Right Technology, Framework or Tool to Build Microservices

Last week, I gave a talk at a German conference (Karlsruher Entwicklertag 2015) about Microservices. The following slide deck shows plenty of different technologies (e.g. REST, WebSockets), frameworks (e.g. Apache CXF, Apache Camel, Puppet, Docker) or tools (e.g. TIBCO BusinessWorks, API Exchange) to realize Microservices.

Abstract: How to Build Microservices

Microservices are the next step after SOA: Services implement a limited set of functions. Services are developed, deployed and scaled independently. This way you get shorter time to results and increased flexibility.

Microservices have to be independent regarding build, deployment, data management and business domains. A solid Microservices design requires single responsibility, loose coupling and a decentralized architecture. A Microservice can to be closed or open to partners and public via APIs.

This session discusses technologies such as REST, WebSockets, OSGi, Puppet, Docker, Cloud Foundry, and many more, which can be used to build and deploy Microservices. The main part shows different open service frameworks and tools to build Microservices on top of these technologies. Live demos illustrate the differences. The audience will learn how to choose the right alternative for building Microservices.

Key Messages: Integration, Real Time Event Correlation, TCO, Time-to-Market

I used three key messages within my talk to explain the complexity and variety of different Microservice concepts:

Integration is key for success of Microservices
Real time event correlation is the game changer
TCO and Time-to-Market are major aspects for tool selection

Slide Deck

Here is the slide deck, which I presented at Karlsruher Entwicklertag in Germany:

http://www.slideshare.net/KaiWaehner/how-to-choose-the-right-technology-framework-or-tool-to-build-microservices

Kai Waehner

bridging the gap between technical innovation and business value for real-time data streaming and applied AI.

Recent Posts

dbt Meets Apache Flink: One Workflow for Data Engineers on Snowflake, BigQuery, Databricks, and Confluent

Two toolchains, two skill sets, two CI/CD pipelines — that has been the reality for…

4 weeks ago

The Shift Left Architecture 2.0: Operational, Analytical and AI Interfaces for Real-Time Data Products

The Shift Left Architecture moves data integration logic into an event-driven architecture where governed data…

4 weeks ago

UFC VIP Experience Worth the Price? Fan Review. Business Perspective. Tech Vision.

The Ultimate Fighting Championship (UFC) held Fight Night London on March 21, 2026, at The…

4 weeks ago

Dashboards and Queries for Apache Kafka: Operational, Explorative, and the Role of the Context Engine

Dashboards are a popular way to make streaming data visible and useful, but they are…

1 month ago

Data Streaming at MWC 2026: How Apache Kafka, Flink and Agentic AI Power Telecom Trends

Mobile World Congress (MWC) 2026 highlights the shift from batch systems to real time data…

2 months ago

From Takeoff to Touchdown: Real-Time Aviation with Data Streaming at Qantas

This blog post explores how data streaming transforms airline operations by enabling real-time visibility, faster…

2 months ago