Artwork

Content provided by SNIA Technical Council. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by SNIA Technical Council or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
Player FM - Podcast App
Go offline with the Player FM app!

#113: Latency is more than just a number

51:26
 
Share
 

Manage episode 245652126 series 1393477
Content provided by SNIA Technical Council. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by SNIA Technical Council or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
Over the years, SSD QoS has become more important to a variety of storage market segments. Traditional latency reporting methods do not always accurately depict QoS behaviors. This is problematic when attempting to understand what events lead to a specific QoS level and how to mitigate latency events that lead to levels of QoS. Defining correct statistical techniques for large populations of latencies deepens our understanding of what drives levels of QoS. Advanced statistical techniques, such a machine learning and utilizing AI, allows for deeper understanding of what drives QoS and how to correctly manage large quantities of latencies. New visualization techniques enhance capabilities to understand latency behavior and define critical scenarios that drive latency. Learning Objectives: 1) Identify shortcomings of current QoS reporting; 2) Generate more reliable QoS values; 3) Techniques to broaden understanding of groups of latencies; 4) Identification of critical transitions in latency; 5) Identify inaccuracies that inhibit understanding QoS.
  continue reading

146 episodes

Artwork
iconShare
 
Manage episode 245652126 series 1393477
Content provided by SNIA Technical Council. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by SNIA Technical Council or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
Over the years, SSD QoS has become more important to a variety of storage market segments. Traditional latency reporting methods do not always accurately depict QoS behaviors. This is problematic when attempting to understand what events lead to a specific QoS level and how to mitigate latency events that lead to levels of QoS. Defining correct statistical techniques for large populations of latencies deepens our understanding of what drives levels of QoS. Advanced statistical techniques, such a machine learning and utilizing AI, allows for deeper understanding of what drives QoS and how to correctly manage large quantities of latencies. New visualization techniques enhance capabilities to understand latency behavior and define critical scenarios that drive latency. Learning Objectives: 1) Identify shortcomings of current QoS reporting; 2) Generate more reliable QoS values; 3) Techniques to broaden understanding of groups of latencies; 4) Identification of critical transitions in latency; 5) Identify inaccuracies that inhibit understanding QoS.
  continue reading

146 episodes

All episodes

×
 
Loading …

Welcome to Player FM!

Player FM is scanning the web for high-quality podcasts for you to enjoy right now. It's the best podcast app and works on Android, iPhone, and the web. Signup to sync subscriptions across devices.

 

Quick Reference Guide