Eventual Consistency with Spring for Apache Kafka: Part 2 of 2
Using Spring for Apache Kafka to manage a Distributed Data Model in MongoDB across multiple microservices
As discussed in Part One of this post, given a modern distributed system composed of multiple microservices, each possessing a sub-set of a domain’s aggregate data, the system will almost assuredly have some data duplication. Given this duplication, how do we maintain data consistency? In this two-part post, we explore one possible solution to this challenge — Apache Kafka and the model of eventual consistency.
Part Two
In Part Two of this post, we will review how to deploy and run the storefront API components in a local development environment running on Kubernetes with Istio, using minikube. For simplicity’s sake, we will only run a single instance of each microservices. Additionally, we are not implementing custom domain names, TLS/HTTPS, authentication and authorization, API keys, or restricting access to any sensitive operational API endpoints or ports, all of which we would certainly do in an actual production environment.
To provide operational visibility, we will add Yahoo’s CMAK (Cluster Manager for Apache Kafka), Mongo Express, Kiali, Prometheus, and Grafana to our system.
