Loan Broker Showcases

Loan Broker showcase

The Loan Broker showcase is a basic loan broker implementation following the structure presented by Gregor Hohpe in his book - Enterprise Integration Patterns.

Logical architecture of the loan broker

The Loan Broker showcase demonstrates how to build distributed systems with NServiceBus and the Particular Service Platform. It's available in two flavors, one for AWS and one for Azure, each using equivalent cloud services for messaging, persistence, and hosting.

The AWS Loan Broker showcase uses AWS SQS and SNS for message queueing and event publishing, DynamoDB for saga data persistence, and Lambda functions to host some of the loan broker components.

The Azure Loan Broker showcase uses Azure Service Bus for message queueing and event publishing, SQL Server for saga data persistence, and Azure Functions to host some of the loan broker components.

flowchart LR Client[["Client endpoint Sends the request"]] FindBestLoan(["FindBestLoan Command"]) CreditBureau["Credit bureau API Serverless, HTTP call"] SagaStore[("Saga persistence SQL Server, DynamoDB, etc.")] subgraph Broker["LoanBrokerSaga manages the loan request"] direction TB Enrich["Enrichment handler Adds credit score"] Decide["LoanBrokerSaga Decides which banks to ask"] Enrich --> Decide end QuoteRequested(["QuoteRequested Event, published by saga"]) BankA[["Bank A endpoint Subscriber queue"]] BankB[["Bank B endpoint Subscriber queue"]] BankC[["Bank C endpoint Subscriber queue"]] HandlerA["QuoteHandler Outbox-backed"] HandlerB["QuoteHandler Outbox-backed"] HandlerC["QuoteHandler Outbox-backed"] LoanQuoteSubmitted(["LoanQuoteSubmitted Command, by SagaId"]) LoanQuotesReady(["LoanQuotesReady Event, saga completes"]) ClientReceives[["Client endpoint Receives the result"]] Notifications[["Notifications endpoint Sends email"]] Client --> FindBestLoan --> Enrich CreditBureau <--> Enrich SagaStore <--> Decide Decide --> QuoteRequested QuoteRequested --> BankA --> HandlerA QuoteRequested --> BankB --> HandlerB QuoteRequested --> BankC --> HandlerC HandlerA --> LoanQuoteSubmitted HandlerB --> LoanQuoteSubmitted HandlerC --> LoanQuoteSubmitted LoanQuoteSubmitted --> Decide Decide --> LoanQuotesReady LoanQuotesReady --> ClientReceives LoanQuotesReady --> Notifications classDef endpoint fill:#64748b,stroke:#334155,color:#fff classDef command fill:#d97706,stroke:#92400e,color:#fff classDef event fill:#0d9488,stroke:#115e59,color:#fff classDef external fill:#dc6e4f,stroke:#9a3412,color:#fff classDef broker fill:#6d28d9,stroke:#4c1d95,color:#fff class Client,ClientReceives,Notifications,BankA,BankB,BankC,HandlerA,HandlerB,HandlerC,Enrich,Decide endpoint class FindBestLoan,LoanQuoteSubmitted command class QuoteRequested,LoanQuotesReady event class CreditBureau,SagaStore external style Broker fill:#f3e8ff,stroke:#6d28d9,stroke-width:2px

The showcase is composed of:

A client application, sending loan requests.
A credit bureau provides the customers' credit scores.
A loan broker service that receives loan requests enriches them with credit scores and orchestrates communication with downstream banks.
Three bank adapters, acting like Anti-Corruption layers (ACL), simulate communication with downstream banks offering loans.
An email sender simulating email communication with customers.

The example also ships the following monitoring services:

The Particular platform to monitor endpoints, capture and visualize audited messages, and manage failed messages.
A Prometheus instance to collect, store, and query raw metrics data.
A Grafana instance with three different metrics dashboards using Prometheus as the data source.
A Jaeger instance to visualize OpenTelemetry traces.
AWS Distro for OpenTelemetry collector (ADOT) to collect and export metrics and traces to various destinations.

Loan Broker showcase

Repositories

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