mbrzus commented 4 months ago

Overview

This pull request introduces a Kubernetes-enabled version of our system, which has been adapted to run on Minikube locally. This adaptation aligns with modern deployment practices, aiming to enhance scalability and manageability.

Implementation

The system architecture mirrors our existing Docker setup with key components such as the frontend, backend, PostgreSQL database, internal Orthanc server, receiver, study handler, and the example product. Key changes and enhancements include:

Modular Design: The receiver and study handler have been restructured for better decoupling and to support horizontal scaling effectively.
Automated Kubernetes Job Management: Introduces dynamic creation of Kubernetes Jobs for processing studies and products, facilitating better resource management and scalability.
Configuration Management: Utilizes Kubernetes primitives like Deployments, Services, Ingresses, and Jobs extensively, alongside appropriate RBAC (Role-Based Access Control) settings to ensure secure and efficient operations.

Usage

The new Kubernetes functionality can be deployed and managed using Minikube. Detailed instructions and step-by-step guides are provided in the README_KUBES.md file, which includes:

Setup instructions for Minikube and necessary Kubernetes configurations. Deployment commands for all Kubernetes resources. Guidelines on how to scale components and handle dynamic job creation.

Testing

Extensive manual testing was conducted to ensure each component functions correctly within the Kubernetes environment. This includes testing data flow between components, job creation and execution, and the responsiveness of the system under different loads.

Problems Faced

Transitioning to a Kubernetes-based deployment presented several challenges:

Networking Issues: We encountered difficulties in managing network communications between pods and configuring external access via HTTP. These were addressed by refining our service and ingress configurations.
Learning Curve: Our team's initial unfamiliarity with Kubernetes required us to engage in comprehensive learning and experimentation, which slowed early progress but significantly built our internal expertise.

github-actions[bot] commented 4 months ago

Jest Coverage

Summary

Lines	Statements	Branches	Functions
	73.25% (515/703)	56.8% (96/169)	66.05% (144/218)

Junit Summary

Tests	Skipped	Failures	Errors	Time
37	0 :zzz:	0 :x:	0 :fire:	3.938s :stopwatch:

Coverage Report (72%)

File	% Stmts	% Branch	% Funcs	% Lines	Uncovered Line #s
All files	73.25	56.8	66.05	72.04
fixtures	100	100	100	100
hospitalFixture.tsx	100	100	100	100
kidneyStudyFixture.tsx	100	100	100	100
providerFixture.tsx	100	100	100	100
src/components	90.99	44.44	89.65	91.17
ErrorMessageBox.tsx	100	100	100	100
EventTimeline.tsx	71.42	0	0	75	79–83
Metadata.tsx	85.71	0	80	84.61	74–75
Navbar.tsx	90.47	50	100	90	150, 163
StackedChart.tsx	100	66.66	100	100	72–85
withAuthenticated.tsx	100	100	100	100
src/contexts	90	100	58.33	89.28
authContext.tsx	90	100	58.33	89.28	72, 90, 104
src/data	30.93	15.38	33.87	20
index.ts	30.93	15.38	33.87	20	17–27, 38–48, 59–69, 80–90, 98–108, 118–128, 140–149, 161–171, 181–190, 200–205, 217–240, 251–259, 269–274, 287–326, 335–345, 355–365, 370–380, 385–395, 411–412
src/hooks	100	100	100	100
useAuthContext.ts	100	100	100	100
src/pages	81.72	67.27	80.39	82.01
analytics.tsx	96.15	100	88.88	96	90
dashboard.tsx	100	100	100	100
index.tsx	100	100	100	100
login.tsx	83.87	88.88	85.71	83.33	52–57, 109
profile.tsx	77.5	61.53	80	80.55	59–61, 83–86
signup.tsx	71.62	55.55	66.66	71.23	89–91, 98–100, 116–140, 224–231, 270–287
src/pages/apikeys	73.21	54.54	64.28	71.69
index.tsx	73.21	54.54	64.28	71.69	74–77, 89, 94–99, 104–108, 195
src/pages/studies	79.56	57.14	74.35	81.74
[id].tsx	69.01	37.5	57.89	71.87	85, 94–108, 112–114, 125–126, 130, 134, 143, 219
index.tsx	90.9	71.87	90	91.93	49, 64, 141, 150, 157