A repository for notes on mlrun

• open-source MLOps framework
• abstraction layer to a variety of technology stacks

• Feature and Artifact Store
• Elastic Serverless Runtimes: Kubernetes/Nuclio/Dask/Spark/Horovod
• ML Pipeline Automation: data prep/modeling/real-time pipelines/monitoring
• Central Management: UI/CLI/SDK

• Speed of deployment
• Elastic scaling of batch and real-time jobs
• Feature management system
• Runs anywhere

• Project
• Function
• Run
• Artifact
• Workflow
• UI

• Safari not supported, used Chrome

Must do TWO THINGS before you run tutorial on hosted platform:

1. !/User/align_mlrun.sh
2. Restart Kernel

• Locally use Docker Desktop as described in Install MLRun on a Kubernetes Cluster

• Follow steps described.

• Install (Make sure you have the latest pip). Install on OS X will take several minutes and requires Rust and Cython.

• Create and source a python virtualenv: python3 -m venv ~/.mlrun-notes && source ~/.mlrun-notes/bin/activate pip install --upgrade pip && pip install mlrun

Can take 30+ minutes to install and contains many dependency errors.

• install latest Python and Rust): brew install python and brew install rust
• ModuleNotFoundError: No module named 'Cython'
• RuntimeError: cargo not found in PATH. Please install rust (https://www.rust-lang.org/tools/install) and try again
• clang: error: the clang compiler does not support 'faltivec', please use -maltivec and include altivec.h explicitly
• ERROR: Could not build wheels for maturin, which is required to install pyproject.toml-based projects

• Install only takes a couple of minutes to install

• Automated Code Deployment and Containerization-Example

(.mlrun-notes) ➜  functions git:(main) ✗ mlrun build function.yaml

> 2021-11-26 11:39:57,419 [info] remote deployment started
> 2021-11-26 11:39:57,419 [error] database connection is not configured
> 2021-11-26 11:39:57,419 [info] building image (.mlrun/func-default-remote-git-test-latest)
deploy error, local docker registry is not defined, set DEFAULT_DOCKER_REGISTRY/SECRET env vars

• Replace README.md with official docs link which is up to date and mentions Docker based workflows

• Hello World example in "one line"
• Target environment recommendation: Github Codespaces, AWS Cloudshell, etc
• Hello World using a pre-built Docker pull command
• Separate demos with foolproof "hello world" commands for each architectural component
• More clear link to official docs
• Point to a VM based solution: i.e AWS AMI, etc.

• mlrun
• Watch on Pragmatic AI Labs
• Watch on O'Reilly Media