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AI monitoring is a critical process which involves continuously observing and analyzing AI applications to maintain their health and efficiency.
It goes beyond traditional application monitoring, since it involves tracking specialized metrics and data specific to AI operations. Some of the key aspects include:

  • Model performance: monitoring the performance of AI models using metrics such as accuracy , precision, recall and F1-score.
  • Data Monitoring: monitoring Data Integrity and Drift.
  • Resource consumption: AI applications can be computationally intensive and may require significant resources, including CPU and GPU usage, memory, and storage, hence resource consumption must be monitored at all time.
  • API usage: tracking metrics like request rates, response times, and throughput for all APIs (Application Programming Interface) involved.