorithms for finding hotspots in data path,SRM use case and application of analytics

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