Docker For Java Developer : Deploying Multiple Spring Boot Microservices to Docker using Docker Networking
Inter Docker Container Communication Using Docker Networking
As the name suggests employee-producer will be exposing REST APIs which will be consumed by the employee-consumer.
The way Docker has been designed such that a Docker Container should have only a single service running.
Again we can have multiple services running in docker using some workarounds but this will not be a good design.
So we will be deploying the two microservices employee-producer and employee-consumer to two different containers and then have them interact with each other.
We have created and started a container named producer where we have deployed the employee-producer service.
So the only change we will be making is while consuming the employee producer service we will be using this container named producer instead of localhost:8080.
So in the ConsumerControllerClient class we will be having the base url as producer:8080/employee instead of localhost:8080/employee.
We will start with the container terminologies used throughout the article:
Container image: a file with a specific format. We convert our application into a container image by running a build tool.
Container: the runtime instance of a container image.
Container engine: the daemon process responsible for running the Container.
Container host: the host machine on which the container engine runs.
Container registry: the shared location that is used for publishing and distributing the container image.
OCI Standard: the Open Container Initiative (OCI) is a lightweight, open governance structure formed under the Linux Foundation.
The OCI Image Specification defines industry standards for container image formats and runtimes to ensure that all container engines can run container images produced by any build tool.
The good news is that you can save a lot of time when starting out experimenting with a new technology, because you can use an image prepared by someone else, without understanding the details immediately. Once you are up for some more complex stuff you can start adding to the knowledge that you can extract and learn from other people’s Dockerfiles.
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