Grok AIOps for Network Operations

Intelligence and Scale Built for Service Assurance

Navigate through the “sea of red” and rely on Grok to separate the signal from the noise to improve MTTI and MTTR without having to create and maintain rules. Integrate with both off-the-shelf and home-grown management tools, while maintaining the ability to scale to the highest event volumes and support the growing business.

Network service outages can trigger hundreds or thousands of alarms across multiple nodes. A single condition, like a fiber cut, can create a cascading effect and result in a “sea of red” in your monitoring tools. This creates huge challenges to quickly determine root cause and take remediation steps. Grok AIOps leverages machine learning to quickly and easily model the infrastructure and utilizes powerful event clustering algorithms to correlate like events and surface probable root cause. Resources can focus on the real problem. Reduce MTTI and MTTR, while more efficiently using resources to ensure your services are up and running.

Eliminate Noise and Correlate to Probable Root Cause

Quickly Isolate and Identify Performance Issues

Performance issues and service degradations are difficult to isolate and remediate. Oftentimes, network and service operators see performance issues such as frame errors, pchip errors, or errant lines, but these can be symptomatic of a bad card or a bad line which can be quickly addressed. The root cause of these issues, however, can be difficult to find, diagnose and correlate. The process can take multiple hours and is resource-intensive. Grok AIOps models your network and infrastructure in real-time and is able to quickly analyze multiple performance metrics, logs, and events. This enables efficient correlation to a probable root cause and effective workflow assignment, guaranteeing issues are quickly addressed.

Find Issues with Early Detection and Advanced Notification to Prevent Outages and Problems

As organizations undergo digital transformation initiatives, the increasing volume of data from networks, systems, applications, and tools continues to grow exponentially. Without appropriate tools to manage the vast volume of these changes, organizations will struggle to proactively manage their environment. Grok AIOps utilizes machine learning to provide an early warning system for event stream analysis by creating incident signatures. When incoming events begin to match recognized signatures, operators can be immediately notified to take remedial actions before a critical outage or incident occurs.

Scale and Logically Manage Event Streams Relevant to Your Business

Every environment has one, but sometimes multiple, massive event pipes being managed and monitored by existing tools. However, analyzing, modeling and making sense of this data is challenging. Grok ingests these events at scale from off-the-shelf or homegrown, custom tools. Grok then provides a unique event splitting and shaping capability that leverages machine learning to help separate, combine and pre-process event streams by a particular services, networks (metro, long haul, RF, etc.), device types (Ciena, Inifinera, Huawei, Cisco, etc), customers, or across multiple dimensions, to ensuring results that are relevant to your business.