IPF Application Data Considerations
This page is written to help explain the components of an IPF solution, where data is present and where that data is exposed for client usage:
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Diagram - shows a typical IPF solution and the data touch points, each labelled/numbered.
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Table - the table which follows gives a description of each data type, intended purpose and references to IPF developer docs for further information.
Data Types and Usage
| Label | Data | Purpose | Good For | Access | Technology | Reference |
|---|---|---|---|---|---|---|
1 |
Event Journal |
Persistence of Akka state by persisting events for recovery/restart |
Internal only |
IPF Flows only |
MongoDB |
Should not be accessed outside of IPF Core software processing |
2 |
Processing Data |
Data belonging, or resulting from, a transaction flow, such as a payment, is egressed by IPF processing nodes throughout its lifecycle. |
Sending domain event data to other systems/DBs - for audit, warehousing, monitoring, MI, reporting, analytics |
Processing Data interface to other infrastructure / DBs |
Kafka & Java Impl |
|
3 |
ODS |
Perform activities like tracking & tracing of payments, exception handling (e.g. understand reason for failure) as well as overall monitoring of payment processes. |
Payments Business and Ops activities - query state of payment, domain event info, payment details |
ODS Ingestion & Inquiry API via UI (or client app) |
MongoDB |
|
4 |
Technical Metrics |
Exposed for the purpose of Prometheus and Grafana integration using sampling over a set interval |
Understanding/monitoring processing metric trends |
Metrics are exposed via a Prometheus HTTP server |
Prometheus/Grafana |
|
5 |
System Events |
Technical events- BAU and error |
Access to step by step processing within an IPF flow, technical level info |
Processing Data or System Events Exporter |
Kafka & Java Impl |
System Events & IPF System Event Exportador Spring Boot paquetes de inicio |
6 |
Application Logs |
Log level integration to banks monitoring tools - e.g. ELK / Dynatrace |
Log driven alerting & query |
Log integration |
Logs to ELK or Splunk |
More on Data Processing
You may also be interested in looking at the Data Processing & Persistence section of the site for more information on Data Identifiers, Processing Data, System Events, ODS and Data Models within IPF.