3. Useful Links
Automating Jupyter Notebook Deployments to Kubeflow Pipelines with Kale
Production-Ready Notebooks for End-to-End ML Workflows With Kubeflow
Build An End-to-End ML Workflow: From Notebook to HP Tuning to Kubeflow Pipelines with Kale
How can I add Actions to the tool-bar in the Dashboard of Jupyter Notebook?
Defining and registering your own actions
Productionizing Machine Learning with a Microservices Architecture
Tutorial: From Notebook to Kubeflow Pipelines to KFServing: the Data Science... - Karl Weinmeister
From Notebook to Kubeflow Pipelines: The Titanic example on MiniKF using Kale and Rok
You can access all the papers in pdf format here
Open Source Software in Industry
The future of research in free/open-source software development
Why do commercial companies contribute to open source software?
How Open Source Tools Can Benefit Industry
Why Open Source software can succeed
Making machine learning models interpretable
Machine Learning Algorithms - A Review
A Brief Review of Machine Learning and its Application
Machine Learning from Theory to Algorithms: An Overview
Machine learning methods: An overview
Microservices: The Journey So Far and Challenges Ahead
The Design and Architecture of Microservices
Challenges in Delivering Software in the Cloud as Microservices
From Monolithic Systems to Microservices: A Comparative Study of Performance
Microservices in Industry: Insights into Technologies, Characteristics, and Software Quality
The Pains and Gains of Microservices: A Systematic Grey Literature Review
Microservices Architecture based Cloudware Deployment Platform for Service Computing
Application deployment using Containers with Auto-scaling for Microservices in Cloud Environment
Design on Deployment of Microservices on Container-based Cloud Platform
Monitoring-aware Optimal Deployment for Applications based on Microservices
Efficient Resources Utilization by Different Microservices Deployment Models
Circuit Breakers, Discovery, and API Gateways in Microservices
Security Strategies for Microservices-based Application Systems
Microservices: Architecting for Continuous Delivery and DevOp
What is DevOps?: A Systematic Mapping Study on Definitions and Practices
A qualitative study of DevOps usage in practice
Microservices Architecture Enables DevOps: Migration to a Cloud-Native Architecture
A Data Quality-Driven View of MLOps
Who Needs MLOps: What Data Scientists Seek to Accomplish and How Can MLOps Help?
Sustainable MLOps: Trends and Challenges
MLOps Challenges in Multi-Organization Setup: Experiences from Two Real-World Case
