AI Blog

Iguazio Product Update: Optimize Your ML Workload Costs with AWS EC2 Spot Instances

August 30, 2022

Iguazio users can now run their ML workloads on AWS EC2 Spot instances. When running ML functions, you might want to control whether to run on Spot nodes or On-Demand compute instances.When deploying Iguazio MLOps platform on AWS, running a job (e.g. model training) or deploying a serving function users are now able to choose to deploy it...

MLOps MLRun

From AutoML to AutoMLOps: Automated Logging & Tracking of ML

August 23, 2022

AutoMLOps means automating engineering tasks so that your code is automatically ready for production. Here we outline the challenges and share open-source tools.

MLOps MLRun

How to Deploy an MLRun Project in a CI/CD Process with Jenkins Pipeline

August 10, 2022

In this article, we will walk you through steps to run a Jenkins server in docker and deploy the MLRun project using Jenkins pipeline.

Industry ML MLOps

Beyond Hyped: Iguazio Named in 8 Gartner Hype Cycles for 2022

August 2, 2022

We’re proud to share that Iguazio has been named a sample vendor in eight Gartner Hype Cycles for 2022.

MLOps MLRun

Build an AI App in Under 20 Minutes

July 19, 2022

Here's how to build simple AI applications that leverage pre-built ML models and allow you to interact with a UI to visualize the results.

Data science MLOps MLRun

Machine Learning Experiment Tracking from Zero to Hero in 2 Lines of Code

June 21, 2022

Here's how to turn your existing model training code into an MLRun job and get the benefit of all the experiment tracking, plus more.

MLRun v1.7 Launched — Solidifying Generative AI Implementation and LLM Monitoring

Iguazio Product Update: Optimize Your ML Workload Costs with AWS EC2 Spot Instances

From AutoML to AutoMLOps: Automated Logging & Tracking of ML

How to Deploy an MLRun Project in a CI/CD Process with Jenkins Pipeline

Beyond Hyped: Iguazio Named in 8 Gartner Hype Cycles for 2022

Build an AI App in Under 20 Minutes

Machine Learning Experiment Tracking from Zero to Hero in 2 Lines of Code

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