Details
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Bug
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Status: Resolved (View Workflow)
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Minor
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Resolution: Fixed
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29.0.2
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None
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Security Level: Default (Default Security Scheme)
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None
Description
When the changes for NMS-13807 was merged to foundation-2021, there were conflicts with other changes to docs/modules/operation/pages/flows/introduction.adoc that had happened in release-29.x.
I resolved them, I think, but it should be reviewed in the H29 branch to be sure I did it right. 
Foundation-2021 version:
* <<telemetryd/introduction.adoc#ga-telemetryd, Telemetryd>> receives and decodes flows on {page-component-title}.
* Telemetryd adapters convert the flows to a canonical flow model and dispatch these to the flow repository.
* The flow repository enriches the flows and persists them to Elasticsearch:
** The <<flows/classification-engine.adoc#ga-flow-support-classification-engine, classification engine>> tags flows with an application name.
** Metadata related to associated nodes (such as IDs and categories) are also added to the flows.
* The REST API supports generating both summaries and time series data from the flows stored in the flow repository.
* OpenNMS Helm visualizes the flow data through the flow datasource, which interfaces with the {page-component-title} REST API.
Horizon 29 version:
* <<telemetryd/introduction.adoc#ga-telemetryd, Telemetryd>> receives and decodes flows on both {page-component-title} and Minion.
* Telemetryd adapters convert the flows to a canonical flow model.
* Flows are enriched:
** Flows are tagged with an application name via the <<flows/classification-engine.adoc#ga-flow-support-classification-engine, classification engine>>.
** Metadata related to associated nodes (such as IDs and categories) are also added to the flows.
* Enriched flows are persisted in Elasticsearch and/or forwarded to Kafka.
* You can use <<flows/nephron.adoc#ga-nephron, Nephron>> to aggregate flows and output aggregates to Elasticsearch, Cortex, or Kafka.
* The REST API supports generating both summaries and time series data from the flows or flow aggregates stored in Elasticsearch.
* Use OpenNMS Helm to visualize flows and/or flow aggregates:
** Use the "Flow Deep Dive" dashboard to visualize flows and flow aggregates that are stored in Elasticsearch using the flow datasource that interfaces with the {page-component-title} REST API.
** Use the "Cortex Flow Deep Dive" dashboard that uses a Prometheus datasource to access flow aggregates stored in Cortex.
My modified version committed to release-29.x:
* <<telemetryd/introduction.adoc#ga-telemetryd, Telemetryd>> receives and decodes flows on {page-component-title}.
* Telemetryd adapters convert the flows to a canonical flow model.
* Flows are enriched:
** The <<flows/classification-engine.adoc#ga-flow-support-classification-engine, classification engine>> tags flows with an application name.
** Metadata related to associated nodes (such as IDs and categories) are also added to the flows.
* Enriched flows are persisted in Elasticsearch and/or forwarded to Kafka.
* You can use <<flows/nephron.adoc#ga-nephron, Nephron>> to aggregate flows and output aggregates to Elasticsearch, Cortex, or Kafka.
* The REST API supports generating both summaries and time series data from the flows or flow aggregates stored in Elasticsearch.
* Use OpenNMS Helm to visualize flows and/or flow aggregates:
** Use the "Flow Deep Dive" dashboard to visualize flows and flow aggregates that are stored in Elasticsearch using the flow datasource that interfaces with the {page-component-title} REST API.
** Use the "Cortex Flow Deep Dive" dashboard that uses a Prometheus datasource to access flow aggregates stored in Cortex.
