Real-Time Streaming Architecture Virtual Internship
In this advanced virtual internship, students will learn to design and implement scalable, high-throughput architectures for real-time data processing using technologies like Apache Kafka, Amazon Kinesis, and Azure Event Hubs. They will gain hands-on experience in building robust, fault-tolerant systems that can handle large volumes of streaming data in real-time. By the end of the internship, students will have a strong understanding of modern real-time streaming architectures and the skills to build production-ready solutions.
Track Overview
Tasks & Milestones
Research Real-Time Streaming Architectures
AdvancedIn this task, students will research and compare the key characteristics, use cases, and design principles of real-time streaming architectures.
Design a Real-Time Data Pipeline
AdvancedIn this task, students will design a scalable, high-throughput data pipeline for real-time data processing using Apache Kafka, Amazon Kinesis, or Azure Event Hubs.
Implement a Real-Time Data Pipeline
AdvancedIn this task, students will implement the real-time data pipeline they designed in the previous module, including the integration of streaming technologies, data processing, and monitoring.
Optimize and Scale the Real-Time Data Pipeline
AdvancedIn this task, students will optimize and scale the real-time data pipeline they implemented in the previous module to handle increasing data volumes and ensure high availability and reliability.
Prerequisites
- • Familiarity with distributed systems concepts
- • Experience with at least one programming language (e.g., Java, Python, Scala)
- • Understanding of software architecture principles
Certificate
Certificate of Completion
Earn a certificate upon successful completion