Aggregate

Aggregation refers to the process of combining, summarizing, or consolidating raw data to create more compact and manageable datasets, often in the form of aggregated metrics. This process involves transforming high-frequency or detailed data points into a condensed and more meaningful representation. Aggregation serves several important purposes in telemetry and monitoring systems:

Reducing Data Volume: Telemetry pipelines often deal with high volumes of data generated by various sources. Aggregation helps reduce the overall data volume by summarizing information over specific time intervals or based on certain criteria. This is crucial for managing storage, network bandwidth, and computational resources efficiently.

Improving Performance: Aggregated data is generally easier and faster to process than raw, high-frequency data. By aggregating information, telemetry systems can achieve better performance in terms of data processing, analysis, and reporting. This is particularly important for real-time monitoring and analytics.

Resource Optimization: Aggregation contributes to resource optimization by reducing the load on storage systems and databases. Storing aggregated metrics instead of raw data can lead to significant savings in terms of storage space.



interval_ms

Optional: Defines the interval between flushes, in milliseconds.

Description: Metrics with the same series data (e.g., name, namespace, tags) are aggregated during this time frame.

Default: 10,000 ms (10 seconds).

Example: interval_ms: 5000 (5 seconds).



mode

Optional: Specifies the function used for aggregating metrics.

Description:

Some functions apply only to incremental metrics, while others are suitable for absolute metrics.

Enum options:

Default: Auto.

Example: mode: "Sum"