Basic Understanding

ChRIS.md

Basic Understanding

Distributed apps are applications or software that runs on multiple computers within a network at the same time and can be stored on server or with cloud computing. Unlike traditional applications, distributed applications run on multiple systems simulataneously for a single task or a job.

The client software accesses the data from the server or cloud environment, while the server or cloud processes the data. ChRIS is designed to manage the execution of data needs of a specific class of computational applications often used in Research. These are applications that require no user interface once started, have runtime specifications passed in command line arguments and collect all output in files.

While ChRIS itself has a web based user interface, the applications that perform the computations are containerized, Linux based applications. Linux containers are technologies that allow you to package and isolate application with their entire run time environment- all of the files necessary to run. This makes it easy to move the contained application between environments while retaining full functionality.

Why ChRIS?

1. Data Sharing: Within in the ChRIS framework, data is managed and shared using services such as Swift/Ceph between various users of the system.

2. Data is protected.

3. Data is visualized

4. Algorithm/Program Sharing: ChRIS is built on the idea of using containerized components that perform the actual analysis and processing. This standardizes application development and deployment for reuse. The Front end of ChRIS provides a powerful real time collaboartion tool.

Deeper Dive into how ChRIS works.

To run medical image processing, a medical Researcher/ Programmer encodes the alogrithm that needs to be executed in the form of "plugin".

The researcher/programmer then makes the plugin available via the ChRIS store. An administration of a ChRIS installation then makes the plugin availble through their ChRIS installation.

Once registered, users of the ChRIS system can use a plugin within their image analysis pipeline. Once execution of a plugin starts, pfcon, running at BCH datacenter, sends the data via pfioh and the algorithm to be applied on the data to pman. Pman then translated the algorithm programmed in the plugin as Kubernetes job. To add scale to medical image processing, pman divides the job amongst several Kubernetes job pods that run in parallel.

OpenShift provides the container platform for seamless orchestration and resource management on the cluster.

Important parts.md

Axios

npm install axios

A basic example

axios.get('https://jsonplaceholder.typicode.com/posts').then(response=>{
console.log(response.data);
});