Digital Lending Platform Modernization using Java microservices on Azure Cloud

1. Business Context

• Existing legacy loan management system (monolithic .NET + SQL Server on-prem).

• Modernization goal: Build cloud-native digital lending platform for retail and MSME loans with API-first, event-driven architecture.

• Coexistence required: Legacy remains system of record (SOR) during phased migration.

• Key drivers: Faster time-to-market, real-time decisioning, compliance with RBI/SEBI, cost optimization.

2. High-Level Architecture Overview

Architecture Style:

• Domain-driven design (DDD) → separate microservices for Loan Origination, KYC, Credit Scoring, Loan Decisioning, Disbursement, Notifications.

• Event-driven architecture → Azure Service Bus for async events (loan_created, kyc_completed).

• Hybrid integration → Legacy loan system via Linked Server/Data Factory APIs.

• Polyglot persistence → Azure SQL MI (transactional), Cosmos DB (real-time), Redis (session caching).

Azure Services Used

• API Gateway / Security: Azure API Management, Azure AD B2C, Azure AD (internal ops)

• Container Platform: Azure Kubernetes Service (AKS) for Java microservices

• Messaging / Events: Azure Service Bus (topic/queue)

• Data Layer:

  • Azure SQL MI (system of record for new platform)

  • Azure Cosmos DB (real-time cache, portfolio snapshot)

  • Azure Cache for Redis (ultra-fast session data)

• Integration:

  • Azure Data Factory (batch file integration with legacy & credit bureau)

  • ExpressRoute / VPN Gateway (private network connectivity with on-prem legacy systems)

• Observability: Azure Monitor, Application Insights, Log Analytics

• Secrets / Config: Azure Key Vault

• Compliance & Archival: Azure Blob Storage (WORM for audit logs)

3. Step-by-Step Architecture Flow

A. Loan Origination (Customer Journey)

1. Customer Initiates Application

   • Persona: Retail customer via mobile/web → Auth via Azure AD B2C

   • API routed via APIM → Loan Origination microservice (AKS)

2. Customer Data Capture

   • Data stored in Azure SQL MI (transactional)

   • Event loan_application_created published to Service Bus

3. KYC Check

   • KYC Microservice consumes event → invokes RTA/KYC API (hybrid) via APIM

   • If API unavailable, fallback to ADF file-based KYC process

   • KYC result → updates SQL MI + triggers kyc_completed event

4. Credit Scoring

   • Credit Microservice triggers Credit Bureau API call (Experian/CIBIL) via APIM

   • For offline bureaus, ADF fetches files (SFTP) → processed and persisted in SQL MI

5. Loan Evaluation & Decisioning

   • Loan Evaluation Microservice aggregates:

     • Applicant data (SQL MI)

     • Credit score (Credit service)

     • Legacy loan exposure (via Linked Server query to on-prem SQL)

   • Decision stored in SQL MI + event loan_decision_made

6. Approval & Agreement

   • Notification Service triggers e-sign (DocuSign API) via APIM

   • Signed loan agreement stored in Blob Storage (immutable for compliance)

7. Disbursement

   • Disbursement Microservice calls Payment API (bank core system)

   • Disbursement details updated in SQL MI + synced to legacy loan app (Linked Server)

B. Operations & Monitoring (Hybrid)

1. Ops Team Dashboard

   • Auth via Azure AD (MFA) → Admin Portal (React)

   • Aggregates data from SQL MI + Cosmos DB (real-time portfolio view)

2. Reconciliation with Legacy

   • Reconciliation Microservice compares SQL MI vs on-prem SQL (legacy) via Linked Server

   • Discrepancies flagged → routed to Ops dashboard

3. Regulatory Reporting

   • Compliance Service generates RBI/SEBI reports from SQL MI

   • ADF pushes reports via SFTP to regulators; archives in Blob Storage (WORM)

4. Monitoring & Alerting

   • Azure Monitor + App Insights track API latency, Service Bus health, ADF pipeline success/failure

   • Log Analytics centralizes audit logs for forensic analysis

4. Hybrid Connectivity Design

• ExpressRoute/VPN Gateway → Secure low-latency connection between Azure and on-prem datacenter

• SQL MI Linked Server → Dual write & read (cloud ↔ legacy) for coexistence during migration

• ADF Pipelines → Batch file ingestion/extraction (legacy loan system, credit bureau, regulators)

• Private Endpoints → For secure access to storage and databases (no public exposure)

5. Risk & Mitigation Plan

A. Business Risks

1. Data Inconsistency during Hybrid Phase

• Mitigation: Implement event sourcing + CDC; reconciliation jobs between SQL MI and legacy SQL; dual-write monitoring dashboards.

2. Downtime during Migration

• Mitigation: Phased rollout with blue-green deployments; feature toggles for rollback; DR strategy with geo-redundant SQL MI.

B. Technology Risks

1. Latency in Legacy Connectivity (ExpressRoute)

• Mitigation: Cache frequently accessed legacy data in Cosmos DB/Redis; async sync instead of real-time dependency where possible.

2. Service Bus Bottlenecks

• Mitigation: Scale-out Service Bus topics; partition events by domain; enable dead-letter queues with retry policies.

3. Credit Bureau API Failures

• Mitigation: Circuit breaker patterns; fallback to batch (ADF) integration; maintain stale-but-usable scores cache for critical flows.

C. Security & Compliance Risks

1. PII Exposure Across Hybrid Links

• Mitigation: Encrypt data in-transit (TLS) & at-rest (TDE); use Key Vault for secrets; private endpoints for data transfer.

2. Regulatory Non-Compliance (RBI, SEBI)

• Mitigation: Store immutable copies of loan agreements/reports in Blob Storage (WORM); audit logs in Log Analytics for 7+ years.

D. Operational Risks

1. Monitoring Gaps Across Cloud & On-Prem

• Mitigation: Unified observability with Azure Monitor + Log Analytics; configure hybrid log collection agents for legacy systems.

2. Skill Gap for Cloud-Native Ops

• Mitigation: Training program for DevOps teams; IaC with Bicep/Terraform to standardize deployments; runbooks for incident response.

"Our modernization approach separates concerns via domain-driven Java microservices on AKS, fronted by APIM for unified API exposure. Azure SQL MI serves as the new system of record, while Cosmos DB and Redis support real-time portfolio and low-latency dashboards. Hybrid connectivity to the legacy loan system is achieved via ExpressRoute and Linked Servers, enabling phased coexistence and dual-write reconciliation. Integration with credit bureaus and RTAs is handled via a combination of real-time APIs (APIM) and nightly file transfers (ADF). Compliance is ensured through immutable Blob Storage archives and centralized monitoring with Azure Monitor and Log Analytics. This design reduces time-to-market for new lending products while enabling progressive migration off legacy systems without disrupting ongoing operations."

1. High-Level Architecture Flow (Text)

Entry Points & Global Routing

• Angular Loan App (public subnet) hosted via Azure Front Door + CDN for global access.

• Traffic Manager for DNS-level active-active routing across two Azure regions.

API Gateway & Security Layer

• Requests enter Azure API Management (APIM) for routing, throttling, and security.

• Authentication:

  • Azure AD B2C for customers/investors.

  • Azure AD for internal operations/distributors (with MFA + Conditional Access).

Microservices Layer (Private Subnet on AKS)

• Istio Service Mesh for service-to-service mTLS, traffic splitting, observability.

• Key microservices (Java Spring Boot):

  • Loan Origination

  • KYC Verification

  • Credit Scoring

  • Loan Evaluation & Decisioning

  • Loan Disbursement

  • Notifications

  • Compliance Reporting

  • Reconciliation (Legacy vs Cloud)

Data Layer

• Azure SQL Managed Instance (SQL MI) – System of record for modern platform.

• Azure Cosmos DB – Real-time portfolio view (multi-region writes).

• Azure Cache for Redis – Session and hot data caching for low latency.

Eventing / Messaging

• Azure Service Bus (Topics/Queues) – Event-driven async communication:

  • Events: loan_created, kyc_completed, loan_disbursed, nav_updated.

Hybrid Integration (Legacy Loan App)

• ExpressRoute / VPN Gateway – Secure private connectivity to on-prem.

• Linked Server / CDC – Real-time data sync between SQL MI and legacy SQL.

• Azure Data Factory (ADF) – Batch integration (SFTP for legacy files, reconciliation).

Compliance & SEBI Integration

• Compliance Microservice – Generates SEBI/RBI reports.

• ADF → SFTP/REST – Automated secure report submission to SEBI.

• Blob Storage (Immutable/WORM) – Archival for 7+ years.

Monitoring & Observability

• Azure Monitor + Application Insights – End-to-end telemetry.

• Log Analytics – Centralized logs and compliance auditing.

• Key Vault – Secrets and API keys (SEBI, Credit Bureau, Payment Gateway).

Active-Active Deployment

• Deployed in two Azure regions (e.g., Central India + South India).

• Traffic Manager → DNS routing, Front Door → L7 routing.

• Cosmos DB multi-region writes, SQL MI failover groups, Service Bus geo-DR.

2. Sequence of Events (Text Timeline)

A. Customer (Investor) Loan Application

Step 1: Access & Authentication

1. User opens Angular Loan App (served via CDN + Front Door).

2. Login via Azure AD B2C → JWT token issued.

3. Request passes through APIM → routed to Loan Origination Microservice in AKS.

Step 2: Loan Application Creation

4. Loan Origination MS stores application in SQL MI.

5. Publishes loan_created event to Service Bus (Topic).

Step 3: KYC Verification

6. KYC MS subscribes → calls RTA real-time API via APIM.

7. If RTA API fails, fallback to ADF SFTP batch process (nightly).

8. KYC result stored in SQL MI, kyc_completed event emitted.

Step 4: Credit Scoring

9. Credit MS triggers Credit Bureau API call (real-time via APIM).

10. Score persisted to SQL MI.

Step 5: Loan Evaluation & Decision

11. Evaluation MS aggregates:

    • Loan details (SQL MI),

    • Credit score (SQL MI),

    • Legacy exposures (Linked Server to on-prem SQL).

12. Decision saved to SQL MI, loan_decision_made event emitted.

Step 6: Agreement & Disbursement

13. Notification MS sends e-sign link (DocuSign API) → stores signed doc in Blob WORM.

14. Disbursement MS calls Payment Gateway API (bank core) → confirms payment → updates SQL MI & legacy system.

Step 7: Portfolio Update

15. Portfolio MS updates Cosmos DB (real-time) → cached in Redis for instant dashboard updates.

B. Distributor Bulk Loan Flow

Step 1: Bulk Upload

1. Distributor portal authenticates via Azure AD (MFA) → APIM → Bulk Upload MS.

2. Bulk file parsed → each loan as event to Service Bus.

Step 2: Processing

3. Same flow as investor: validation → KYC → credit → evaluation → disbursement (parallelized).

Step 3: Acknowledgment

4. Status updates aggregated in Cosmos DB → exposed via APIM for distributor dashboard.

C. Operations & Compliance Flow

Step 1: Ops Dashboard

1. Ops portal authenticates via Azure AD.

2. Data fetched from SQL MI + Cosmos DB for monitoring KPIs, portfolio, reconciliations.

Step 2: Reconciliation

3. Reconciliation MS compares SQL MI (cloud) vs Legacy SQL (on-prem) via Linked Server.

4. Discrepancies flagged → events published to Service Bus → Ops dashboard alerts.

Step 3: Compliance Reporting

5. Compliance MS generates SEBI reports (CSV/XBRL).

6. ADF pipeline → securely pushes report to SEBI endpoint (SFTP/REST).

7. Copy archived to Blob WORM for 7-year retention.

Step 4: Monitoring & Alerting

8. Azure Monitor tracks API latency, Service Bus health, ADF pipeline SLAs.

9. Application Insights logs traces; Log Analytics consolidates for audits.

3. Hybrid Touchpoints Summary

• Legacy Loan App:

  • Real-time via Linked Server (SQL MI ↔ On-prem SQL).

  • Batch via ADF SFTP for reconciliation and historical migration.

• RTA/KYC & Credit Bureau:

  • Real-time via APIM-secured APIs.

  • Fallback batch (ADF) via secure file transfer.

• SEBI Compliance:

  • Automated export via ADF SFTP/REST.

  • Immutable archive via Blob WORM.

4. Active-Active Specific Sequence

1. DNS routing via Traffic Manager (Central India vs South India).

2. Front Door routes to nearest region; App Gateway WAF secures traffic.

3. AKS clusters run in both regions with Istio controlling intra-cluster routing.

4. Cosmos DB handles multi-region writes; SQL MI in failover group for DR.

5. Service Bus geo-disaster recovery ensures message durability across regions.

Here’s a comprehensive high-level solution architecture for a Digital Lending Platform Modernization using Java microservices on Azure Cloud with hybrid connectivity to an existing legacy loan application and compliance integration with SEBI. I’ve covered:

• Solutioning (end-to-end design)

• Integration points (cloud, legacy, SEBI)

• Persona-based flows (Investor, Distributor, Operations)

• Hybrid architecture components (network, data, messaging)

• Active-active deployment strategy

• Top 20 enterprise risks with mitigation plan

1. High-Level Solution Architecture (Java Microservices + Azure)

Core Components

Frontend Layer (Public Subnet)

• Angular Loan App (Web + Mobile)

  • Deployed in Azure App Service (or AKS Ingress) in Public Subnet

  • Fronted by Azure Front Door + Azure CDN for global routing & caching

  • Secured by WAF on Azure Application Gateway

API & Security Layer

• Azure API Management (APIM) for API gateway

• Azure AD B2C for customer authentication, Azure AD for internal Ops/Distributor

• Istio Service Mesh in AKS for service-to-service mTLS and traffic control

Microservices Layer (AKS in Private Subnet)

• Java Spring Boot microservices (Loan Origination, KYC, Credit Scoring, Evaluation, Disbursement, Notifications, Reporting)

• Each microservice uses sidecar Istio proxy for observability, security, and canary deployments

Data Layer

• Azure SQL Managed Instance – transactional data (loan applications, approvals, disbursements)

• Azure Cosmos DB – real-time portfolio, pre-aggregated dashboards

• Azure Cache for Redis – session caching, rate limiting, hot data (eligibility scores)

Messaging/Eventing

• Azure Service Bus – domain events (loan_created, kyc_completed, loan_disbursed) for async communication

• Event Grid (optional) – integration events (audit/log streaming, compliance triggers)

Hybrid Connectivity (Legacy Loan App)

• ExpressRoute/VPN Gateway – secure private network between on-prem & Azure

• Linked Server / Data Sync / ADF – SQL MI ↔ Legacy SQL for dual write & reconciliation

• ADF Pipelines – nightly batch file exchanges (KYC, NAV, legacy reports)

Compliance & SEBI Integration

• Automated Reporting Microservice generates regulatory reports (XBRL, CSV)

• ADF → SFTP over ExpressRoute for secure submission to SEBI endpoints

• Immutable storage in Azure Blob (WORM) for 7+ year retention

Active-Active & Global Traffic Management

• Azure Traffic Manager (DNS-based) + Azure Front Door (Layer 7) → geo-load balancing across regions

• AKS active-active in two Azure regions with Cosmos DB multi-region writes and SQL MI failover groups

Monitoring & Security

• Azure Monitor + Application Insights for telemetry

• Log Analytics for audit trails & anomaly detection

• Key Vault for secrets/API keys (RTA, Credit Bureau, SEBI)

• Network Security Groups (NSG) + Private Link for zero-trust network

2. Integration Points

Cloud Components

• Angular App (Public Subnet) → APIM → AKS Microservices (Private Subnet)

• Microservices → Azure SQL MI / Cosmos DB / Redis Cache

• Service Bus → Decoupled event communication between microservices

Hybrid (Legacy Loan Application)

• SQL MI ↔ On-Prem SQL (Linked Server, Data Sync, CDC) for dual writes

• ADF SFTP Pipelines for nightly reconciliation & bulk legacy migration files

• ExpressRoute/VPN Gateway ensures encrypted private connectivity

SEBI Compliance

• Reporting Microservice → Generates periodic compliance reports

• ADF → SFTP/REST Endpoint → Secure transfer to SEBI

• Blob WORM Storage → Immutable archival for audits

3. Persona-Based Flows (End-to-End)

Investor Flow (Loan Applicant)

1. Login & Application – Angular app (Front Door/CDN) → APIM → Loan Origination MS (AKS)

2. KYC Validation – KYC MS → RTA API via APIM (real-time) or ADF file (batch)

3. Credit Score Check – Credit MS → Bureau API via APIM

4. Loan Evaluation – Evaluation MS aggregates data (SQL MI, Cosmos, Legacy SQL via Linked Server)

5. Approval & Agreement – Notification MS → DocuSign API (e-sign) → store in Blob (WORM)

6. Disbursement – Disbursement MS → Payment Gateway (bank core) → update SQL MI & Legacy SQL

Distributor Flow

1. Bulk Loan Application Upload – Distributor portal (Front Door) → APIM → Bulk Upload MS (AKS)

2. Async Processing – Publish events to Service Bus → individual loan processing MS

3. Status Updates – Cosmos DB updates real-time → exposed via APIM endpoint for distributor dashboards

4. Hybrid Sync – Legacy SQL updated via Linked Server for reconciliation

Operations Flow

1. Admin Dashboard – Angular Admin Portal (Front Door) → APIM → Reporting MS (AKS)

2. Reconciliation – Compare SQL MI vs Legacy SQL via Linked Server

3. Compliance Reports – Reporting MS → ADF → SEBI endpoint via SFTP/REST

4. Monitoring – Azure Monitor + App Insights for full observability of microservices, pipelines, APIs

4. Active-Active Deployment Strategy

• Regions: Primary (Central India) + Secondary (South India)

• Traffic Management: Azure Traffic Manager (DNS) + Front Door (Layer 7 routing)

• Database: Cosmos DB multi-region writes; SQL MI failover groups with auto-failover

• Service Bus: Geo-disaster recovery enabled

• CI/CD: Azure DevOps Pipelines with blue-green/canary deployments using Istio

5. Top 20 Enterprise Risks & Mitigation

Business Risks

1. Data inconsistency during hybrid phase – Dual-write reconciliation, CDC jobs, automated alerts

2. Regulatory non-compliance (SEBI/RBI) – Immutable WORM storage, automated report exports, compliance dashboards

3. Delayed time-to-market – Phased rollout with MVP approach, agile sprints

4. Customer adoption resistance – Unified UX across legacy and new, omni-channel strategy

5. Legacy system dependency – Gradual decoupling, API façade pattern for legacy calls

Technology Risks

6. Latency in hybrid connectivity (ExpressRoute) – Cache legacy data in Cosmos DB, async sync

7. Single point of failure (AKS) – Active-active AKS clusters with Traffic Manager failover

8. Event bus overload (Service Bus) – Partitioning, dead-letter queues, auto-scaling

9. Database performance (SQL MI) – Elastic pools, read replicas for analytics

10. Versioning of APIs – Use APIM versioning & backward compatibility strategy

Security Risks

11. PII data leakage – TLS 1.3, encryption-at-rest, tokenization of sensitive fields

12. API abuse (DDoS) – APIM rate limiting, Azure Front Door WAF

13. Unauthorized internal access – RBAC, Managed Identities, Conditional Access policies

14. Secrets compromise – Centralized Key Vault with HSM-backed keys

Operational Risks

15. Monitoring blind spots – Unified dashboards via Monitor, App Insights, Log Analytics

16. Skill gaps (cloud & microservices) – Training, paired implementation, clear runbooks

17. Deployment errors – Automated CI/CD with canary releases & Istio traffic shifting

18. Legacy outages impacting cloud – Graceful degradation, stale cache fallback

19. High cost of cloud resources – Autoscaling, reserved instances, FinOps monitoring

20. Disaster recovery gaps – Active-active design, periodic DR drills, geo-redundant storage

Pls walk me through Architecture

"We modernized the digital lending platform by building Java microservices on AKS within private subnets, fronted by APIM and secured with Istio service mesh. The customer-facing Angular loan app is hosted in a public subnet behind Front Door, CDN, and App Gateway with WAF for global routing and protection. Data flows into Azure SQL MI for transactions, Cosmos DB for real-time portfolio dashboards, and Redis for session caching. Hybrid connectivity with the legacy loan application is achieved via ExpressRoute, Linked Servers, and ADF pipelines for both real-time queries and nightly batch processing. Compliance reporting to SEBI is automated via ADF pipelines exporting data to secure endpoints and archived in immutable Blob Storage. The platform runs active-active across two Azure regions, leveraging Traffic Manager and multi-region Cosmos DB for resiliency. We identified and mitigated top 20 enterprise risks, covering data consistency, regulatory compliance, latency, security, and operational gaps through caching, CDC, WORM storage, Istio, and robust monitoring with Azure Monitor and Log Analytics."

Here’s the high-level architecture flow and sequence of events (text version) for the Digital Lending Platform Modernization using Java Microservices on Azure Cloud with hybrid legacy integration and SEBI compliance. This is structured for interview explanation (2–3 min high-level narrative + 5–6 min detailed flow).

1. High-Level Architecture Flow (Text)

Entry Points & Global Routing

• Angular Loan App (public subnet) hosted via Azure Front Door + CDN for global access.

• Traffic Manager for DNS-level active-active routing across two Azure regions.

API Gateway & Security Layer

• Requests enter Azure API Management (APIM) for routing, throttling, and security.

• Authentication:

  • Azure AD B2C for customers/investors.

  • Azure AD for internal operations/distributors (with MFA + Conditional Access).

Microservices Layer (Private Subnet on AKS)

• Istio Service Mesh for service-to-service mTLS, traffic splitting, observability.

• Key microservices (Java Spring Boot):

  • Loan Origination

  • KYC Verification

  • Credit Scoring

  • Loan Evaluation & Decisioning

  • Loan Disbursement

  • Notifications

  • Compliance Reporting

  • Reconciliation (Legacy vs Cloud)

Data Layer

• Azure SQL Managed Instance (SQL MI) – System of record for modern platform.

• Azure Cosmos DB – Real-time portfolio view (multi-region writes).

• Azure Cache for Redis – Session and hot data caching for low latency.

Eventing / Messaging

• Azure Service Bus (Topics/Queues) – Event-driven async communication:

  • Events: loan_created, kyc_completed, loan_disbursed, nav_updated.

Hybrid Integration (Legacy Loan App)

• ExpressRoute / VPN Gateway – Secure private connectivity to on-prem.

• Linked Server / CDC – Real-time data sync between SQL MI and legacy SQL.

• Azure Data Factory (ADF) – Batch integration (SFTP for legacy files, reconciliation).

Compliance & SEBI Integration

• Compliance Microservice – Generates SEBI/RBI reports.

• ADF → SFTP/REST – Automated secure report submission to SEBI.

• Blob Storage (Immutable/WORM) – Archival for 7+ years.

Monitoring & Observability

• Azure Monitor + Application Insights – End-to-end telemetry.

• Log Analytics – Centralized logs and compliance auditing.

• Key Vault – Secrets and API keys (SEBI, Credit Bureau, Payment Gateway).

Active-Active Deployment

• Deployed in two Azure regions (e.g., Central India + South India).

• Traffic Manager → DNS routing, Front Door → L7 routing.

• Cosmos DB multi-region writes, SQL MI failover groups, Service Bus geo-DR.

2. Sequence of Events (Text Timeline)

A. Customer (Investor) Loan Application

Step 1: Access & Authentication

1. User opens Angular Loan App (served via CDN + Front Door).

2. Login via Azure AD B2C → JWT token issued.

3. Request passes through APIM → routed to Loan Origination Microservice in AKS.

Step 2: Loan Application Creation

4. Loan Origination MS stores application in SQL MI.

5. Publishes loan_created event to Service Bus (Topic).

Step 3: KYC Verification

6. KYC MS subscribes → calls RTA real-time API via APIM.

7. If RTA API fails, fallback to ADF SFTP batch process (nightly).

8. KYC result stored in SQL MI, kyc_completed event emitted.

Step 4: Credit Scoring

9. Credit MS triggers Credit Bureau API call (real-time via APIM).

10. Score persisted to SQL MI.

Step 5: Loan Evaluation & Decision

11. Evaluation MS aggregates:

    • Loan details (SQL MI),

    • Credit score (SQL MI),

    • Legacy exposures (Linked Server to on-prem SQL).

12. Decision saved to SQL MI, loan_decision_made event emitted.

Step 6: Agreement & Disbursement

13. Notification MS sends e-sign link (DocuSign API) → stores signed doc in Blob WORM.

14. Disbursement MS calls Payment Gateway API (bank core) → confirms payment → updates SQL MI & legacy system.

Step 7: Portfolio Update

15. Portfolio MS updates Cosmos DB (real-time) → cached in Redis for instant dashboard updates.

B. Distributor Bulk Loan Flow

Step 1: Bulk Upload

1. Distributor portal authenticates via Azure AD (MFA) → APIM → Bulk Upload MS.

2. Bulk file parsed → each loan as event to Service Bus.

Step 2: Processing

3. Same flow as investor: validation → KYC → credit → evaluation → disbursement (parallelized).

Step 3: Acknowledgment

4. Status updates aggregated in Cosmos DB → exposed via APIM for distributor dashboard.

C. Operations & Compliance Flow

Step 1: Ops Dashboard

1. Ops portal authenticates via Azure AD.

2. Data fetched from SQL MI + Cosmos DB for monitoring KPIs, portfolio, reconciliations.

Step 2: Reconciliation

3. Reconciliation MS compares SQL MI (cloud) vs Legacy SQL (on-prem) via Linked Server.

4. Discrepancies flagged → events published to Service Bus → Ops dashboard alerts.

Step 3: Compliance Reporting

5. Compliance MS generates SEBI reports (CSV/XBRL).

6. ADF pipeline → securely pushes report to SEBI endpoint (SFTP/REST).

7. Copy archived to Blob WORM for 7-year retention.

Step 4: Monitoring & Alerting

8. Azure Monitor tracks API latency, Service Bus health, ADF pipeline SLAs.

9. Application Insights logs traces; Log Analytics consolidates for audits.

3. Hybrid Touchpoints Summary

• Legacy Loan App:

  • Real-time via Linked Server (SQL MI ↔ On-prem SQL).

  • Batch via ADF SFTP for reconciliation and historical migration.

• RTA/KYC & Credit Bureau:

  • Real-time via APIM-secured APIs.

  • Fallback batch (ADF) via secure file transfer.

• SEBI Compliance:

  • Automated export via ADF SFTP/REST.

  • Immutable archive via Blob WORM.

4. Active-Active Specific Sequence

1. DNS routing via Traffic Manager (Central India vs South India).

2. Front Door routes to nearest region; App Gateway WAF secures traffic.

3. AKS clusters run in both regions with Istio controlling intra-cluster routing.

4. Cosmos DB handles multi-region writes; SQL MI in failover group for DR.

5. Service Bus geo-disaster recovery ensures message durability across regions.

Azure Solution Architect (Java Microservices) – Interview Q&A

1. Walk us through an architecture you designed using Azure for a digital lending platform.

Step-by-step Answer Structure:

1. Business Context

• Explain legacy pain points (monolithic loan app, batch processes, high latency).

• Objective: Modernize with cloud-native microservices on Azure, ensure hybrid connectivity for phased migration.

2. Architecture Style

• Microservices (Spring Boot Java) deployed on Azure Kubernetes Service (AKS).

• API-first design with Azure API Management (APIM) as gateway.

• Event-driven architecture via Azure Service Bus.

• Data split: Azure SQL MI (transactional) + Cosmos DB (real-time) + Redis (cache).

3. Network & Security

• VNET with public & private subnets:

  • Public subnet: Angular app behind Front Door + CDN + App Gateway WAF.

  • Private subnet: AKS, SQL MI, Cosmos DB via Private Endpoints.

• Istio service mesh for mTLS and observability inside AKS.

• Authentication: Azure AD B2C for customers, Azure AD (MFA) for internal Ops.

4. Hybrid Integration

• ExpressRoute for secure private connection to legacy loan system.

• Linked Servers / CDC for dual-write between SQL MI & on-prem SQL.

• ADF pipelines for batch sync with legacy & external bureaus (KYC, credit).

5. Compliance & Reporting

• Automated SEBI/RBI report generation via ADF → SFTP/REST endpoints.

• Immutable storage via Blob WORM for 7+ year retention.

6. Active-Active Deployment

• Multi-region AKS + Cosmos DB multi-write + SQL MI failover groups.

• Traffic Manager + Front Door for DNS + L7 routing between regions.

7. Monitoring & Ops

• Centralized telemetry with Azure Monitor + Application Insights + Log Analytics.

• Automated scaling, health checks, blue-green deployments (Istio).

Wrap-up (Impact):

• Reduced loan approval time from days to minutes.

• Enabled 99.99% uptime, regulatory compliance, and phased legacy migration with no downtime.

2. How would you design hybrid connectivity between Azure microservices and an on-prem legacy loan application?

Step-by-step Answer:

1. Connectivity Choice

• Use Azure ExpressRoute for private, low-latency, SLA-backed connection.

• Fall back to VPN Gateway during setup or DR.

2. Data Access Model

• Dual-write: New loan transactions in SQL MI → replicate to on-prem SQL via Linked Server / Data Sync.

• Read-only: For legacy exposure checks → secure queries from cloud to on-prem SQL via private endpoint.

3. Integration Methods

• Real-time APIs (REST) exposed via APIM → façade over legacy services.

• Batch Integration: ADF pipelines for nightly reconciliations and historical migrations.

4. Security

• Use Private Endpoints + NSGs for isolation.

• TLS 1.3 for all data in transit; TDE for at-rest.

• Secrets in Key Vault.

5. Monitoring

• Hybrid logs ingested into Log Analytics for unified observability.

3. Which Azure services would you choose for real-time vs batch processing in this architecture and why?

Real-time:

• Service Bus (Topics/Queues) – Event-driven async communication between microservices (loan_created, kyc_completed).

• Cosmos DB – Real-time denormalized views for dashboards (multi-region).

• Redis Cache – Sub-millisecond access for session & eligibility calculations.

Batch:

• Azure Data Factory (ADF) – For file-based exchanges (legacy, RTA, SEBI).

• Blob Storage – Staging area for batch data, WORM mode for compliance archives.

4. How do you secure APIs and data in this architecture?

Step-by-step security measures:

• Identity & Access Management

  • Customers: Azure AD B2C (JWT tokens).

  • Internal Ops: Azure AD + Conditional Access + MFA.

• API Security

  • APIM for OAuth2/JWT validation, IP filtering, throttling, versioning.

  • WAF on App Gateway for L7 protection (OWASP Top 10).

• Data Security

  • SQL MI: TDE, Always Encrypted for PII.

  • Cosmos DB: Private Link + RBAC + encryption at rest.

  • Redis: TLS & firewall rules.

• Secrets Management

  • Azure Key Vault (HSM-backed keys) for API keys, connection strings.

• Network Security

  • NSGs + Private Endpoints → Zero-trust segmentation.

5. How would you ensure active-active architecture and disaster recovery?

Step-by-step approach:

1. Regions: Deploy AKS, SQL MI, Cosmos DB in two regions (Central + South India).

2. Routing: Use Traffic Manager (DNS) + Front Door (Layer 7) for global load balancing.

3. Data Layer:

   • Cosmos DB → Multi-region writes.

   • SQL MI → Auto-failover groups for RPO < 5s, RTO < 30s.

4. Messaging: Service Bus geo-disaster recovery (paired namespace).

5. CI/CD: Multi-region deployment pipelines (Azure DevOps).

6. DR Drills: Regular failover tests & runbooks.

6. Explain how you would handle regulatory compliance (e.g., SEBI) in this architecture.

Key points:

• Generate periodic compliance reports (loan portfolios, NPAs) via Reporting MS.

• Export via ADF to SEBI endpoints (SFTP/REST) with TLS + IP whitelisting.

• Archive reports in Blob Storage (WORM) to prevent tampering.

• Log all compliance events in Log Analytics (auditable trail).

• Use Azure Policy & Blueprints for governance (tagging, RBAC, compliance posture).

7. What are the top risks in modernizing a lending platform and how do you mitigate them?

Examples (Pick 3-4 during interview):

• Data Consistency in Hybrid Mode → Dual-write with CDC, reconciliation jobs, alerts.

• Legacy Dependency → API façade pattern; gradual feature migration.

• Security Breaches → Zero-trust network, Key Vault, WAF, API throttling.

• Latency with Credit Bureaus/RTA → Cache responses (Redis), fallback to batch mode.

• Cost Overruns → Autoscale AKS, reserved instances for SQL/Cosmos, FinOps monitoring.

8. How do you optimize cost while ensuring performance and scalability?

• AKS Autoscaling (HPA/VPA) for microservices workloads.

• Cosmos DB – Autoscale RU/s, multi-region writes only where required.

• SQL MI – Use General Purpose tier unless high IOPS needed (Business Critical).

• Redis Cache – Use Premium only for session-critical flows.

• FinOps Practices – Azure Cost Analysis, Budgets, tagging per environment/team.

9. How do you manage CI/CD and deployments for microservices on AKS?

• Azure DevOps Pipelines → Build Spring Boot microservices → containerize with Docker → push to Azure Container Registry.

• Helm Charts / Bicep / Terraform → Deploy to AKS.

• Istio → Canary deployments, traffic shifting, progressive rollouts.

• Blue-Green Deployments → Minimize downtime during releases.

10. How would you troubleshoot latency in a microservices-based loan application on Azure?

• APIM Metrics → Check API latency, throttling, policy issues.

• App Insights Distributed Tracing → Identify slow microservices or dependencies.

• Service Bus Metrics → Queue depth, dead-letter messages.

• SQL Insights / Query Store → Long-running queries in SQL MI.

• Network Watcher → Diagnose ExpressRoute or Private Link issues.

• Cosmos DB Metrics → RU throttling or latency spikes.

  
  

1. Core & Advanced Questions with Step-by-Step Answers

Q1: Describe the architecture you built for a digital lending modernization project on Azure.

"We modernized a monolithic loan system by building domain-driven Java microservices on AKS in private subnets, exposed via APIM. The Angular loan app runs in a public subnet behind Front Door, CDN, and App Gateway WAF. Data flows to Azure SQL MI (transactional) and Cosmos DB (real-time dashboards), with Redis for hot caching. Hybrid connectivity to the legacy loan system is achieved via ExpressRoute and Linked Servers, with ADF handling nightly reconciliations. Compliance reports for SEBI are auto-generated and securely transmitted via ADF, archived in Blob WORM. The platform runs active-active across two regions with Traffic Manager, multi-region Cosmos DB, and SQL MI failover groups, monitored via Azure Monitor and Log Analytics."

Detailed Answer (5 min):

• Business Need: Legacy loan system was batch-driven, high latency, non-scalable. Modernization aimed for digital-first, API-driven, cloud-native platform with hybrid coexistence.

• Architecture:

  • Frontend: Angular app in public subnet → Front Door + CDN → App Gateway WAF → APIM.

  • Microservices: Java Spring Boot on AKS (private subnet) with Istio for service mesh.

  • Data: SQL MI (SOR), Cosmos DB (real-time), Redis (cache).

  • Integration: Service Bus for async events; ADF for batch (legacy, credit bureaus, RTA).

  • Hybrid Connectivity: ExpressRoute to on-prem; Linked Server/CDC for dual-write.

  • Compliance: SEBI reporting via ADF → SFTP; immutable storage in Blob WORM.

  • Resiliency: Active-active across two Azure regions (Traffic Manager, multi-region Cosmos).

• Outcome: Faster loan approvals (days → minutes), seamless coexistence, 99.99% uptime, compliant with RBI/SEBI.

Q2: How do you design hybrid connectivity between Azure microservices and legacy systems?

• Use ExpressRoute (preferred) or VPN for private network connectivity.

• Implement API façade over legacy services for real-time integration (via APIM).

• Use Linked Server/CDC for SQL MI ↔ Legacy SQL dual writes.

• Handle nightly reconciliations and bulk data via ADF pipelines + SFTP.

• Secure with Private Endpoints, NSGs, Key Vault, TLS 1.3.

• Monitor with Azure Monitor + Log Analytics (unified hybrid logs).

Q3: How do you ensure active-active and DR on Azure?

• Deploy AKS clusters in two regions, managed by Traffic Manager (DNS) + Front Door (L7).

• Use Cosmos DB multi-region writes and SQL MI failover groups.

• Service Bus geo-DR for eventing layer.

• CI/CD pipelines deploy to both regions; Istio handles canary deployments.

• Regular DR drills to test failover (RPO < 5s, RTO < 30s).

Q4: How do you secure APIs and data in this architecture?

• APIM for JWT/OAuth2 validation, throttling, IP restrictions.

• Azure AD B2C (customer) and Azure AD (internal) for identity.

• App Gateway WAF for OWASP Top 10 protection.

• SQL MI/Cosmos with encryption-at-rest (TDE) and in-transit (TLS).

• Key Vault for secrets, certificates, and managed identities.

Q5: How do you handle SEBI compliance and reporting?

• Generate regulatory reports (CSV/XBRL) via Reporting Microservice.

• Push reports via ADF SFTP/REST to SEBI secure endpoints.

• Archive immutable copies in Blob WORM (Write Once Read Many).

• Audit trails stored in Log Analytics (7+ years retention).

• Govern via Azure Policy + Blueprints for tagging, RBAC, compliance.

2. Text-based Architecture Diagram

[Users: Investor / Distributor / Ops]

|

v

+------------------+ Global Routing & Caching

| Azure Front Door| ---> Azure CDN

+------------------+

|

v

+------------------+

| Azure App Gateway|

| (WAF + SSL Term) |

+------------------+

|

v

+------------------+

| API Management |

| (OAuth/JWT) |

+------------------+

|

v

+---------------------------+ +---------------------------+

| AKS (Private Subnet) | | Legacy Loan App (On-Prem) |

| Microservices (Java + |<-------->| SQL via Linked Server |

| Istio, Service Bus Events)| Hybrid | Batch via ADF Pipelines |

+---------------------------+ (ER/VPN)+---------------------------+

| | |

v v v

Azure SQL MI Cosmos DB Redis Cache

(Transaction) (Realtime) (Session/Hot Data)

|

v

Azure Data Factory (Batch to SEBI, RTA)

|

v

SEBI Endpoint (SFTP/REST) + Blob WORM (Archive)

3. Quick Pitches

2-Min Elevator Pitch

"We designed a cloud-native digital lending platform on Azure using Java microservices on AKS, with APIM for API security and Front Door + CDN for global routing. Data is split across SQL MI for transactions, Cosmos DB for real-time views, and Redis for caching. We built hybrid connectivity to the legacy loan system via ExpressRoute and Linked Server, with ADF pipelines for nightly reconciliations and SEBI reporting. The solution is active-active across two regions with Traffic Manager and multi-region Cosmos DB, ensuring high availability and regulatory compliance."

5-Min Pitch (Detailed)

• Legacy pain point → monolithic, slow batch processing, compliance heavy.

• Solution → DDD microservices (Java), AKS with Istio, APIM, hybrid link to legacy.

• Data → SQL MI (SOR), Cosmos DB (dashboards), Redis (hot cache).

• Compliance → Automated SEBI/RBI reporting via ADF, WORM storage for audit.

• Resiliency → Active-active deployment (multi-region Cosmos + SQL MI failover).

• Impact → Faster loan approvals, seamless hybrid migration, compliance by design.

4. Top 20 Risks & Mitigation (Matrix)

Risk Category	Risk	Mitigation
Business	Data inconsistency (cloud vs legacy)	Dual-write with CDC, reconciliation dashboards
Business	Delayed go-live	Phased rollout, MVP first
Technology	Latency in hybrid connectivity	Cache legacy data, async sync
Technology	Event bus overload	Partitioning, dead-letter queues
Technology	SQL MI performance	Elastic pools, query tuning
Security	PII leakage	TDE, Always Encrypted, Key Vault
Security	API abuse (DDoS)	APIM rate limits, Front Door WAF
Security	Unauthorized access	RBAC, Conditional Access, Private Link
Compliance	SEBI non-compliance	Automated ADF exports, Blob WORM
Compliance	Audit failures	Centralized logging, Log Analytics
Operational	Monitoring blind spots	Unified Azure Monitor dashboards
Operational	Skill gaps in cloud team	Training, runbooks, paired ops
Operational	Deployment errors	Blue-green/canary deployments
Operational	Cost overruns	FinOps, autoscaling, reserved instances
DR/HA	Region failure	Traffic Manager failover, multi-region DB
DR/HA	Data loss during failover	Cosmos multi-write, SQL MI failover groups
Integration	Credit bureau/RTA API downtime	Circuit breaker, batch fallback (ADF)
Integration	Legacy outages	Graceful degradation, stale cache fallback
Performance	High traffic spikes	Autoscale AKS, Redis caching
Performance	API versioning issues	APIM versioning strategy

5. Cheat Sheet – Azure Services Mapping

• Frontend: Angular + Front Door + CDN + App Gateway WAF

• API Security: APIM, Azure AD B2C, Azure AD (MFA)

• Compute: AKS (Java microservices), Istio service mesh

• Data: SQL MI (SOR), Cosmos DB (real-time), Redis (cache)

• Messaging: Azure Service Bus (async events), Event Grid (integration)

• Hybrid: ExpressRoute, Linked Server, ADF pipelines

• Compliance: Blob WORM, ADF exports, Log Analytics for audits

• Observability: Azure Monitor, App Insights, Log Analytics

• HA/DR: Traffic Manager, Front Door, Cosmos multi-write, SQL MI failover groups

1. Investor Persona (Retail Loan Applicant)

Sequence: Loan Application → Disbursement → Notification

Investor → Angular App (Front Door/CDN) → APIM (JWT via Azure AD B2C)

| Submit Loan Application

v

Loan Origination MS (AKS) → Save to SQL MI → Emit `loan_created` (Service Bus)

KYC MS (Triggered)

→ Call RTA API via APIM

→ If RTA offline → Fallback ADF batch file

→ Update SQL MI → Emit `kyc_completed`

Credit Scoring MS (Triggered)

→ Call Credit Bureau API (APIM)

→ Save score in SQL MI → Emit `credit_score_ready`

Loan Evaluation MS

→ Fetch data from SQL MI + Legacy exposure (Linked Server)

→ Calculate eligibility → Update SQL MI → Emit `loan_decision_made`

Agreement MS

→ Generate PDF → Store in Blob WORM → DocuSign API (APIM)

→ Emit `agreement_signed`

Disbursement MS

→ Call Payment Gateway API

→ Update SQL MI + Legacy loan ledger

→ Emit `loan_disbursed`

Notification MS

→ Event Grid → SendGrid/Twilio (email/SMS to Investor)

Compliance MS

→ Generate SEBI report (ADF → SFTP)

→ Archive to Blob WORM

2. Distributor Persona (Bulk Loan Initiator)

Sequence: Bulk Loan Upload → KYC → Bulk Approval

Distributor → Angular App (Front Door/CDN) → APIM (Azure AD with MFA)

| Upload Bulk Loan File (CSV/XLS)

v

Bulk Processing MS (AKS)

→ Parse file → Validate → Split into loan records

→ Emit `bulk_loan_created` events (Service Bus)

KYC MS

→ For each record → Parallel RTA API calls (APIM)

→ Failed KYC → Mark for Ops review (Cosmos DB dashboard)

Credit Scoring MS

→ Batch credit score lookup (APIM)

→ Store in SQL MI → Emit `credit_score_ready_bulk`

Loan Evaluation MS

→ Aggregate results per record

→ Update SQL MI → Emit `bulk_loan_decision_made`

Agreement MS

→ Generate bulk agreements (PDF) → Archive in Blob WORM

→ Send for DocuSign signing

Disbursement MS

→ Initiate bulk payment to bank via API

→ Update SQL MI + Legacy system

Compliance MS

→ Generate bulk SEBI report (ADF)

→ Archive to Blob WORM

3. Operations Persona (Compliance & Monitoring)

Sequence: Real-time Monitoring + Reconciliation + SEBI Reporting

Ops User → Angular Ops Dashboard (Front Door/CDN) → APIM (Azure AD + MFA)

| View Loan Portfolio

v

Cosmos DB (Real-time cache of portfolio) ← Subscribed from Service Bus events

Reconciliation MS

→ Nightly job: Compare SQL MI vs Legacy DB

→ Publish discrepancies to Cosmos DB (Ops dashboard)

→ Alert via Event Grid → Email to Ops team

Compliance MS

→ Scheduled SEBI/RBI report generation

→ ADF pipeline → Export reports to SEBI endpoint (SFTP/REST)

→ Archive in Blob WORM (Immutable storage)

→ Log compliance event in Log Analytics (Audit trail)

4. Combined View Overlay

Combine the three personas:

• Investor: Retail, single loan → uses real-time flows (APIs, Service Bus).

• Distributor: Bulk loans → uses batch hybrid flows (bulk file → ADF → microservices).

• Ops: Monitoring & compliance → uses Cosmos DB real-time + batch reconciliation.

Combined Flow:

Front Door/CDN

|

v

App Gateway (WAF) → APIM

|

v

AKS Microservices (Loan Origination, KYC, Credit Scoring, Evaluation, Agreement, Disbursement)

|

+-- SQL MI (System of Record)

+-- Cosmos DB (Real-time dashboards for Ops)

+-- Redis (Session cache)

|

Hybrid Layer:

+-- ExpressRoute to Legacy Loan System

+-- Linked Server (SQL MI ↔ Legacy SQL)

+-- ADF (Batch sync, RTA fallback, SEBI exports)

|

Compliance Layer:

+-- Blob WORM (Immutable storage)

+-- SEBI Endpoint (SFTP/REST)

+-- Log Analytics (Audit trails)

5. Risk Matrix (Top 20 Risks for Interview Handout)

(Tailored for personas + hybrid flows)

#	Risk Category	Persona Impact	Risk Description	Mitigation
1	Business	Investor	Loan status mismatch (cloud vs legacy)	Dual-write + reconciliation dashboards
2	Business	Distributor	Bulk upload errors	Pre-validation in Bulk MS, retry + DLQ
3	Business	Ops	Delayed SEBI reporting	Automated ADF, schedule monitoring
4	Technology	All	ExpressRoute outage	VPN failover, cache fallback
5	Technology	Investor	Service Bus overload	Partitioning, auto-scale, DLQs
6	Technology	Distributor	SQL MI latency (bulk inserts)	Elastic pools, batching strategy
7	Technology	Ops	Cosmos DB RU throttling	Autoscale RUs, partition keys
8	Security	All	API DDoS attacks	APIM throttling + Front Door WAF
9	Security	Ops	Unauthorized ops dashboard access	Azure AD RBAC, MFA
10	Security	Investor	PII exposure in transit	TLS 1.3, Always Encrypted
11	Compliance	Ops	SEBI retention failure	Blob WORM, Policy enforcement
12	Compliance	All	Audit gaps	Centralized Log Analytics
13	Operational	Ops	Misconfigured batch jobs	Runbooks, automated alerts
14	Operational	Distributor	Failed bulk processing	Retry policies, DLQs
15	Operational	Investor	Delayed notifications	Event Grid retries, fallback SMS gateway
16	DR/HA	All	Region failure (primary down)	Traffic Manager failover, multi-region DB
17	DR/HA	All	Data loss on failover	Cosmos multi-write, SQL failover groups
18	Integration	Investor	RTA/KYC API downtime	Fallback to ADF batch processing
19	Integration	Distributor	Credit bureau latency	Cache bureau responses, async processing
20	Performance	Ops	Dashboard staleness	Cosmos DB TTL-based refresh, streaming events

Mock Q&A Drill 1 – RTA Down Scenario

Question (CTO Style):

"What if the RTA API is down during peak KYC processing for investor and distributor flows? How does your architecture handle this, and what do you tell business stakeholders?"

Ideal Answer (Structured in 4 Steps)

1. Acknowledge and Reframe"RTA downtime is a critical single point of failure for KYC; we’ve designed for graceful degradation and fallback processing."

2. Solution Architecture Response

• Primary Path: KYC Microservice calls RTA API (APIM secured) for real-time validation.

• Fallback Path: If RTA is unreachable (monitored via APIM health probes + Circuit Breaker pattern):

  • Route KYC requests to Azure Service Bus DLQ (tagged for batch).

  • Trigger ADF pipeline to fetch/process KYC via file-based batch integration when RTA resumes.

  • Notify Ops dashboard via Event Grid for visibility.

3. User Impact

• Investor flow: Application submitted, marked as “Pending KYC – will auto-complete.”

• Distributor flow: Bulk file partially processed; failed records retried via batch.

4. Communication / SLA

• Communicate to business: “Real-time KYC temporarily degraded, fallback batch in 2 hours; no data loss.”

• Ensure audit: Event logged in Log Analytics + alert sent to Ops.

Refinement Tip (For Interview)

End with resilience principle: “We ensure no single external dependency can halt loan processing — every integration has circuit breakers + async fallbacks.”

Mock Q&A Drill 2 – Reconciling Bulk vs Retail Loans

Question (CTO Style):

"How do you reconcile data between bulk distributor loans and individual retail loans across cloud and legacy systems?"

Ideal Answer

1. Context"Retail flows are API-first; bulk flows are file/batch. Legacy also runs parallel until migration completes — so reconciliation is mandatory to ensure data integrity."

2. Approach

• Use Reconciliation Microservice (AKS) scheduled nightly:

  • Compare SQL MI (cloud SoR) vs Legacy SQL via Linked Server/ADF extract.

  • Validate loan IDs, amounts, status, disbursement dates.

  • Detect mismatches (e.g., missing bulk disbursement entries).

3. Handling Bulk vs Retail

• Retail loans: Real-time sync via Service Bus events → Legacy dual-write.

• Bulk loans: File ingestion + delayed updates → Tag records as “bulk” in SQL MI → reconciliation logic accommodates delayed status updates.

4. Ops Visibility

• Publish reconciliation results to Cosmos DB (Ops dashboard) → flag mismatches with severity.

• Trigger Event Grid alerts for high-impact mismatches (e.g., disbursement without approval).

5. Outcome

• Ensures financial correctness, prevents regulatory penalties, and supports SEBI reporting accuracy.

Mock Q&A Drill 3 – Legacy Latency Challenge

Question:

"If legacy loan system latency increases (e.g., 2s per API call), how do you prevent it from degrading overall platform performance?"

Answer (Crisp):

• Introduce caching layer (Redis) for read-heavy data (loan status, customer profile).

• Use async write-behind pattern for updates to legacy (write to Service Bus → process via worker).

• Apply circuit breaker + timeout in API calls to prevent cascading failures.

• For critical paths (approval/disbursement), provide “eventual consistency” banner to Ops.

Mock Q&A Drill 4 – Active-Active DR Scenario

Question:

"How do you ensure loan approvals continue if an entire Azure region fails during month-end bulk disbursement?"

Answer:

• Active-active setup: AKS clusters + SQL MI failover groups + multi-region Cosmos DB across two regions.

• Traffic Manager for DNS failover, Front Door for global routing.

• Bulk jobs (ADF) designed with resume checkpoints → can restart in secondary region without data duplication.

• SEBI reporting unaffected — data archived in Blob WORM (geo-redundant).

Mock Q&A Drill 5 – Compliance Escalation

Question:

"SEBI has mandated 1-hour reporting turnaround. How do you meet this SLA?"

Answer:

• Compliance MS generates real-time deltas → triggers ADF pipeline on event rather than nightly batch.

• Use Blob WORM for immediate archive (compliance retention).

• Leverage Event Grid to notify Ops of submission status → provide SLA dashboard in Cosmos DB.

• Redundant pipeline ensures reporting continues even if one path fails (active-active).