Welcome to the Multiviz Integrator documentation!

MultiViz Integrator (MVI) is a software deployment tool that is perfect for smaller applications where Time-to-Market and ease of use is more important than scalability to tens of thousands of users and requests.

MVI strives to make writing and deploying services (small applications) as quick and easy as possible without requiring much, or any, prior knowledge and experience. We want Data Scientists and Algorithm Engineers to spend their time doing what they love and less time writing flask API:s and dockerfiles.

Viking Analytics AB

MultiViz Integrator is developed by Viking Analytics AB. Viking Analytics is a computer software and services company founded in 2017 and headquartered in Gothenburg, Sweden. Our vision is to enable our customers to unlock the potential in their data. For more information, head to our homepage https://vikinganalytics.se/. If you want to get in contact, you can reach us at info@vikinganalytics.se

Overview

• MultiViz Integrator

Getting Started

• Installation
• Deploying Your First Service
• Creating Your Own service
• Dashboard
• API Autodocs
• Versioning and Shadow Deployment
• Reaching a service from external applications
• Schedule Repeating Actions
• Monitoring Your Service
• Cross-service Communication
• Read Logs From Service

Advanced Tutorials

• Deploying Machine Learning Models
• Typing in the SDK
• Using Multiple Hosts
• Email Notifications
• Manager API
• Deployment Options
• Autocompletion
• Service Environment
• Manager Configuration
• Testing Services Before Deployment
• Proxy Dashboard
• Upload local docker image
• HTTP Status Codes
• Connecting MVI with Other Tools
• Going Beyond the SDK

Special Usecases

• Using Streamlit to build a dashboard
• Using Plotly Dash to build a dashboard
• Using MVI with Conda
• Access NVIDIA GPUs

Api Reference

• Command-line Interface
• Software Development Kit

About

• 3rd party software

Indices and tables

• Index

• Module Index

• Search Page