Core Token Lifecycle and Transaction Validation

GENERALSequenceintermediate
Core Token Lifecycle and Transaction Validation — GENERAL sequence diagram

About This Architecture

Core token lifecycle and transaction validation sequence diagram illustrating two-phase processing: Phase 1 captures token storage in the Frontend APP via PI Microservice with Audit Log tracking, while Phase 2 routes transactions through FEP, RFT, PI authentication, and NVBK core accounting. Data flows synchronously between Frontend APP, PI Microservice, Audit Log, FEP, RFT, and NVBK components, with internal processing steps and async responses clearly marked. This architecture demonstrates secure token management and multi-stage transaction validation essential for payment systems requiring compliance and auditability. Fork this diagram on Diagrams.so to customize component names, add additional validation stages, or adapt the sequence for your payment processing pipeline. The two-scenario approach provides a reusable template for systems separating token provisioning from transaction execution.

People also ask

How should token lifecycle and transaction validation be sequenced across microservices in a payment system?

This sequence diagram separates token provisioning (Phase 1: Frontend APP stores token via PI Microservice with Audit Log) from transaction execution (Phase 2: FEP routes to RFT, PI authenticates, NVBK processes accounting). The two-phase approach ensures tokens are securely managed before transaction routing, with synchronous calls between services and internal processing steps clearly marked for

sequence-diagrampayment-systemsmicroservicestransaction-validationtoken-managementarchitecture-pattern
Domain:
Software Architecture
Audience:
backend architects and payment systems engineers designing token lifecycle and transaction validation flows

Generated by Diagrams.so — AI architecture diagram generator with native Draw.io output. Fork this diagram, remix it, or download as .drawio, PNG, or SVG.

Generate your own sequence diagram →

About This Architecture

Core token lifecycle and transaction validation sequence diagram illustrating two-phase processing: Phase 1 captures token storage in the Frontend APP via PI Microservice with Audit Log tracking, while Phase 2 routes transactions through FEP, RFT, PI authentication, and NVBK core accounting. Data flows synchronously between Frontend APP, PI Microservice, Audit Log, FEP, RFT, and NVBK components, with internal processing steps and async responses clearly marked. This architecture demonstrates secure token management and multi-stage transaction validation essential for payment systems requiring compliance and auditability. Fork this diagram on Diagrams.so to customize component names, add additional validation stages, or adapt the sequence for your payment processing pipeline. The two-scenario approach provides a reusable template for systems separating token provisioning from transaction execution.

People also ask

How should token lifecycle and transaction validation be sequenced across microservices in a payment system?

This sequence diagram separates token provisioning (Phase 1: Frontend APP stores token via PI Microservice with Audit Log) from transaction execution (Phase 2: FEP routes to RFT, PI authenticates, NVBK processes accounting). The two-phase approach ensures tokens are securely managed before transaction routing, with synchronous calls between services and internal processing steps clearly marked for

Core Token Lifecycle and Transaction Validation

Autointermediatesequence-diagrampayment-systemsmicroservicestransaction-validationtoken-managementarchitecture-pattern
Domain: Software ArchitectureAudience: backend architects and payment systems engineers designing token lifecycle and transaction validation flows
3 views0 favoritesPublic

Created by

March 17, 2026

Updated

April 17, 2026 at 11:56 AM

Type

sequence

Need a custom architecture diagram?

Describe your architecture in plain English and get a production-ready Draw.io diagram in seconds. Works for AWS, Azure, GCP, Kubernetes, and more.

Generate with AI