Distributed Scientific InfrastructureIn Production
License: Proprietary / Open AccessBrainlife.io Workflow Observability & Diagnostic Engine
Automated Pipeline Diagnostic & Performance Observability Platform for Distributed Scientific Workflows
Node.jsPythonReactELK StackREST APIsDockerHPC Cluster Integration
Core Research Ecosystem Vision
Building observability tools that monitor, diagnose, and auto-triage HPC neuroimaging pipeline errors across thousands of distributed compute executions on Brainlife.io.
Execution Commands & Pipeline Workflow
# 1. Train MONAI 3D DenseNet-121 Benchmark:
python src/models/cnn.py --model densenet121 --task task4 --epochs 50 --batch_size 4 --out_dir ./checkpoints/densenet
# 2. Evaluate Degradation Robustness & RRI Metrics:
python src/evaluation/metrics.py --evaluate_robustness --model_dir ./checkpoints/ --out_dir ./results/
# 3. Generate Grad-CAM Explainability Heatmaps under Perturbation:
python src/evaluation/explain.py --model_path ./checkpoints/densenet/best.pth --method gradcam --out_dir ./results/explanations/