Microservices

✅ Section 1: Technical Deep Dive

1. What is microservices architecture? How is it different from monolithic architecture?

2. What are the key benefits and challenges of using microservices?

3. How do microservices communicate with each other? What are the pros and cons of synchronous vs asynchronous communication?

4. What is service discovery and how is it implemented?

5. How do you handle data consistency in microservices?

6. Explain the role of API Gateway. What are its common responsibilities?

7. How do you handle versioning of APIs in a microservices ecosystem?

8. How do you secure communication between microservices?

9. What is the role of service mesh in microservices?

10. What are sidecars, and how do they help in microservices deployments?

✅ Section 2: Architecture & Design Questions

1. How would you design a microservices-based architecture for a digital banking platform?

2. How would you decompose a monolithic application into microservices?

3. What design patterns do you commonly use in microservices (e.g., Circuit Breaker, Saga, CQRS)?

4. How do you handle distributed transactions in microservices?

5. How do you ensure observability (monitoring, tracing, logging) across microservices?

6. How do you implement DevOps practices (CI/CD) in a microservices ecosystem?

7. What’s your approach to handling failures in microservices (e.g., retries, fallbacks)?

8. How do you handle schema evolution in a microservices-based system?

✅ Section 3: Scenario-Based Questions

1. Your microservices are failing intermittently in production. How would you investigate and resolve this?

2. A particular service is receiving high traffic and is becoming a bottleneck. What steps would you take?

3. You need to implement a fraud detection service that needs to talk to 4 different services. How would you architect this to ensure scalability and resilience?

4. Your team is planning to add GenAI-based personalization in a microservices setup. How would you integrate it?

5. How would you migrate a legacy credit scoring module to a microservices model in a live banking system with minimal downtime?

✅ Section 4: Hands-On or Whiteboard Exercise (if applicable)

Design Prompt:

"Design a microservices-based architecture for a loan origination system. Include services, communication mechanisms, data stores, and DevOps practices."

🏗️ 1. Core Microservices

Service	Description
Customer Service	Handles KYC, customer info, integration with external ID validation
Loan Application Service	Manages loan requests, status, validations
Credit Evaluation Service	Calculates creditworthiness from credit bureau APIs
Risk Assessment Service	Applies business rules to calculate loan eligibility
Document Management Service	Upload, validate, and store documents
Notification Service	Sends SMS, email, in-app notifications
Workflow Orchestration Service	Orchestrates the loan lifecycle across services
Audit/Logging Service	Captures all events for compliance/audit
Analytics Service	Generates insights and scoring for underwriting
User/Identity Service	Handles Azure AD integration, JWT token issuing and validation

🔗 2. Communication Mechanisms

Use Case	Mechanism
Synchronous service calls	RESTful APIs via Istio-managed service mesh
Asynchronous events	Apache Kafka (loan-created, credit-check-complete, etc.)
External APIs (e.g., credit bureau, Aadhaar)	REST with API Gateway & security
API Gateway	Azure API Management (APIM) to expose APIs securely
Service discovery, load balancing	Istio + AKS

🛢️ 3. Data Stores per Service

Service	Data Store
Customer	Azure SQL / PostgreSQL
Loan Application	Azure SQL
Credit Evaluation	NoSQL (Cosmos DB or MongoDB)
Document	Azure Blob Storage
Notification	Azure Table Storage or Cosmos DB
Audit	Azure Data Lake or Cosmos DB
Analytics	Azure Synapse / Azure Data Explorer

🔐 4. Security & Access Control

• Azure AD for user/service authentication

• OAuth2 + JWT for access control

• Istio mTLS for service-to-service encryption

• Azure Key Vault for storing secrets/certificates

• Role-based access via API Gateway & microservices

🚀 5. DevOps & CI/CD Practices (Azure DevOps)

Stage	Tool/Action
Code repo	Azure Repos or GitHub
CI Pipeline	Azure DevOps: build, run tests, scan with SonarQube
Docker	Containerize each service; push to Azure Container Registry
Helm	Helm charts for each service
CD Pipeline	Deploy to AKS via Azure DevOps with release gates
Monitoring	Azure Monitor + Application Insights + Grafana
Logging	Fluent Bit → Azure Log Analytics
Canary/Blue-Green	Istio + Azure DevOps deployment strategy
Infra-as-Code	Terraform or Bicep for AKS, VPC, Key Vault, etc.

🌐 6. Workflow Diagram (Loan Flow)

1. Customer submits loan via Loan Application Service

2. Triggers:

   • Credit Evaluation (external API)

   • Risk Assessment

3. Document Upload and validation

4. Workflow Service coordinates progress → final approval

5. Sends real-time notifications to the customer

6. Data logged to Audit Service

7. Results sent to Analytics for performance tracking

🧠 7. Bonus Considerations

• API-First Design using OpenAPI + contract testing

• Circuit breakers, retries, and rate-limiting via Istio

• Chaos engineering and fault injection in AKS for resilience

• Horizontal pod autoscaling and node pool isolation by workload type

✅ Summary Diagram (Conceptual Layout)

yaml

[Client / Portal / Mobile App]

|

[API Gateway]

|

---------------------

| | | |

Customer Loan Credit Workflow

Service App Eval Service

| | | |

Kafka <---+------+--------+----> Notification

|

Risk Service

|

Document Service

|

Azure Blob Storage

|

Audit + Analytics

🧠 Hands-On / Whiteboard Exercise: Design & Deploy a Secure Customer Onboarding Microservice

🎯 Objective:

Design and explain the complete flow of a Customer Onboarding microservice application using:

• Microservices (Spring Boot)

• Azure Kubernetes Service (AKS)

• Istio Service Mesh

• Azure Container Registry (ACR)

• Azure AD for security

• Azure DevOps CI/CD

• Observability (Azure Monitor)

• API Management & Kafka

🔧 Step-by-Step Task Breakdown

✅ 1. Whiteboard the Architecture

Ask the candidate to draw or explain:

• Microservice-to-microservice communication

• Service Mesh (Istio) integration

• API Gateway/API Management routing

• External consumer access via ingress

• Azure AD Authentication & Authorization flow

• Kafka for async onboarding events

• AKS node group setup

• Where Azure DevOps pipeline fits in

Deliverable: A diagram covering all key components (services, mesh, security, data, CI/CD, observability)

🔐 2. Security Considerations

• How would you secure service-to-service traffic?

  • (Expected: Istio mTLS, Azure AD integration)

• Where do you place secrets? (Expected: Azure Key Vault)

• How do you restrict network access? (Expected: NSGs/VPCs, Istio ingress policies)

⚙️ 3. DevOps & CI/CD Integration

Ask how the deployment happens:

• Explain Helm chart structure

• Pipeline stages: build → test → containerize → push → deploy

• How to integrate OpenAPI contract testing in pipeline

• Rollback strategy if a deployment fails

📊 4. Observability Setup

Ask how to:

• Monitor health of microservices

• Set up alerts

• Visualize traffic via Istio dashboard

• Integrate logs to Azure Monitor / Log Analytics

🧪 5. Optional Hands-On (Bonus Points)

If in a hands-on setup, ask the candidate to:

• Create a simple Spring Boot API from an OpenAPI contract (openapi.yaml)

• Containerize it using Docker

• Deploy it to AKS using Helm

• Setup an Azure DevOps YAML pipeline to deploy on commit

💬 Key Evaluation Criteria

Area	What to Look For
Architecture	Clear separation of concerns, secure flow
Azure Cloud Knowledge	Uses right services for compute, networking, secrets
CI/CD & DevOps	Pipeline breakdown, rollback, secrets
Security	Azure AD integration, Istio mTLS
Observability	Proper monitoring and alerting
Communication	Clarity in explaining design decisions

macrofrontend + microservices architecture for digital wallet with springboot microservices + Azure cloud

ChatGPT said:

Here’s a detailed Macrofrontend + Microservices Architecture for a Digital Wallet Platform using Spring Boot microservices and Azure Cloud.

🌐 1. High-Level Architecture Overview

A. Macrofrontend (Web UI Layer)

• Built using Micro Frontend Architecture

• Frameworks: React + Module Federation (Webpack 5) or Single SPA

• Each frontend team owns a domain-specific UI (e.g., Wallet, Payments, KYC, Offers)

• Shared components: Authentication, Navbar, Footer

B. Microservices (Backend)

• Each microservice is built using Spring Boot

• REST APIs secured using OAuth2 / Azure AD

• Services include:

  • User Management Service

  • KYC Service

  • Wallet Service

  • Transaction Service

  • Rewards & Offers Service

  • Notification Service

  • Payment Gateway Integration Service

  • Ledger/Accounting Service

  • Audit & Logging Service

☁️ 2. Azure Cloud Components

Component	Azure Service
API Gateway	Azure API Management
Service Discovery	Azure Kubernetes Service (AKS) + Istio
CI/CD	Azure DevOps Pipeline
Database	Azure SQL, Cosmos DB, PostgreSQL
Object Storage	Azure Blob Storage
Identity & Access Management	Azure Active Directory (Azure AD B2C)
Monitoring & Logging	Azure Monitor + Log Analytics + App Insights
Messaging	Azure Event Hubs / Azure Service Bus
Secret Management	Azure Key Vault
Load Balancing	Azure Traffic Manager + Azure Application Gateway
Container Registry	Azure Container Registry

🧱 3. Logical Microservices Architecture

sql

CopyEdit

+-------------------------+ +----------------------------+ |  Macro Frontend (SPA) | -> | Azure API Management | | React + Webpack |    +----------------------------+ | (via BFF per domain) |             | +-------------------------+ | ↓ ↓ +----------------------+ +--------------------------+ |   BFF for Wallet UI |      | BFF for KYC UI | | Spring Boot (optional)|      | Spring Boot (optional) | +----------------------+ +--------------------------+ ↓ ↓ +----------------------------- Kubernetes (AKS) ----------------------------+ |                                                                          | |  +------------------+ +-------------------+ +--------------------+ | |  | Wallet Service |    | KYC Service |   | Payment Service |  | |  +------------------+ +-------------------+ +--------------------+ | |  | Ledger Service |    | Notification Svc |   | Rewards Service |  | |  +------------------+ +-------------------+ +--------------------+ | |      ... Microservices communicate via REST or Event Bus (Kafka) | +--------------------------------------------------------------------------+

🔐 4. Security Architecture

• Frontend Auth: Azure AD B2C for login / token issuance

• API Gateway: Validates JWTs or OAuth2 tokens

• Service-to-Service Auth: Mutual TLS via Istio + Azure Managed Identities

• Secrets: Stored in Azure Key Vault

🔁 5. CI/CD & DevOps

• Source Control: Azure Repos / GitHub

• CI/CD: Azure DevOps Pipelines

  • Build → Test → Push to Azure Container Registry → Deploy to AKS

• Helm charts or Kustomize for AKS deployments

• Canary / Blue-Green deployments using Istio

📊 6. Observability

• Logs & Metrics: Azure Monitor + Log Analytics

• Tracing: OpenTelemetry + Azure Monitor

• Dashboards: Custom dashboards for latency, success rate, usage metrics

📦 7. Micro Frontend Modules

Module	Responsibility
Wallet	Balance, top-up, transfer
KYC	Upload documents, track status
Transactions	View history, dispute a charge
Offers & Rewards	Loyalty points, cashback
Notifications	In-app and push notifications
Settings & Profile	User preferences, contact info, security

🔄 8. Event-Driven Use Cases

• KYC Completed → triggers → Wallet Activation

• Transaction Failed → triggers → Notification + Retry Queue

• Top-up Success → triggers → Ledger Update + Reward Calculation

✅ Section 1: Technical Deep Dive

1. What is microservices architecture? How is it different from monolithic architecture?

Answer:Microservices architecture is an approach where an application is composed of small, loosely coupled, independently deployable services. Each service focuses on a specific business capability and communicates via lightweight protocols (typically HTTP or messaging queues).

Differences:

Monolith	Microservices
Single codebase	Multiple independent services
Tight coupling	Loose coupling
Shared DB	Independent DBs
Hard to scale selectively	Scalable per service
Single point of failure	Resilient and fault-tolerant

2. What are the key benefits and challenges of using microservices?

Benefits:

• Independent deployment

• Technology diversity

• Scalability per service

• Improved fault isolation

• Aligned with Agile/DevOps

Challenges:

• Complexity in distributed systems

• Data consistency

• Inter-service communication

• DevOps sophistication needed

• Testing and monitoring become harder

3. How do microservices communicate with each other?

Answer:

• Synchronous (HTTP/REST, gRPC): Easy to implement, but tightly coupled and prone to cascading failures.

• Asynchronous (Kafka, RabbitMQ): Decoupled, more scalable, resilient, but harder to debug and ensure delivery guarantees.

4. What is service discovery and how is it implemented?

Answer: Service discovery helps microservices locate each other dynamically. Implemented using:

• Client-side discovery (e.g., Netflix Eureka with Ribbon)

• Server-side discovery (e.g., AWS ALB, Consul)

• Service mesh (e.g., Istio + Envoy)

5. How do you handle data consistency in microservices?

Answer:

• Prefer eventual consistency

• Use Saga pattern for long-running transactions (choreography or orchestration)

• Event-driven architecture to propagate state changes

• Avoid distributed transactions if possible

6. Explain the role of API Gateway.

Answer: Acts as a single entry point for client requests. Responsibilities:

• Request routing

• Authentication/Authorization

• Rate limiting

• Logging/Monitoring

• Load balancing

Examples: Kong, NGINX, AWS API Gateway, Spring Cloud Gateway

7. How do you handle API versioning?

Answer:

• URI-based (/api/v1/resource)

• Header-based (Accept: application/vnd.api.v1+json)

• Query param-based (?version=1) Ensure backward compatibility and deprecate carefully.

8. How do you secure communication between microservices?

Answer:

• Use mTLS for service-to-service encryption

• Token-based auth (e.g., JWT, OAuth2)

• API Gateway for auth and rate-limiting

• Use service mesh (e.g., Istio) for consistent policy enforcement

9. What is the role of a service mesh?

Answer: A service mesh handles service-to-service communication transparently. It provides:

• Traffic routing

• Observability

• Security (mTLS)

• Retry, timeout, circuit breaking

Examples: Istio, Linkerd, Consul Connect

10. What are sidecars, and how do they help?

Answer: Sidecars are helper containers deployed alongside application containers (in the same pod) in Kubernetes. They provide:

• Logging

• Service discovery

• Proxies (e.g., Envoy)

• Security (auth, TLS)

✅ Section 2: Architecture & Design Questions

1. Design a microservices-based architecture for a digital banking platform.

Answer:

• Services: Accounts, Payments, Loans, Customer, Auth, Notification

• Communication: REST + Kafka (event-driven)

• DB per service (PostgreSQL, MongoDB)

• API Gateway for aggregation

• CI/CD with Jenkins + Docker + Kubernetes

• Observability: Prometheus, Grafana, ELK

• Security: OAuth2, mTLS, rate limiting

2. How to decompose a monolith into microservices?

Answer:

• Identify business domains → create bounded contexts

• Use Domain-Driven Design (DDD)

• Start with non-critical modules

• Use strangler pattern to gradually replace parts

• Ensure contracts via APIs

3. Design patterns used in microservices?

Answer:

• API Gateway

• Circuit Breaker (e.g., Resilience4j)

• Saga pattern

• CQRS (Command Query Responsibility Segregation)

• Service Registry

• Sidecar & Ambassador

4. How do you handle distributed transactions?

Answer: Avoid 2PC. Use:

• Saga pattern – local transactions + compensating actions

• Eventual consistency via events

• Orchestrator pattern if coordination needed

5. How to ensure observability?

Answer:

• Logging: Centralized via ELK or Fluentd

• Metrics: Prometheus + Grafana

• Tracing: OpenTelemetry, Jaeger, Zipkin

• Dashboards + Alerts: Grafana + Alertmanager

6. CI/CD in microservices ecosystem?

Answer:

• CI: Code → Build → Test → Package (Jenkins, GitHub Actions)

• CD: Deploy to staging/prod (ArgoCD, Spinnaker)

• Containerize each service (Docker)

• Use Kubernetes with Helm charts or Kustomize

7. Handling failures in microservices?

Answer:

• Retries with exponential backoff

• Circuit breaker

• Fallback logic

• Timeouts

• Bulkheads

• Alerting and dashboards

8. How to handle schema evolution?

Answer:

• Use backward/forward-compatible schemas

• Evolve APIs carefully (add new fields, avoid removing required ones)

• For events: use Protobuf/Avro with schema registry

• Implement consumer-first contracts (Consumer-Driven Contracts)

✅ Section 3: Scenario-Based Questions

1. Intermittent service failure in prod?

Approach:

• Check dashboards/logs/alerts

• Use distributed tracing to find root cause

• Check dependencies and external services

• Rollback recent deployments if needed

• Add circuit breaker/fallback if pattern detected

2. Service bottleneck due to high traffic?

Approach:

• Scale horizontally (add pods/instances)

• Optimize code/db queries

• Add caching (e.g., Redis)

• Use rate limiting or throttle non-critical requests

• Offload to async processing (e.g., queue)

3. Fraud detection service needing 4 service integrations?

Answer:

• Use async pub-sub model via Kafka for resilience

• Retry + circuit breakers for external calls

• Aggregate responses if needed using Saga

• Ensure observability

• Cache frequent responses (if possible)

4. Integrate GenAI-based personalization in microservices?

Answer:

• Create a separate AI inference microservice

• Use REST/gRPC to invoke GenAI APIs

• Use RAG (Retrieval Augmented Generation) for contextual responses

• Add monitoring + auto ML model retraining

• Ensure latency control (use async if needed)

5. Migrate legacy credit scoring module to microservices?

Answer:

• Use strangler pattern

• Create new credit scoring microservice in parallel

• Route a subset of traffic for A/B testing

• Ensure data sync

• Gradually increase usage, then retire monolith part

can u pls come up with banking use case using microservices architecture , kubernetes and service mesh istio ,with all architecture flow , pls take care of security and integration with azure AD and deployed this microservices to Azure cloud by leveraging Azure cloud services like Azure SQL, Traffic manager, VPC , AKS with service mesh istio and kafka,azure monitoring, api management, azure monitoring, azure container and azure devops pipeline

Absolutely! Here's a detailed banking use case architecture using microservices, Kubernetes (AKS), Istio service mesh, integrated with Azure AD, and fully deployed on Azure Cloud using native services. The use case chosen is Digital Loan Origination & Management System.

🏦 Use Case: Digital Loan Origination & Management

✳️ Key Capabilities:

• Customer onboarding & KYC

• Loan application and credit scoring

• Risk and fraud detection

• Approval workflow

• Disbursement

• EMI management

• Notifications and customer support

📌 Microservices Breakdown:

Microservice	Responsibility
CustomerService	Customer onboarding, profile, KYC
LoanService	Loan application, product matching
CreditService	Credit scoring, CIBIL check integration
RiskService	Fraud detection, risk profiling
ApprovalService	Loan approval workflow
DisbursementService	Loan disbursement, transaction logging
EMIService	EMI scheduling, repayment, ledger updates
NotificationService	Email/SMS/Push alerts
SupportService	Chatbot and agent escalation
AuthService	Auth via Azure AD (OIDC, OAuth2)

🧱 High-Level Architecture Flow

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

| Azure Traffic |

| Manager |

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

|

v

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

| Azure API Management (APIM) |

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

|

v

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

| Azure Kubernetes Service |

| (AKS Cluster) |

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

|

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

| Istio Service Mesh (Envoy Proxy) |

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

| | | | |

Customer LoanService CreditService ... Notification

Service ... Service Service etc.

- All services use mTLS, retries, circuit breakers via Istio

- Observability through Istio + Azure Monitor + Prometheus

🔐 Security Architecture

Layer	Control
Auth	Azure Active Directory + OIDC (via Azure AD App Registration)
API Security	Azure APIM validates JWT tokens and scopes
mTLS	Istio enforces encrypted service-to-service communication
RBAC	Kubernetes RBAC for pod-level access
Network	Azure VNET with NSG + private subnets for AKS
Secrets	Azure Key Vault + CSI driver in AKS

🧩 Integration & Messaging

• Azure Event Hub / Kafka on HDInsight – used for event-driven messaging (e.g., loan events, fraud alerts)

• Azure SQL / Cosmos DB – backend per microservice (polyglot persistence)

• Azure Blob Storage – store documents (KYC, loan agreements)

• External Integrations – CIBIL API, GSTN, Aadhaar KYC (via secured APIs)

🔄 DevOps & Observability Stack

Function	Tools Used
CI/CD	Azure DevOps Pipelines + YAML for multi-stage pipelines
Container Registry	Azure Container Registry (ACR)
Monitoring	Azure Monitor + Log Analytics + Prometheus + Grafana
Logging	FluentD + ELK stack + Application Insights
Tracing	OpenTelemetry + Jaeger
Secrets Management	Azure Key Vault
Helm	Helm Charts for AKS deployments
Istio Add-ons	Kiali, Jaeger, Grafana, Prometheus for mesh observability

🧬 Azure Services Mapping

Component	Azure Service Used
Container Orchestration	Azure Kubernetes Service (AKS)
Networking + VPC	Azure VNET, NSG, Subnets
API Gateway	Azure API Management (APIM)
Identity & Auth	Azure Active Directory (Azure AD)
Messaging	Azure Event Hub / Kafka on HDInsight
Database	Azure SQL, Cosmos DB
CI/CD	Azure DevOps
Container Registry	Azure Container Registry (ACR)
Monitoring & Logs	Azure Monitor, Log Analytics, Prometheus
Document Storage	Azure Blob Storage
Secrets	Azure Key Vault

🔁 Workflow Example: Loan Application

1. User logs in via Azure AD B2C, JWT is issued.

2. API call goes through Azure Traffic Manager → APIM → AKS.

3. CustomerService collects profile + KYC.

4. Sends data to CreditService via Kafka.

5. CreditService calls external APIs (e.g., CIBIL).

6. Result sent to RiskService, triggers rules.

7. If eligible, ApprovalService initiates workflow.

8. DisbursementService posts to core banking.

9. EMIService schedules repayments.

10. NotificationService alerts the customer.