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Building High-Throughput Data Microservices

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Microservices come with all kinds of great benefits. But they can be extremely difficult to manage well at scale. As organizations face the challenge of processing increasingly large volumes of data, they need to be able to build and maintain high-throughput data microservices. In this course, instructor Gregory Green covers the fundamental skills you need to know to meet today’s growing data demands with high-performance, scalable, high-throughput architectures.

Discover best practices for data patterns for throughput with flexible data services and multisite cloud-based use cases. Explore some of the most critical factors that affect high-throughput requirements, before diving deeper into antipatterns and the pros and cons of data technologies. Along the way, Gregory provides examples with RabbitMQ, Postgres, MySQL, Spring, and Apache Kafka, offering tips and pointers with hands-on demonstrations of how to design and implement successful, high-throughput data microservices.


01 - Introduction
  • 01 - Improve your microservices
  • 02 - What you should know

  • 02 - 1. Introduction to High Throughput Data Microservices
  • 01 - Microservices overview
  • 02 - What are cloud-native data services
  • 03 - Overview of throughput
  • 04 - Why is high throughput with microservices important
  • 05 - Throughput architectural data patterns
  • 06 - High throughput scalability

  • 03 - 2. High Throughput Architecture
  • 01 - High throughput data architectures using Spring
  • 02 - Database throughput with Postgres or MySQL
  • 03 - Batch architecture throughput
  • 04 - Event streaming throughput
  • 05 - RabbitMQ streams for high throughput
  • 06 - Apache Kafka for high throughput

  • 04 - 3. Spring Throughput Overview
  • 01 - Microservices with Spring Boot
  • 02 - Batching throughput with Spring Batch
  • 03 - Event streaming throughput with Spring Cloud Stream
  • 04 - API throughput with Spring Web

  • 05 - 4. Batching Throughput Implementation
  • 01 - Spring Batch with Postgres throughput tuning
  • 02 - Spring Batch with MySQL throughput tuning
  • 03 - Spring Batch with Apache Kafka throughput tuning
  • 04 - Spring Batch with RabbitMQ streams throughput tuning

  • 06 - 5. Event Streaming and API Throughput
  • 01 - Event streaming and API throughput architecture with Spring Boot
  • 02 - Spring Cloud Stream Consumer with RabbitMQ streams and Postgres
  • 03 - API with Spring Boot RabbitMQ streams publisher
  • 04 - Spring Web Event streaming performance and observability

  • 07 - Conclusion
  • 01 - Continue your journey
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