Endpoint Security

Prevent Data Downtime with Machine Learning

Data downtime is highly costly for organizations and causes significant problems for immediate and downstream teams when a data ingestion pipeline breaks because of a bug, misconfiguration, traffic spike, network issue or malicious attack. Applying Machine Learning to your data in Splunk can help you find these warning signs in advance and enable your team to address potential issues before there’s a consequential impact.

In this webinar, we’ll showcase how machine learning can be used to improve the ‘getting data in’ experience with Splunk. Specifically, we will demonstrate how to set up an automated alerting system that detects unexpected downtimes or spikes in your data ingestion volumes.

Learn how to:

  • Leverage the power of machine learning search commands with SPL and MLTK
  • Set up an anomaly detection model for monitoring data inputs
  • Build a dashboard & implement alerting to enable real-time monitoring

About the Author

Information Security Media Group (ISMG) is the world's largest media company devoted to information security and risk management. Each of its 37 media sites provides relevant education, research and news that is specifically tailored to key vertical sectors including banking, healthcare and the public sector; geographies from the North America to Southeast Asia; and topics such as data breach prevention, cyber risk assessment and fraud. Its yearly global Summit series connects senior security professionals with industry thought leaders to find actionable solutions for pressing cybersecurity challenges.

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