Automatically identify the

root cause of an IT incident

Reduce MTTR by up to 50% by harnessing AI to automatically identify the underlying cause of an IT incident and its impact across complex hybrid cloud deployments.

See it in action

How Automated Root Cause Analysis works

BigPanda AI automatically identifies the factors causing IT incidents and suggests actions in real-time how to resolve them.

Detect IT incidents with relevant data

BigPanda correlates alerts across your hybrid cloud deployments with change, topology, and available CMDB data to build actionable and contextually rich incidents in real-time.

Determine the change that triggered an incident

Visualize the full history of alerts chronologically to understand where the problem with an incident first started.

Identify change-related root cause of an incident

Advanced AI identifies high-confidence alerts and change data matches, providing users with a comprehensive view of statistically important changes that caused the incident.

Confidently identify and explain impact across IT systems

BigPanda Generative AI explains the probable root cause and impact of incidents across interrelated IT systems in a natural, easy-to-understand way.

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Automated Root Cause Analysis has arrived for ITOps

FAQ

What is Root Cause Analysis (RCA)?
A Root Cause Analysis (RCA) examines the highest level of a problem to find the root cause. This is traditionally a post-mortem practice used to improve processes. Conducting an RCA lets you accurately determine the root cause of incidents, identify flawed processes, and discern underlying causes rather than surface symptoms to get to the root of recurring issues early on.
Why use Root Cause Analysis (RCA) for IT Operations?
RCAs in IT and ITOps are traditionally used post-outage to discover how to prevent similar outages in the future, maintain an agile environment, improve processes, and eliminate known symptoms. BigPanda enables ITOps teams to automate Root Cause Analysis and fix issues at the source in real-time to greatly reduce their Mean Time to Resolution (MTTR).
What are Root Cause Analysis techniques?
Standard RCA methods and techniques can include a causal factor tree analysis, barrier analysis, risk tree analysis, fault tree analysis, the Kepner-Tregoe method, the Five Whys, Pareto charts, fishbone diagrams, scatter diagrams, Failure Mode and Effect Analysis (FMEA). We recommend automating your Root Cause Analysis with AI-powered tools and techniques to make conducting your RCA more accurate and faster.
How to do Root Cause Analysis?

A Root Cause Analysis is typically conducted post-mortem using RCA techniques. However, your team must also prioritize swiftly identifying issues in real-time, automating root causes, and fixing the root causes at their source to gain efficiency. Learn how to conduct a Root Cause Analysis in our blog.

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