Cloud Native Middleware Microservices – 10 Lessons Learned (O’Reilly Software Architecture 2017, New York)

I want to share my slide deck and video recordings from the talk “10 Lessons Learned from Building Cloud Native Middleware Microservices” at O’Reilly Software Architecture April 2017 in New York, USA in April 2017.

Abstract
Microservices are the next step after SOA: Services implement a limited set of functions; services are developed, deployed, and scaled independently; continuous delivery automates deployments. This way you get shorter time to results and increased flexibility. Containers improve things even more, offering a very lightweight and flexible deployment option.

In the middleware world, you use concepts and tools such as an enterprise service bus (ESB), complex event processing (CEP), business process management (BPM), or API gateways. Many people still think about complex, heavyweight central brokers. However, microservices and containers are not only relevant for custom self-developed applications but are also a key requirement to make the middleware world more flexible, Agile, and automated.

Kai Wähner shares 10 lessons learned from building cloud-native microservices in the middleware world, including the concepts behind cloud native, choosing the right cloud platform, and when not to build microservices at all, and leads a live demo showing how to apply these lessons to real-world projects by leveraging Docker, CloudFoundry, and Kubernetes to realize cloud-native middleware microservices.

Slide Deck

Here is the slide deck “10 Lessons Learned from Building Cloud Native Middleware Microservices“:

Click on the button to load the content from www.slideshare.net.

Load content

Video Recordings / Live Demos

Two video recordings which demo how to apply the discussed lessons learned with middleware and open source frameworks:

Kai Waehner

builds cloud-native event streaming infrastructures for real-time data processing and analytics

Recent Posts

A New Era in Dynamic Pricing: Real-Time Data Streaming with Apache Kafka and Flink

In the age of digitization, the concept of pricing is no longer fixed or manual.…

3 days ago

IoT and Data Streaming with Kafka for a Tolling Traffic System with Dynamic Pricing

In the rapidly evolving landscape of intelligent traffic systems, innovative software provides real-time processing capabilities,…

2 weeks ago

Fraud Prevention in Under 60 Seconds with Apache Kafka: How A Bank in Thailand is Leading the Charge

In the fast-paced world of finance, the ability to prevent fraud in real-time is not…

3 weeks ago

When to Choose Apache Kafka vs. Azure Event Hubs vs. Confluent Cloud for a Microsoft Fabric Lakehouse

Choosing between Apache Kafka, Azure Event Hubs, and Confluent Cloud for data streaming is critical…

4 weeks ago

How Microsoft Fabric Lakehouse Complements Data Streaming (Apache Kafka, Flink, et al.)

In today's data-driven world, understanding data at rest versus data in motion is crucial for…

1 month ago

What is Microsoft Fabric for Azure Cloud (Beyond the Buzz) and how it Competes with Snowflake and Databricks

If you ask your favorite large language model, Microsoft Fabric appears to be the ultimate…

1 month ago