From the course: DevOps Foundations: Monitoring and Observability
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Machine learning and observability
From the course: DevOps Foundations: Monitoring and Observability
Machine learning and observability
- [Instructor] With the advent of AI and machine learning technologies, the observability space has also benefited and leveraged this in different ways. Some of the applications of machine learning and AI are, anomaly detection, this is when your observability tool is able to detect changes in the trend of your data, for example, a sudden increase in the volume of logs a service is emitting. With machine learning, you can compare the current trend to previous trends and use this to determine if the thresholds are out of bounds. This can also be alerted on, so that you and your team can respond proactively to these types of issues. Next, you have root cause analysis. Incident response tools and observability tools can suggest root causes for incidents based on the trend of incidents that are usually triggered around the same time. If you send multiple signals like your metrics, logs, and traces to the same tool, they…
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