OCI Anomaly Detection Service & OIC – Part I by Niall Commiskey

Oracle Cloud Infrastructure (OCI) Anomaly Detection is an AI service that enables developers to more easily build business-specific anomaly detection models that flag critical incidents, resulting in faster time to detection and resolution. Specialized APIs and automated model selection simplify training and deploying anomaly detection models to applications and operations—all without data science expertise. Read more about OCI Anomaly Detection here. My starting point is the workshop, which can be found here

The workshop is very easy to follow – essentially you have the following artifacts –

• Projects – for organizing your work
• Data Assets – links to the data sources which will be used as the basis for anomaly detection.
• Models – ML models trained to detect anomalies. Models leverage Data Assets for the base data.
• Detection – you can upload a file and test it against the model, or else you can leverage the Anomaly Detection api for this. We will be using the latter, in respect of OIC.

So now to the simple workshop example – the starting point is a .csv file containing sensor readings. Read the complete article here.

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