Let’s Make Docker Engine Connections Seamless
Overview
Purposed to Compliment the Docker Engine
The Anypoint Connector for Docker, built using Docker Java API client, is a communication tool that provides seamless integration with the Docker engine from a mule flow.
Connecter exposes Docker operations by executing API calls as per configuration.
It also supports HTTP and HTTPS connections and can be used as an inbound or as an outbound connector from the mule flow.
Connector Details
Latest Tech Specs – Highlighting Version & Compatibility
Connector Version – 1.0.0
Compatible with – Runtime 3.8.5 Version
Check it out
– Anypoint Exchange Listing
Published on
– 9th February 2018
More About Docker Connector
Exploring The Maximum Potential Of The Docker Container
The Docker connector functions within a Mule application. Using the connector, your application can perform several operations that Docker exposes via their APIs. When building an application that connects with Docker, such as an application which executes in docker container, you don’t have to go through the effort of custom-coding (and securing!) a connection. Rather, you can just drop a connector into your flow, configure a few connection details, then begin application running in Docker.
The real value of the Docker connector is in the way you use it at design-time in conjunction with other functional features available in Mule.
Exploring The Maximum Potential Of The Docker Container
DataSense
DataSense extracts metadata for Docker standard response to automatically determine the data type and format that your application must deliver to, or can expect from, Docker. Mule does the heavy lifting of discovering the type of data you must send to, or be prepared to receive from Docker.
Transform Message Component
This component’s integrated scripting language called DataWeave can automatically extract response metadata that you can use to visually map and/or transform to a different data format or structure. Essentially, DataWeave lets you control the mapping between data types. For example, if you configure a Docker connector in your application, then drop a Transform Message component after the connector, the component uses DataWeave to gather information that DataSense extracted to pre-populate the input values for mapping. In other words, DataSense makes sure that DataWeave knows the data format and structure it must work with so you don’t have to figure it out manually.
