Develop an AI-driven anomaly detection system that analyzes cloud monitoring metrics to detect unusual resource usage patterns and predict potential failures, improving proactive cloud infrastructure management.
Collect historical cloud metrics data.
Preprocess time-series datasets.
Implement anomaly detection algorithms (Isolation Forest, LSTM).
Deploy monitoring agents on cloud instances.
Visualize anomalies using dashboards.
Configure automated alert triggers.
Test detection accuracy using simulated spikes.
Evaluate false positives and precision metrics.
Deploy system on cloud environment.
Document AI workflow and monitoring integration.
