Root cause analysis is complex and time-consuming, and often takes place as a post-mortem well after user and business impact has already occurred.
Troubleshooting shouldn’t be so hard
Despite all the innovation in application management, including widespread adoption of machine learning and AI, troubleshooting is still a task that’s left to humans – and it’s full of challenges.
Siloed monitoring doesn’t capture interactions between apps or infrastructure components.
You can’t infer from the code how one app will interface with others.
Troubleshooting requires intricate knowledge of applications’ interactions with each other and the underlying infrastructure.
Multiple people or teams are often responsible for monitoring different apps, infrastructure, or even services within them.
Organizational conflict arises between teams when failures happen, due to gaps between expertise and tooling.
Automating troubleshooting requires causality
“Machines' lack of understanding of causal relations is perhaps the biggest roadblock to giving them human-level intelligence.”
– Judea Pearl, Turing Award winner and author
The Book of Why: The New Science of Cause and Effect
Current troubleshooting tools are built on correlation and anomaly detection technologies. These approaches use data and models that assume the future will look a lot like the past.
Unfortunately, this doesn’t work in environments where applications, databases, infrastructure, and software versions are constantly changing – so it can take hours or even days for humans to determine causality.
A new approach is needed. One that captures human knowledge in structured and abstract data models to help software “learn” causality and relieve humans of this burden.
Causely delivers this critical solution for the IT industry.
Introducing the IT industry’s first causal AI platform
Our breakthrough causal AI platform captures, represents, and analyzes causality. It uses structured causal models to identify defects, determine root cause and propagated symptoms, and automatically remediate.
Causely for Kubernetes apps is now available for early access
The first Causely service built on our causal AI platform detects and remediates application failures in Kubernetes environments.Try it now