AWS scenario-based interview Q&A

## 1. Security & Identity Management

Q1: A developer accidentally deletes an S3 bucket in the dev account. How would you prevent such incidents across all accounts without impacting productivity?

Testing: Knowledge of SCPs, IAM best practices, and least privilege.

Answer:

 Use AWS Organizations → Service Control Policies (SCP) to restrict destructive actions (e.g., `s3:DeleteBucket`) in non-prod accounts.

 Enable MFA Delete for critical buckets.

 Configure CloudTrail + EventBridge alerts for bucket deletion events.

Q2: How do you implement least privilege for a team of developers?

Testing: IAM role & policy design.

Answer:

 Assign roles with service-specific permissions rather than using root/admin.

 Use managed policies but customize to remove unused actions.

 Monitor with IAM Access Advisor to tighten permissions over time.

---

## 2. Networking

Q1: Your application in VPC A needs to connect to a database in VPC B in the same region without using public internet. How would you do it?

Testing: VPC connectivity, security best practices.

Answer:

 Use VPC Peering if it’s a simple one-to-one link.

 Use PrivateLink if only specific services need access.

 Avoid routing through IGW or NAT for security.

Q2: You need to connect 10 VPCs across 3 regions. How would you design the network to minimize complexity?

Testing: Multi-VPC & multi-region architecture.

Answer:

 Use AWS Transit Gateway to centralize connectivity.

 Enable inter-region peering between TGWs.

 Configure route tables carefully per environment to control traffic flow.

---

## 3. Compute Layer

Q1: During a flash sale, EC2 instances behind an ALB reach 90% CPU. What’s your immediate plan?

Testing: Auto Scaling & load management.

Answer:

 Check Auto Scaling policies and trigger scale-out.

 Temporarily add spot or on-demand instances.

 Implement caching (CloudFront/ElastiCache) for future spikes.

Q2: How do you ensure zero downtime during EC2 app updates?

Testing: Deployment strategies.

Answer:

 Use Auto Scaling group rolling updates.

 Implement blue/green deployment via CodeDeploy.

 Gradually switch traffic with weighted ALB target groups.

---

## 4. Database Layer

Q1: RDS MySQL is experiencing slow queries at peak traffic. How do you troubleshoot and optimize?

Testing: Performance tuning.

Answer:

 Check CloudWatch metrics for CPU, memory, IOPS.

 Enable Performance Insights to identify slow queries.

 Add indexes, use Read Replicas for read-heavy workloads.

 Consider Provisioned IOPS if storage is bottleneck.

Q2: How do you migrate a large production database from on-prem to AWS with minimal downtime?

Testing: Database migration strategy.

Answer:

 Use AWS DMS with Change Data Capture (CDC).

 Pre-create schema on target RDS/Aurora.

 Perform full load first, then replicate ongoing changes until cutover.

---

## 5. Automation & DevOps

Q1: Manual deployments lead to wrong versions being deployed. How would you automate?

Testing: CI/CD implementation.

Answer:

 Use CodePipeline + CodeDeploy or integrate Jenkins/GitHub Actions.

 Bake versioned AMIs using Packer.

 Automate rollback strategies in deployment configs.

Q2: How would you automate IAM key rotation?

Testing: Security automation.

Answer:

 Store keys in AWS Secrets Manager.

 Rotate keys automatically using Lambda triggered via EventBridge.

 Send notifications on rotation completion.

---

## 6. Serverless

Q1: Your Lambda function has cold start issues affecting response time. How do you mitigate?

Testing: Serverless performance optimization.

Answer:

 Use Provisioned Concurrency.

 Keep function code and dependencies small.

 Use VPC endpoints if accessing VPC resources to reduce latency.

Q2: How would you secure a serverless REST API using API Gateway + Lambda?

Testing: Serverless security best practices.

Answer:

 Enable IAM authorization or Cognito user pools.

 Enable WAF to filter malicious requests.

 Use API keys and throttling to prevent abuse.

---

## 7. Monitoring & Logging

Q1: How do you monitor Lambda functions for performance and errors?

Testing: CloudWatch and observability.

Answer:

 Enable CloudWatch Logs for function output.

 Use CloudWatch Metrics & Alarms for errors and duration.

 Use X-Ray for distributed tracing.

Q2: How do you set up centralized logging for multiple AWS accounts?

Testing: Cross-account logging & monitoring.

Answer:

 Aggregate logs to central S3 bucket via CloudWatch Logs subscription or Kinesis.

 Enable CloudTrail multi-account logging.

 Integrate with SIEM tools like Splunk.

## 8. Storage

Q1: Your S3 bucket stores critical backups. How do you ensure data durability, compliance, and disaster recovery?

Testing: Storage architecture & DR planning.

Answer:

 Enable versioning and MFA delete.

 Use S3 Cross-Region Replication (CRR) for DR.

 Apply server-side encryption (SSE-KMS).

 Set lifecycle policies to move data to Glacier/Deep Archive for compliance.

Q2: EBS volume performance is low for a high-I/O database. What’s your solution?

Testing: Block storage optimization.

Answer:

 Use Provisioned IOPS SSD (io2/io1).

 Striping multiple volumes with RAID 0 if necessary.

 Enable EBS optimization on EC2.

Q3: When would you use EFS over S3?

Answer:

 For shared file system access by multiple EC2 instances.

 When NFS file semantics are required.

 For low-latency file storage rather than object storage.

---

## 9. Databases

Q1: Your read-heavy RDS MySQL instance is under load. How do you scale reads efficiently?

Answer:

 Implement Read Replicas.

 Use Aurora Global Database for multi-region reads.

 Offload caching with ElastiCache.

Q2: How would you optimize DynamoDB for high traffic spikes?

Answer:

 Enable on-demand mode or auto-scaling read/write capacity.

 Use partition keys with high cardinality.

 Enable DAX (DynamoDB Accelerator) for caching.

Q3: What is the difference between Multi-AZ and Read Replica in RDS?

Answer:

 Multi-AZ: High availability and failover, synchronous replication.

 Read Replica: Scale reads, asynchronous replication.

---

## 10. DevOps Integration

Q1: How do you implement zero-downtime deployments with AWS CodeDeploy?

Answer:

 Use Blue/Green deployment to switch traffic to the new version gradually.

 Validate using health checks and rollback on failure.

 Integrate ALB target group weighting for incremental traffic shift.

Q2: How would you automate AMI creation for multiple environments?

Answer:

 Use Packer templates to build AMIs with required packages/config.

 Automate builds with CodePipeline or Lambda triggers.

 Version AMIs for dev/test/prod environments.

Q3: How do you integrate CI/CD with containerized apps in ECS/EKS?

Answer:

 Build Docker images using CodeBuild or Jenkins.

 Push to ECR.

 Deploy to ECS/Fargate or EKS using CodePipeline or ArgoCD.

---

## 11. Migration & Hybrid

Q1: You need to migrate petabytes of on-premises data to AWS quickly. What options do you use?

Answer:

 AWS Snowball/Snowmobile for large-scale offline transfer.

 Direct Connect for high-bandwidth online transfer.

 Use AWS DataSync for incremental sync.

Q2: How do you design a hybrid cloud setup for on-prem apps using AWS?

Answer:

 Establish VPN or Direct Connect for secure connectivity.

 Use VPC Peering/Transit Gateway for centralized routing.

 Extend Active Directory via AWS Managed AD for authentication.

---

## 12. Cost Optimization

Q1: Your AWS monthly bill is high. How would you identify and optimize costs?

Answer:

 Use AWS Cost Explorer & Trusted Advisor for resource recommendations.

 Analyze underutilized EC2 instances and EBS volumes.

 Switch to Reserved Instances or Savings Plans for predictable workloads.

 Use Spot Instances for non-critical workloads.

Q2: How would you reduce costs in a multi-region deployment?

Answer:

 Review cross-region replication usage; replicate only necessary data.

 Optimize data transfer costs by using CloudFront for caching.

 Right-size instances and remove idle resources.

Q3: How do you manage cost in serverless applications?

Answer:

 Monitor Lambda invocation metrics.

 Optimize memory allocation and execution time.

 Use DynamoDB on-demand mode for unpredictable workloads.

---

## 13. Advanced Architecture / High Availability

Q1: Design a multi-region highly available web application. What’s your approach?

Answer:

 Deploy ALB + EC2/ECS in multiple AZs per region.

 Use Route 53 latency-based routing across regions.

 Replicate databases using Aurora Global DB or DynamoDB global tables.

 Use CloudFront for global content caching.

Q2: How do you design for Disaster Recovery (DR) in AWS?

Answer:

 Backup & restore: Snapshots, S3/Glacier backups.

 Pilot light: Minimal resources in DR region, scale when needed.

 Warm standby: Scaled-down environment running continuously.

 Multi-site: Fully active-active in multiple regions.

Q3: Define RTO and RPO.

Answer:

 RTO (Recovery Time Objective): Max tolerable downtime.

 RPO (Recovery Point Objective): Max tolerable data loss.

 Choose DR strategy based on business requirements.

AWS Interview Master Guide

AWS Interview Master Guide - Full Q&A

1. Security & Identity Management

·         Q: What is IAM in AWS?

A: Identity and Access Management – controls who can access AWS resources and what actions they can take.

 

·         Q: IAM Users vs Roles?

A: Users: Long-term credentials for people/services. Roles: Temporary credentials for AWS resources or cross-account access.

 

·         Q: IAM Policy types?

A: Identity-based, Resource-based, Permissions boundaries, SCPs.

 

·         Q: AWS WAF use cases?

A: Block SQL injection, XSS, DDoS mitigation, geo-restriction.

 

·         Q: What is AWS Shield?

A: Managed DDoS protection (Standard = free, Advanced = paid with SLA).

 

·         Q: How does GuardDuty detect threats?

A: Analyzes VPC Flow Logs, CloudTrail, DNS logs using ML and threat intel.

 

·         Q: AWS Inspector vs AWS Config?

A: Inspector → Security vulnerability scans. Config → Configuration tracking & compliance.

 

·         Q: Steps for least privilege access?

A: Create minimal policies, review with IAM Access Analyzer, remove unused permissions.

 

·         Q: KMS vs Secrets Manager?

A: KMS = encryption keys. Secrets Manager = credentials & rotation.

 

·         Q: How to secure S3 buckets?

A: Block public access, bucket policies, SSE encryption, MFA delete.

 

·         Q: Difference between Security Groups and NACLs?

A: SG: Instance-level, stateful. NACL: Subnet-level, stateless.

 

·         Q: What is MFA in AWS?

A: Multi-Factor Authentication – extra security layer using device codes.

 

·         Q: Bastion Host best practice?

A: Public subnet, SSH from admin IP only, use SSM Session Manager.

 

·         Q: Encryption at rest vs in transit?

A: At rest → SSE-KMS, EBS encryption. In transit → TLS/HTTPS.

 

2. Networking

·         Q: What is VPC?

A: Isolated virtual network in AWS for resources.

 

·         Q: Key VPC components?

A: Subnets, Route Tables, IGW, NAT Gateway, SG, NACLs, VPC Peering.

 

·         Q: Public vs Private subnet?

A: Public: route to IGW, public IP. Private: no IGW, only private IP.

 

·         Q: VPC Peering vs Transit Gateway?

A: Peering: direct 2-VPC link. TGW: hub for many VPCs & on-prem.

 

·         Q: NAT Gateway purpose?

A: Allows private subnet instances to reach internet without inbound access.

 

·         Q: VPN types in AWS?

A: Site-to-Site, Client VPN, AWS Direct Connect.

 

·         Q: PrivateLink use case?

A: Secure private service access without public internet.

 

·         Q: VPC Flow Logs use?

A: Track traffic in/out of ENIs for troubleshooting.

 

·         Q: Route Table function?

A: Controls outbound/inbound traffic destinations.

 

·         Q: Difference between IGW & EIGW?

A: IGW: full internet access. EIGW: only outbound internet access.

 

·         Q: How to connect multiple VPCs securely?

A: TGW, PrivateLink, Peering + route tables.

 

·         Q: ALB vs NLB?

A: ALB: HTTP/HTTPS, content routing. NLB: TCP/UDP, high speed.

 

·         Q: VPC Endpoint types?

A: Gateway (S3/DynamoDB), Interface (ENI-based).

 

3. Compute

·         Q: EC2 pricing models?

A: On-Demand, Reserved, Spot, Savings Plans.

 

·         Q: EC2 families?

A: General, Compute Optimized, Memory Optimized, Storage Optimized.

 

·         Q: Auto Scaling use?

A: Scale EC2 count based on metrics (CPU, traffic).

 

·         Q: ALB vs NLB vs CLB?

A: ALB = L7 HTTP/HTTPS. NLB = L4 TCP/UDP. CLB = legacy.

 

·         Q: Placement groups?

A: Cluster, Spread, Partition – for network latency control.

 

·         Q: Spot Instances use?

A: Cost saving, non-critical workloads.

 

·         Q: What is ECS?

A: AWS managed container orchestration (Docker).

 

·         Q: ECS vs EKS?

A: ECS: AWS-native. EKS: Kubernetes.

 

·         Q: User Data in EC2?

A: Scripts run at instance launch for config automation.

 

·         Q: Elastic IP use?

A: Static public IPv4 for EC2.

 

·         Q: Difference between ELB and API Gateway?

A: ELB = traffic distribution. API Gateway = API management.

 

·         Q: RDS Proxy role?

A: Connection pooling for RDS/Lambda/EC2.

 

4. Storage

·         Q: S3 vs EFS vs EBS?

A: S3 = object storage, EFS = shared file storage, EBS = block storage.

 

·         Q: S3 storage classes?

A: Standard, IA, One-Zone IA, Glacier, Deep Archive.

 

·         Q: S3 versioning use?

A: Keeps old versions for recovery.

 

·         Q: Lifecycle policies?

A: Auto-move/expire objects.

 

·         Q: Cross-region replication?

A: Auto-copy S3 objects to another region.

 

·         Q: How to secure S3?

A: Block public, bucket policy, SSE encryption.

 

·         Q: EBS snapshot purpose?

A: Backup EC2 volumes to S3.

 

·         Q: EBS vs Instance Store?

A: EBS persistent, Instance Store temporary.

 

·         Q: EFS vs FSx?

A: EFS = NFS Linux, FSx = Windows/High-perf.

 

·         Q: Multipart upload in S3?

A: Upload large files in parts for efficiency.

 

5. Databases

·         Q: RDS vs DynamoDB?

A: RDS = SQL, DynamoDB = NoSQL.

 

·         Q: Aurora vs RDS?

A: Aurora = AWS-optimized RDS with better scaling.

 

·         Q: Multi-AZ vs Read Replica?

A: Multi-AZ = HA. Read Replica = scale reads.

 

·         Q: DynamoDB partition key best practice?

A: High cardinality to avoid hot partitions.

 

·         Q: ElastiCache use?

A: In-memory caching for fast reads.

 

·         Q: RDS Proxy benefit?

A: Connection pooling.

 

·         Q: DMS purpose?

A: Migrate DB with minimal downtime.

 

·         Q: Backup in DynamoDB?

A: On-demand + point-in-time recovery.

 

6. Serverless

·         Q: Lambda cold start?

A: Delay on first run – fix with Provisioned Concurrency.

 

·         Q: Lambda vs EC2?

A: Lambda = short-lived, event-based. EC2 = full control.

 

·         Q: API Gateway + Lambda?

A: Build serverless REST APIs.

 

·         Q: Step Functions use?

A: Workflow orchestration.

 

·         Q: EventBridge vs SNS?

A: EventBridge = event bus, SNS = pub/sub messaging.

 

·         Q: DynamoDB scaling?

A: On-demand mode, adaptive capacity.

 

7. Automation & IaC

·         Q: CloudFormation vs Terraform?

A: CF = AWS-only. Terraform = multi-cloud.

 

·         Q: AWS CLI use?

A: Automate via shell scripts.

 

·         Q: Boto3 use?

A: AWS SDK for Python.

 

·         Q: CodePipeline?

A: CI/CD orchestration.

 

·         Q: AMI automation?

A: Packer or Lambda scripts.

 

8. Monitoring & Logging

·         Q: CloudWatch vs CloudTrail?

A: CW = metrics/logs. CT = API calls audit.

 

·         Q: X-Ray use?

A: Trace requests for performance bottlenecks.

 

·         Q: Alarms in CloudWatch?

A: Notify via SNS.

 

·         Q: Centralized logging?

A: CloudWatch → Kinesis → S3/SIEM.

 

9. DevOps Integration

·         Q: CI/CD in AWS?

A: CodeCommit → CodeBuild → CodeDeploy → CodePipeline.

 

·         Q: Blue/Green deployment?

A: Zero-downtime deployments.

 

·         Q: Canary release?

A: Gradual traffic shift.

 

10. Migration & Hybrid

·         Q: Snowball?

A: Physical device for TB-PB data transfer.

 

·         Q: DMS?

A: Minimal downtime DB migration.

 

·         Q: Direct Connect?

A: Private dedicated link to AWS.

 

11. Cost Optimization

·         Q: Trusted Advisor?

A: Cost, security, performance checks.

 

·         Q: RI vs Savings Plans?

A: Both give discounts; Savings Plans more flexible.

 

·         Q: Spot instances?

A: Cheapest EC2 pricing.

 

12. Advanced Architecture

·         Q: Multi-Region design?

A: DR, latency optimization.

 

·         Q: RTO vs RPO?

A: Recovery Time Objective, Recovery Point Objective.

 

·         Q: DR strategies?

A: Backup/restore, pilot light, warm standby, multi-site.

 

AWS

 1. Security Services

Q1. Explain how AWS WAF works and common use cases.

 Definition: AWS WAF (Web Application Firewall) protects web applications from common exploits (SQL injection, XSS, etc.) by filtering HTTP(S) requests based on customizable rules.

 Example: Block requests from specific IP ranges or allow only certain country-based traffic.

 Use Cases:

  1. Mitigate DDoS attacks.

  2. Prevent OWASP Top 10 vulnerabilities.

  3. Restrict access by geolocation.

Q2. What is Amazon GuardDuty, and how does it detect threats?

 Definition: GuardDuty is a threat detection service that continuously monitors AWS accounts for malicious activity.

 How it works: Uses AWS logs (VPC Flow Logs, CloudTrail, DNS logs) + ML models to detect anomalies like suspicious API calls or port scanning.

 Example: Alerts when a new API key is used from an unusual location.

Q3. Difference between AWS Inspector and AWS Config.

| AWS Inspector                                                           | AWS Config                                             |

| ----------------------------------------------------------------------- | ------------------------------------------------------ |

| Automated security assessment of EC2 instances and container workloads. | Tracks AWS resource configurations over time.          |

| Focused on vulnerabilities & compliance.                                | Focused on configuration compliance & drift detection. |

Q4. How does AWS Systems Manager help in managing EC2 instances?

 Definition: AWS Systems Manager (SSM) lets you manage EC2 & on-prem servers at scale without direct SSH.

 Features:

   Run commands remotely (patching, software install).

   Parameter Store for secure config storage.

   Session Manager for secure shell-less access.

Q5. What are Network ACLs (NACL) and how are they different from Security Groups?

| NACL                                                   | Security Group                                   |

| ------------------------------------------------------ | ------------------------------------------------ |

| Operates at subnet level.                              | Operates at instance level.                      |

| Stateless (return traffic must be explicitly allowed). | Stateful (return traffic automatically allowed). |

| Rules are evaluated in order.                          | Rules are evaluated as a whole (no priority).    |

Q6. How would you design a bastion host for secure access to private instances?

 Launch EC2 in a public subnet with restricted inbound SSH (only admin IP).

 Access private instances via the bastion host using SSH agent forwarding.

 Enable CloudTrail and SSM Session Manager for auditing.

Q7. Difference between IAM Roles, Policies, and Users.

 User: Represents a person/service with credentials.

 Role: Temporary identity for AWS resources or services.

 Policy: JSON document defining permissions for a user/role/group.

Q8. Best practices for securing SSH/HTTPS connections in AWS.

 Use key pairs instead of passwords.

 Restrict inbound rules to known IPs.

 Use ACM for HTTPS certificates.

 Enable Perfect Forward Secrecy (PFS).

Q9. How do you implement least privilege access in AWS?

 Create minimal permission policies per role.

 Use IAM Access Analyzer to detect unused permissions.

 Rotate keys regularly and remove unused accounts.

Q10. Steps to enable and monitor encryption in transit and at rest.

 At rest: Enable SSE (Server-Side Encryption) in S3, KMS for RDS/EBS.

 In transit: Use HTTPS, enable TLS ≥ 1.2, enforce via ALB/API Gateway.

 Monitor via AWS Config rules and CloudTrail events.

 2. Networking

Q1. What is a VPC, and what are its key components?

 Definition: Amazon Virtual Private Cloud (VPC) is a logically isolated network in AWS where you launch resources.

 Key Components: Subnets, Route Tables, Internet Gateway, NAT Gateway, Security Groups, NACLs, VPC Peering.

Q2. How does a VPC Peering connection work?

 Private network connection between two VPCs using private IPs without VPN or internet.

 Traffic routing done via route tables.

Q3. Difference between VPC Peering and Transit Gateway.

| VPC Peering                                 | Transit Gateway                                                |

| ------------------------------------------- | -------------------------------------------------------------- |

| Point-to-point connection between two VPCs. | Central hub for connecting multiple VPCs and on-prem networks. |

| No transitive routing.                      | Supports transitive routing.                                   |

Q4. What is a NAT Gateway and when would you use it?

 Provides outbound internet access for instances in private subnets without exposing them to inbound internet traffic.

Q5. Difference between Public and Private subnets.

| Public                         | Private                              |

| ------------------------------ | ------------------------------------ |

| Has route to Internet Gateway. | No direct route to Internet Gateway. |

| Instances can have public IPs. | Instances only have private IPs.     |

Q6. How does a VPN connection work between on-premises and AWS?

 Uses IPsec tunnels between AWS VPN Gateway and on-premises gateway to securely transmit data.

Q7. Explain Security Groups vs NACLs in detail.

 SG: Instance-level, stateful.

 NACL: Subnet-level, stateless.

Q8. How do you connect multiple VPCs securely?

 Transit Gateway, VPC Peering, or PrivateLink depending on architecture.

Q9. Steps to configure VPC Flow Logs and analyze them.

1. Enable Flow Logs for VPC/Subnet/ENI.

2. Send logs to S3 or CloudWatch Logs.

3. Analyze with Athena, CloudWatch Insights, or SIEM.

Q10. What are Route Tables and how do they control network traffic?

 Route tables map destination CIDR blocks to targets (IGW, NAT, VGW, TGW).

---

## 3. Compute Layer (Frontend/Backend)

Q1. Difference between EC2 instance types

 General Purpose: Balanced CPU/memory.

 Compute Optimized: High CPU.

 Memory Optimized: High RAM.

 Storage Optimized: High IOPS.

Q2. How to scale EC2 instances automatically.

 Use Auto Scaling Groups with scaling policies (CPU utilization, request count).

Q3. Application Load Balancer vs Network Load Balancer.

| ALB                    | NLB                            |

| ---------------------- | ------------------------------ |

| Layer 7, HTTP/HTTPS.   | Layer 4, TCP/UDP.              |

| Content-based routing. | High performance, low latency. |

Q4. Configure high availability across multiple AZs.

 Deploy instances in multiple AZs + load balancer + health checks.

Q5. Use an RDS Proxy and why?

 Pools DB connections, improves scalability, reduces DB overload.

Q6. ELB vs API Gateway.

 ELB: Distributes traffic to servers.

 API Gateway: Manages APIs with rate limiting, caching, auth.

---

## 4. Database Layer

Q1. RDS vs DynamoDB

 RDS: Relational, SQL-based.

 DynamoDB: NoSQL, key-value.

Q2. How Redis (ElastiCache) improves performance

 In-memory caching reduces DB queries latency.

Q3. RDS Proxy benefits

 Connection pooling, failover handling.

Q4. Multi-AZ deployment in RDS

 Synchronous standby in another AZ for HA.

Q5. Read Replica vs Multi-AZ

| Read Replica            | Multi-AZ     |

| ----------------------- | ------------ |

| Asynchronous.           | Synchronous. |

| Used for scaling reads. | Used for HA. |

Q6. MemoryDB vs ElastiCache

 MemoryDB: Durable, Redis-compatible, Multi-AZ.

 ElastiCache: Cache only, less durable.

---

## 5. Automation

Q1. CloudFormation working

 Infrastructure as Code (YAML/JSON) to create/manage AWS resources.

Q2. Terraform vs CloudFormation

| Terraform    | CloudFormation    |

| ------------ | ----------------- |

| Multi-cloud. | AWS only.         |

| HCL syntax.  | JSON/YAML syntax. |

Q3. AWS Lambda trigger examples

 S3 events, DynamoDB streams, API Gateway calls.

Q4. Role of Boto3

 Python SDK for AWS automation.

Q5. AWS CLI for automation

 Scripting tasks like resource creation, backups.

Q6. Automate AMI creation

 Lambda + CloudWatch + EC2 CreateImage API.

Q7. CI/CD in AWS

 CodeCommit → CodeBuild → CodeDeploy → CodePipeline.

---

## 6. Serverless

Q1. Lambda vs EC2

 Lambda: Event-driven, no server mgmt.

 EC2: Full control, long-running apps.

Q2. API Gateway + Lambda

 API Gateway routes HTTP requests to Lambda functions.

Q3. Secure serverless

 IAM roles, parameter store, VPC access, WAF.

Q4. DynamoDB scaling best practices

 On-demand mode, partition key design.

Q5. Cold starts in Lambda

 Reduce by using Provisioned Concurrency.

Q6. Step Functions usage

 Orchestrate multiple Lambdas in workflows.

Q7. Sync vs Async Lambda

 Sync: Waits for result.

 Async: Queues invocation.

---

## 7. Monitoring & Logging

Q1. CloudWatch vs CloudTrail

 CloudWatch: Metrics, logs, alerts.

 CloudTrail: API call history.

Q2. CloudWatch alarms setup

 Choose metric → define threshold → set SNS notification.

Q3. Centralized logging with Splunk

 Use Kinesis Firehose to stream logs to Splunk.

Q4. Monitor Lambda

 CloudWatch metrics + X-Ray tracing.

Q5. Grafana/Prometheus for AWS

 Pull metrics from CloudWatch via data sources.

Q6. VPC Flow Logs for troubleshooting

 Identify blocked traffic, latency issues.

Q7. Centralized monitoring best practices

 Unified dashboards, log retention policy.

---

## 8. Storage

Q1. S3 vs EFS vs EBS

 S3: Object storage.

 EFS: Shared file storage.

 EBS: Block storage for EC2.

Q2. S3 versioning

 Keeps old object versions for recovery.

Q3. Secure S3

 Block public access, enable encryption, IAM policies.

Q4. S3 Standard vs IA vs Glacier

 Standard: Frequent access.

 IA: Infrequent access.

 Glacier: Archival.

Q5. When to use EFS over S3

 When file system semantics needed.

Q6. S3 cross-region replication

 Replicates objects automatically to another region.

---

## 9. Packer & AMI Management

Q1. Packer with AWS

 Automates AMI creation using templates.

Q2. Create custom AMI

 Launch EC2 → install configs → Create Image.

Q3. Automate AMI creation with Packer

 Define JSON template → run `packer build`.

Q4. Manual vs automated AMI creation

| Manual                   | Automated                   |

| ------------------------ | --------------------------- |

| Manual steps in console. | Fully scripted, repeatable. |

Micro Services

 1) What is micro services architecture and how does it work?

A)Microservices architecture is a way of designing software systems where an application is built as a collection of small, independent services that communicate with each other over a network.

Instead of having one big, tightly integrated monolithic codebase, you break it into smaller, self-contained components—each responsible for a specific business function.

How It Works

1. Decomposition into Services

    Each micro service handles a single, well-defined capability (e.g., User Management, Payment Processing, Inventory Tracking).

    Services are developed, deployed, and scaled independently.

2. Independent Deployment

    You can update or replace one service without redeploying the whole system.

    This enables faster releases and easier experimentation.

3. Communication Between Services

    Services talk to each other using APIs (often HTTP/REST, gRPC, or messaging systems like Kafka or RabbitMQ).

    Data sharing is typically minimal—each service usually has its own database to maintain independence.

4. Service Discovery & Load Balancing

    A service registry helps services find each other dynamically.

    Load balancers distribute requests across multiple instances.

5. Resilience & Scaling

    If one service fails, others can still operate (assuming proper design).

    You can scale only the services that need extra capacity instead of the whole system.

6. Technology Flexibility

    Teams can choose different programming languages, frameworks, and storage solutions for each micro service (as long as they speak the agreed-upon communication protocols).

Example

Imagine an e-commerce platform:

Auth Service – Handles login and registration

Catalog Service – Manages product listings

Cart Service – Handles shopping cart operations

Payment Service – Processes transactions

Shipping Service – Calculates delivery estimates and handles logistics

If you need to improve payment speed, you just update the Payment Service without touching the rest.

Advantages

Scalability – Scale services independently

Faster Development – Parallel work by small teams

Resilience – Failure in one service won’t necessarily crash the whole app

Tech Diversity – Use the right tool for each job

Challenges

Complexity – More moving parts than monolithic architecture

Data Consistency – No single database, so distributed transactions are harder

Networking Overhead – More API calls = higher latency potential

DevOps Skills Needed – CI/CD pipelines, containerization (Docker, Kubernetes) often required

1. Steps to Implement Microservices Architecture

 Step 1 – Identify Business Capabilities Break down your application into domains (e.g., Billing, Orders, Shipping, Inventory).

 Each domain becomes a microservice.

 Step 2 – Define Service Boundaries

 Clearly define what each service is responsible for.

 Use Domain-Driven Design (DDD) concepts like bounded contexts.

 Step 3 – Choose Communication Mechanism

 Synchronous: REST, gRPC (for request-response)

 Asynchronous: Message queues like RabbitMQ, Kafka (for event-driven)

 Step 4 – Assign Independent Databases

 Each service should have its own database to avoid tight coupling.

 Choose storage type based on needs (SQL, NoSQL, in-memory).

 Step 5 – Containerize Services

 Use Docker to package services.

 Orchestrate them with Kubernetes or ECS.

 Step 6 – Implement Service Discovery

 Use Eureka, Consul, or Kubernetes DNS to let services find each other dynamically.

 Step 7 – Ensure Observability

 Logging (ELK stack, Splunk)

 Metrics (Prometheus, Grafana)

 Tracing (Jaeger, Zipkin)

 Step 8 – Secure the Services

 API Gateway for routing & authentication.

 OAuth 2.0 / JWT for securing endpoints.

 2. Approaches to Building Microservices

 A. Top-Down (Greenfield Development)

 Build a brand-new system using microservices from scratch.

 Best when starting a new project with no legacy constraints.

 B. Bottom-Up (Refactoring Monolith)

 Start from your existing monolith and gradually extract services.

 Typical pattern:

  1. Identify a feature.

  2. Extract it as a microservice.

  3. Connect via API Gateway.

 Example: Extract Order Processing from your monolith into a separate service.

 C. Strangler Fig Pattern

 Replace monolith modules one by one with microservices until nothing of the monolith remains.

 Both old and new code run together during migration.

 D. Hybrid Approach

 Keep core features in the monolith, and build new features as microservices.

 Gradually replace monolith parts.

Q) How to secure API

A) We secure APIs using authentication, authorization, and encryption.

Authentication is done via OAuth2/OpenID Connect with JWT tokens or API keys.

Authorization uses RBAC or scopes.

All traffic goes over HTTPS/TLS, with input validation and rate limiting at API Gateway.

We use centralized identity providers (e.g., Azure AD) and follow least privilege & key rotation best practices.

Circuit Breaker 

A Circuit Breaker is a design pattern in micro Services that prevents repeated calls to a failing service.

It has three states: Closed (calls pass), Open (calls blocked after failures), and Half-Open (test limited calls before fully closing again).

It improves fault tolerance and avoids cascading failures.

Circuit Breaker States

 Closed → Normal state, all requests pass through. Failures are counted.

 Open → Triggered after threshold failures, all calls blocked for a cooldown period.

 Half-Open → After cooldown, a few test calls are allowed to check if service is healthy.

OSLATE

OSLATE is a checklist for designing resilient microservices — it covers Observability, Security, Latency, Availability, Throughput, and Efficiency to ensure high performance, reliability, and scalability.

O – Observability: Logging, metrics, tracing (e.g., OpenTelemetry, Application Insights).

S – Security: Authentication, authorization, data encryption, API Gateway protection.

L – Latency: Optimize response times, use caching, asynchronous messaging.

A – Availability:Redundancy, failover, health checks, load balancing.

T – Throughput:Scale services horizontally, queue workloads, use batching.

E – Efficiency:Resource optimization, cost control, auto-scaling, right-sizing services.

Q) How to implement microservices and approaches

To implement microservices, I follow these steps and approaches:

1. Identify Services – Break the application into small, business-capable services (Domain-Driven Design).

2. Choose Communication – Use REST/gRPC for synchronous, and messaging (RabbitMQ, Azure Service Bus, Kafka) for asynchronous.

3. Database per Service – Each service has its own DB to ensure loose coupling.

4. API Gateway – Central entry point for routing, authentication, and rate limiting.

5. Security – OAuth2/OpenID Connect with JWT tokens, HTTPS, role-based access.

6. Resilience – Patterns like Circuit Breaker, Retry, Bulkhead (Polly in .NET).

7. Observability – Centralized logging, metrics, tracing (e.g., OpenTelemetry).

8. Deployment – Use containers (Docker, Kubernetes, Azure Container Apps) for scalability.

One-line wrap-up:

Identify services → isolate them → secure & connect them → monitor & deploy independently.

Q) Security Configuration in microservices/API

Security configuration in microservices covers authentication, authorization, and transport security.

We configure services to use OAuth2/OpenID Connect with JWT tokens, validate them at the API Gateway, 

enforce HTTPS/TLS, and apply role- or scope-based authorization.

We also secure service-to-service calls with mTLS or managed identities, enable input validation, rate limiting, and use centralized secrets management (e.g., Azure Key Vault).

1. Authentication – Azure AD / Auth0 / IdentityServer, JWT token validation in middleware.

2. Authorization – RBAC/Scopes, `[Authorize]` attributes in .NET.

3. Transport Security – HTTPS/TLS, HSTS headers, disable weak protocols.

4. Secrets & Keys – Store in Azure Key Vault, not in code.

5. Service-to-Service Security – mTLS, managed identities, network restrictions.

6. API Gateway Policies – Validate tokens, apply IP whitelisting, throttle requests.

7. Monitoring – Security logging, intrusion detection, anomaly alerts.

Q) how to secure DB

•  I secure a database by enforcing strong authentication and least-privilege authorization.
•  encrypting data at rest with TDE and in transit with TLS, and isolating the database in a private   network with firewall rules or VNET integration. 
• I store credentials securely in a vault like Azure Key Vault, never in code, and use managed identities where possible. 
• I also enable auditing, monitoring,and alerts for suspicious activity, keep the database patched, and maintain tested backups for disaster recovery.

Q)  Client Correlation ID

   A Client Correlation ID is a unique ID (like a GUID) sent with each request so that logs from             different microservices can be linked together.

   for tracing and debugging. It’s passed in headers like `X-Correlation-ID` and reused across all service     calls for end-to-end tracking.

Q) Azure Service Bus Publish/Subscribe

  Azure Service Bus supports Pub/Sub using Topics and Subscriptions.

  A publisher sends a message to a Topic, and each Subscription gets its own copy of the message.

  This allows multiple independent subscribers to process the same event without knowing 

  about each other.

 We can also apply SQL-like filters so only relevant messages reach a subscription.

  It’s reliable, decouples services, and ensures at-least-once delivery. 

Q)  How database communicate DB  in microservices

In microservices, each service has its own database to ensure loose coupling. Services never share the same DB directly. 

If one service needs data from another, it communicates through APIs or messaging, not by querying the other service’s DB. 

For consistency, we use patterns like Saga or CQRS, and for async data sharing, we use events via message brokers like Azure Service Bus or Kafka.

1. Saga Pattern

    Saga manages distributed transactions in microservices by breaking them into smaller local transactions. Each service updates its DB and triggers the next step via events. If one step fails, compensating transactions roll back previous changes. Can be implemented as Choreography (event-driven) or Orchestration (central controller).

2. CQRS (Command Query Responsibility Segregation)

CQRS separates write (commands) and read (queries) models. Commands update the data store, while queries read from a separate read model optimized for retrieval. This improves scalability, performance, and allows event sourcing.

1. Sidecar Pattern

Sidecar Pattern runs helper components alongside the main service in the same deployment environment (like a pod in Kubernetes). 

The sidecar adds capabilities like logging, monitoring, service discovery, or security without changing the main service code.

2. Aggregator Pattern

Aggregator Pattern collects data from multiple microservices, combines it, and sends a single unified response to the client. It reduces the number of client calls and hides service complexity.nt logic.

 1. Delayed Queue (DQ)

A delayed queue holds messages for a set amount of time before making them available to consumers. It’s used for scenarios like scheduled tasks, retrying failed processes after a delay, or order cancellation grace periods. In Azure Service Bus, we can use `ScheduledEnqueueTimeUtc` to implement it; in RabbitMQ, we use a delayed exchange or TTL + dead-letter queue.

2. Dead Letter Queue (DLQ)

(I think you meant Deleterent as Dead Letter Queue — common in messaging systems)

A Dead Letter Queue stores messages that cannot be delivered or processed after multiple retries. This prevents losing data and allows investigation. In Azure Service Bus, each queue/topic has a built-in DLQ, accessed via a sub-queue path `/$DeadLetterQueue`.

IQS

 1. Techniques for Generating Tokens

* JWT (JSON Web Token) – Common in Web API, contains claims, digitally signed.

* OAuth2 Access Tokens – Generated via authentication servers (e.g., IdentityServer).

* GUID Tokens – Random unique IDs for session/transaction purposes.

* Refresh Tokens – Long-lived tokens to get new access tokens.

* Encrypted Tokens – Using symmetric/asymmetric encryption.

Fastest: Usually JWT is faster for stateless APIs because no DB lookup is needed once issued.

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 2. DB First vs Code First (Entity Framework)

* DB First – Start from an existing DB → generate model from DB schema.

* Code First – Start from C# classes → EF generates DB schema.

Which is faster?

* Development Speed: DB First is quicker if DB already exists.

* Flexibility/Maintenance: Code First is better for iterative development.

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 3. Bundle Config & CDN

* Bundle Config – Combines and minifies multiple JS/CSS files into one bundle for fewer HTTP requests.

* CDN (Content Delivery Network) – Hosts static files across global servers to serve them faster to users.

Which is better?

* Use both: CDN for delivery speed, Bundle for minimizing HTTP requests.

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 4. Application Object vs Session Object

* Application Object – Global data shared across all users in the application.

* Session Object – Data stored per user session.

Difference: Application is global, Session is user-specific.

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 5. Abstract Class vs Interface

* Abstract Class – Can have implemented & abstract methods, fields, constructors.

* Interface – Only method/property/event signatures, no implementation (until default methods in C# 8+).

Key Difference: Abstract class supports inheritance with shared code; interface is a contract only.

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 6. IIS Request Processing

1. Request hits HTTP.sys (kernel mode listener).

2. Passes to IIS Worker Process (w3wp.exe).

3. Request pipeline executes modules/handlers.

4. ASP.NET runtime processes request.

5. Response sent back to client.

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 7. Status Codes

* 200 OK – Successful request.

* 403 Forbidden – Request understood but denied (permissions).

* 500 Internal Server Error – Server error.

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 8. What is Render

* In ASP.NET MVC: `RenderBody`, `RenderSection`, `RenderPartial` methods output HTML to response.

* In general: Process of generating and sending the final output to browser.

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 9. Web API Testing Techniques

* Manual Testing (Postman, Swagger).

* Unit Testing (NUnit, xUnit).

* Integration Testing.

* Automated UI + API Tests (Selenium + API tests).

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 10. Difference: Web API vs WCF

* Web API – REST, lightweight, works over HTTP only, supports JSON/XML.

* WCF – SOAP, supports multiple protocols (HTTP, TCP, MSMQ), more configuration-heavy.

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 11. Without Try Block Exception Handling

* Global.asax `Application_Error` event.

* Custom Middleware in .NET Core.

* Exception Filters (`IExceptionFilter`).

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 12. Verbs in Web API

* GET – Retrieve.

* POST – Create.

* PUT – Update (replace).

* PATCH – Update (partial).

* DELETE – Remove.

* HEAD/OPTIONS – Metadata & pre-flight.

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 13. Contracts

* A contract defines the shape of communication between service & client in WCF.

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 14. Service Contract vs Message Contract

* Service Contract – Methods & operations exposed by service.

* Message Contract – Defines custom SOAP message structure.

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 15. SOLID Principles

1. S – Single Responsibility.

2. O – Open/Closed.

3. L – Liskov Substitution.

4. I – Interface Segregation.

5. D – Dependency Inversion.

1. **S — Single Responsibility Principle (SRP)**

   * A class/module should have only **one reason to change** — meaning it should do **one thing well**.

2. **O — Open/Closed Principle (OCP)**

   * Code should be **open for extension but closed for modification**, allowing you to add features without altering existing, tested code.

3. **L — Liskov Substitution Principle (LSP)**

   * Subclasses should be **replaceable for their base classes** without breaking functionality.

4. **I — Interface Segregation Principle (ISP)**

   * Prefer many **small, specific interfaces** over one large, general-purpose interface to avoid forcing classes to implement things they don’t need.

5. **D — Dependency Inversion Principle (DIP)**

   * Depend on **abstractions, not concrete implementations**, so code is loosely coupled and more maintainable.

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 16. Install Certificates in IIS

1. Open IIS → Server Certificates.

2. Import certificate (.pfx/.cer).

3. Bind it to HTTPS site in Bindings.

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 17. Passport Authentication

* Microsoft’s old identity system.

* Redirects to passport.net, authenticates, returns ticket to site.

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 18. Difference: Web Service vs WCF

* Web Service – SOAP over HTTP, only XML.

* WCF – Supports SOAP + multiple protocols, flexible serialization.

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 19. Web API Token Types

* Bearer Tokens (JWT).

* OAuth Access Tokens.

* Refresh Tokens.

* Hawk/MAC Tokens (less common).

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 20. Where Configure Endpoints in WCF

* `web.config` or `app.config` under `<system.serviceModel><services>`.

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 21. Difference XML vs JSON

* XML – Verbose, supports attributes, tags, schema validation.

* JSON – Lightweight, easier to parse, widely used in REST.

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 22. Bundle Config vs CDN – Which Better

* CDN – Better for public libraries (fast load globally).

* Bundle Config – Better for your own site scripts to reduce requests.

* Best: Use both.

JAN 1st