Using GPT-3 for plain language incident root cause from logs
Zebrium uses unsupervised machine learning to automatically find root cause.
A few weeks ago, Ltheir CTO, wrote about a new beta feature leveraging the GPT-3 language model - Using GPT-3 for plain language incident root cause from logs. To recap – Zebrium’s unsupervised ML identifies the root cause of incidents and generates concise reports (typically between 5-20 log events) identifying the first event in the sequence (typically the root cause), worst symptom, other associated events and correlated metrics anomalies.
The GPT-3 integration allows them to take the next step – distill root cause reports down to concise natural language summaries by scanning the entire internet for occurrences of a similar incident, and extracting brief “English” descriptions for a user to scan.
You can read the full blog post here: https://www.zebrium.com/blog/real-world-examples-of-gpt-3-plain-language-root-cause-summaries-zebrium