Metrics for data ingestion and processing

Data ingestion rate: The amount of data ingested by monitoring systems in a given time period which indicates that the system can effectively process large volumes of telemetry data, leading to more accurate insights. Measure this metric by calculating the volume of data ingested by the monitoring systems per unit of time.

Data processing latency: The time it takes for telemetry data to be processed and made available for analysis. Lower data processing latency aims to quickly assess and act on insights from telemetry data. Measure the time elapsed between data ingestion and the availability of processed data for analysis.

Data cost efficiency: Measuring the cost of collecting, storing, and processing telemetry data compared to the number of actionable insights generated or decisions made based on these insights. This metric assures that resources are utilized effectively and unnecessary expenses are minimized. Calculate the total cost of data collection, storage, and processing, and contrast it to the actionable insights they provide.

Anomaly detection rate: The percentage of anomalies detected by the monitoring systems. A higher anomaly detection rate indicates that the system is effective in identifying potential issues, enabling teams to proactively address them. Measure this metric by calculating the number of anomalies detected by the monitoring systems, divided by the total number of events, then multiply by 100 for the percentage.