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An Automation Architecture to Reduce MTTR

Reducing MTTR in today’s complex, heterogeneous networks isn’t about detecting or fixing a problem more quickly — it’s about being able to identify the problem faster and then leveraging post-mortem lessons learned so you can do better next time.

Most approaches to reduce incident-response and resolution times have failed because they do not solve the biggest time hog, Mean Time to Identify (MTTI).

This paper lays out a systematic approach to automate troubleshooting diagnostics at scale and integrate workflow automation.

Topics covered:

  • The urgent need to reduce MTTR
  • The challenges in reducing MTTR, especially the “scalability challenge”
  • A framework for incident response — where along the workflow you can make greatest improvement
  • An automation framework to continuously improve MTTR, exploring closed-loop improvement
  • How NetBrain automates troubleshooting as scale



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