AWS AURORA (POSTGRESQL COMPATIBLE) & DYNAMO DB

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The AWS Aurora (PostgreSQL Compatible) & DynamoDB syllabus is a job-oriented training program focused on designing, deploying, and managing cloud-native databases for real AWS projects. It explains how Aurora delivers high-performance, scalable relational databases and how DynamoDB supports fully managed NoSQL workloads for modern applications. This training is important because data reliability, scalability, and cost efficiency are critical in cloud environments. It is best suited for Cloud Engineers, DevOps Engineers, Database Engineers, and Solution Architects who work in AWS operations, support, and production-level implementations.

Duration of Training : 45 – 60 Hours
Batch type : Weekdays/Weekends
Mode of Training : Classroom/Online/Corporate Training
Detailed Syllabus • Hands-on Labs • Assignments
• Real – Time Scenarios • Projects Level: Intermediate to Advanced

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Overview

The Syllabus

Curriculum Designed by Experts

PART 1: AWS Aurora with PostgreSQL (30–35 Hours)

Module 1: AWS Database Fundamentals & RDS Overview (3 Hours)

Topics
OLTP vs OLAP databases
RDS vs Aurora vs Self-managed PostgreSQL
Aurora architecture overview
Shared storage, 6-way replication
Regional vs Global databases
Lab
Create PostgreSQL RDS
Compare with Aurora PostgreSQL
Job Scenario
Choose Aurora vs RDS PostgreSQL for a high-availability application.

Module 2: Aurora PostgreSQL Architecture Deep Dive (5 Hours)

Topics
Compute & Storage separation
Aurora storage engine
Read replicas & writer endpoint
Failover & recovery
Serverless v2 overview
Lab
Create Aurora PostgreSQL cluster
Configure reader endpoints
Simulate failover
Assignment
Architecture diagram & justification document

Module 3: Aurora PostgreSQL Setup & Configuration (5 Hours)

Topics
Parameter groups
Option groups
Subnet groups
Security groups & IAM authentication
TLS/SSL connections
Lab
Tune PostgreSQL parameters
Enable IAM authentication
Secure cluster with VPC rules
Job Scenario
Application connection timeout after migration → troubleshoot.

Module 4: Backup, Restore & Disaster Recovery (4 Hours)

Topics
Automated backups
Manual snapshots
Point-in-Time Recovery (PITR)
Cross-region snapshots
Global Aurora
Lab
Restore cluster from snapshot
Test PITR recovery
Assignment
DR strategy for a fintech workload

Module 5: Performance Tuning & Monitoring (5 Hours)

Topics
Performance Insights
CloudWatch metrics
Query execution plans
Indexing strategies
Connection pooling (PgBouncer)
Lab
Identify slow queries
Tune indexes
Enable Performance Insights
Job Scenario
CPU spikes during peak hours → root cause analysis.

Module 6: Security & Compliance (4 Hours)Module 6: Security & Compliance (4 Hours)

Topics
Encryption at rest & in transit
KMS integration
Network isolation
Audit logging
Compliance basics (PCI, SOC)
Lab
Enable encryption
Configure logging
Restrict access via IAM

Module 7: Migration & Automation (4–5 Hours)

Topics
DMS (Database Migration Service)
Schema Conversion Tool (SCT)
Blue-Green deployments
Terraform basics for Aurora
Zero-downtime migration
Lab
Migrate PostgreSQL to Aurora
Automate cluster creation
Job Scenario
On-prem DB migration with <5 min downtime.

Aurora PostgreSQL Capstone Project

Project: High-Availability Financial Application DB
Scope
Multi-AZ Aurora PostgreSQL
Read replicas for reporting
Automated backup & DR
Monitoring & alerts
Security hardening
Deliverables
Architecture diagram
Performance tuning report
DR & SOP documentation

PART 2: AWS DynamoDB (15–20 Hours)

PART 2: AWS DynamoDB (15–20 Hours)

Module 1: DynamoDB Fundamentals (3 Hours)

Topics
NoSQL concepts
Key-value & document model
DynamoDB architecture
Partition keys & sort keys
Lab
Create DynamoDB table
Insert and query data
Job Scenario
Replace RDBMS for high-scale workload.

Module 2: Data Modeling & Access Patterns (4 Hours)

Topics
Single-table design
Access pattern driven design
GSIs & LSIs
Sparse indexes
Lab
Design e-commerce schema
Implement GSIs
Assignment
Data model for ride-sharing app

Module 3: Capacity & Performance Management (3 Hours)

Topics
On-Demand vs Provisioned
Auto scaling
Hot partitions
Adaptive capacity
Lab
Configure auto scaling
Stress test partitions
Job Scenario
Throttling errors in production → fix design.

Module 4: Security, Backup & Global Tables (3 Hours)

Topics
IAM policies
Encryption with KMS
Backup & restore
Global tables (multi-region)
Lab
Enable PITR
Setup global tables

Module 5: DynamoDB Streams & Integrations (3 Hours)

Topics
Streams
Lambda triggers
Event-driven architecture
TTL (Time to Live)
Lab
Trigger Lambda from stream
Implement TTL cleanup

Module 6: Monitoring, Cost & Optimization (2–3 Hours)

Topics
CloudWatch metrics
Cost optimization strategies
Query vs Scan
Reserved capacity
Job Scenario
DynamoDB cost spike → optimize.

DynamoDB Mini Project

Project: Serverless Order Management System
Scope
DynamoDB single-table design
Lambda integration
Auto scaling
Global replication
Deliverables
Table design document
Cost optimization report

Job-Oriented Scenario Mapping

Role Responsibilities
L1 Connectivity, monitoring, access issues
L2 Performance tuning, scaling, backups
L3 Architecture, migration, optimization

Final Outcome

After this training, learners can:
✅ Design & operate Aurora PostgreSQL at scale
✅ Build high-performance DynamoDB applications
✅ Handle production incidents & migrations
✅ Work in Cloud / DevOps / Database Engineer roles

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Aws Aurora (postgresql Compatible) & Dynamo Db Course Certification With Training In Bangalore

Q: Module 1: AWS Database Fundamentals & RDS Overview (3 Hours)

Topics OLTP vs OLAP databases RDS vs Aurora vs Self-managed PostgreSQL Aurora architecture overview Shared storage, 6-way replication Regional vs Global databases Lab Create PostgreSQL RDS Compare with Aurora PostgreSQL Job Scenario Choose Aurora vs RDS PostgreSQL for a high-availability application.

Q: Module 2: Aurora PostgreSQL Architecture Deep Dive (5 Hours)

Topics Compute & Storage separation Aurora storage engine Read replicas & writer endpoint Failover & recovery Serverless v2 overview Lab Create Aurora PostgreSQL cluster Configure reader endpoints Simulate failover Assignment Architecture diagram & justification document

Q: Module 3: Aurora PostgreSQL Setup & Configuration (5 Hours)

Topics Parameter groups Option groups Subnet groups Security groups & IAM authentication TLS/SSL connections Lab Tune PostgreSQL parameters Enable IAM authentication Secure cluster with VPC rules Job Scenario Application connection timeout after migration → troubleshoot.

Q: Module 4: Backup, Restore & Disaster Recovery (4 Hours)

Topics Automated backups Manual snapshots Point-in-Time Recovery (PITR) Cross-region snapshots Global Aurora Lab Restore cluster from snapshot Test PITR recovery Assignment DR strategy for a fintech workload

Q: Module 5: Performance Tuning & Monitoring (5 Hours)

Topics Performance Insights CloudWatch metrics Query execution plans Indexing strategies Connection pooling (PgBouncer) Lab Identify slow queries Tune indexes Enable Performance Insights Job Scenario CPU spikes during peak hours → root cause analysis.

Q: Module 6: Security & Compliance (4 Hours)Module 6: Security & Compliance (4 Hours)

Topics Encryption at rest & in transit KMS integration Network isolation Audit logging Compliance basics (PCI, SOC) Lab Enable encryption Configure logging Restrict access via IAM

Q: Module 7: Migration & Automation (4–5 Hours)

Topics DMS (Database Migration Service) Schema Conversion Tool (SCT) Blue-Green deployments Terraform basics for Aurora Zero-downtime migration Lab Migrate PostgreSQL to Aurora Automate cluster creation Job Scenario On-prem DB migration with <5 min downtime.

Q: Aurora PostgreSQL Capstone Project

Project: High-Availability Financial Application DB Scope Multi-AZ Aurora PostgreSQL Read replicas for reporting Automated backup & DR Monitoring & alerts Security hardening Deliverables Architecture diagram Performance tuning report DR & SOP documentation

Q: PART 2: AWS DynamoDB (15–20 Hours)

PART 2: AWS DynamoDB (15–20 Hours)

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