NETSCOUT: Rethinking AIOPs – It’s all about the data

A conversation with Rick Fulwiler at NETSCOUT on optimizing network operations with AIOps

In network operations, we are always looking for areas for improvement. How can we manage applications to best serve end customers? How can we use end-to-end visibility of application and service performance to improve customer experience? Will anomaly detection for automated pattern discovery and prediction improve the quality of experience? What is the best way to use software-driven networks to support new services and monetization strategies?

Rick Fulwiler, Chief Solutions Architect at NETSCOUT, addressed these questions in this discussion on how AIOps is becoming the focal point driving transformation in network operations across all lines of business—IT, enterprise, cable, security and wireless—and how its success requires rich and reliable network data.

  • Network data is hidden gold we need to mine to move from traditional operations to AIOps. How do we meet the challenges of extracting this gold for AIOps?
  • The quality of data determines the quality of the results. How do we curate the rich data collected at the source to make complex analytics successful at scale?
  • How can scalable AI sensors at the source reduce data blot by feeding consumable, actionable data to 3rd-party AIOps engines?
  • AI and ML are no silver bullets; every model has a specific behavior. How can we choose the right model for a task?
  • How can we integrate the mined data into the AIOps ecosystem?

More from NETSCOUT:

Next-Level AI for Telecom Networks

Conversation timestamps

  • 00:05 Introduction, AIOps, NETSCOUT
  • 03:30 Rick introduces himself
  • 04:18 What is AIOps and why it matters, learning from other industries
  • 07:02 Are AI and AIOps ready to be deployed commercially? Use cases
  • 10:47 Data requirements for AIOps, hidden gold to be mined
  • 13:59 What data is relevant? How to curate data, how data requirements are changing with 5G standalone
  • 19:50 Data and AIOps in a multivendor environment, role of standardization, KPIs definition
  • 25:23 Best practices for data curation, advice from NETSCOUT
  • 29:37 AI sensors to capture real-time packet-level data, use cases, NWDAF
  • 39:37 More use cases, monetization, value creation
  • 43:32 Business case, quantifying the benefits, APIs
  • 46:24 Role of GenAI, telco-specific models
  • 52:00 Why is NETSCOUT supporting AIOps, need for real-time data, interest and investment in AIOps
  • 57:51 Reliability, what the future stores

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