Description

Introduction
This training provides a comprehensive foundation for building modern full stack applications powered by scalable microservices, robust big data pipelines, and cloud platforms. Participants learn how to design cloud-native systems that handle large-scale data processing while supporting high-performance, resilient applications.

Prerequisites
Basic programming knowledge (Java, Python, or JavaScript)
Understanding of web application fundamentals
Basic knowledge of databases and SQL
Familiarity with cloud concepts and Linux is beneficial

Table of Contents

1. Full Stack Application Foundations
   1.1 Frontend frameworks and modern UI architecture
   1.2 Backend development with REST and APIs
   1.3 Authentication, authorization, and API security

2. Microservices Architecture
   2.1 Microservices concepts and design principles
   2.2 Service communication and API gateways
   2.3 Data management in microservices
   2.4 Resilience, fault tolerance, and scalability

3. Big Data Ecosystem and Data Pipelines
   3.1 Big data architecture and processing models
   3.2 Data ingestion using Kafka and messaging systems
   3.3 Batch processing with Hadoop and Spark
   3.4 Real-time and streaming data pipelines

4. Cloud Platforms for Data-Driven Applications
   4.1 Cloud service models and deployment strategies
   4.2 Big data services on AWS, Azure, and GCP
   4.3 Cloud storage, data lakes, and warehouses
   4.4 Designing multi-cloud and hybrid architectures

5. Containerization and Orchestration
   5.1 Docker for microservices packaging
   5.2 Kubernetes fundamentals and deployment models
   5.3 Scaling microservices and data workloads
   5.4 Configuration and secrets management

6. Data Pipeline Management and Optimization
   6.1 Workflow orchestration and scheduling
   6.2 Data quality, validation, and governance basics
   6.3 Performance tuning for big data pipelines
   6.4 Cost optimization strategies on cloud

7. Monitoring, Security, and Reliability
   7.1 Observability for microservices and data systems
   7.2 Logging, tracing, and metrics on cloud
   7.3 Security best practices for applications and data
   7.4 High availability and disaster recovery

8. Capstone Project
   8.1 Designing a cloud-native full stack big data solution
   8.2 Building microservices and data pipelines
   8.3 Deploying and operating the solution on cloud

This training equips learners with practical skills to build, deploy, and manage full stack big data solutions using microservices and cloud platforms. It prepares participants for real-world roles requiring scalable architectures, efficient data pipelines, and cloud-native engineering expertise.