MLFlow is an open source platform used for managing machine learning workflows. It is a crucial component of the open source MLOps ecosystem, having passed 10 million monthly downloads at the end of 2022. It has four main components that ensure experiment tracking, model registry, model deployment and code packaging. Join our webinar to learn more about MLFlow During this webinar, Andreea Munteanu will discuss MLFlow and Charmed MLFlow, Canonical’s distribution of the open source platform.

Big data and artificial intelligence (AI) go hand in hand. Used for tasks like trend prediction, process automation and research, these two technologies can help organisations solve some of the toughest problems. However, the growing volume of data and increasing diversity of data sources make it difficult to use data and AI effectively and at scale.

Learn how to maximize developer productivity by leveraging large language models for rapid code refactoring. Large language models like ChatGPT have tremendous potential to automate repetitive coding tasks and boost team effectiveness. In this MAAS Show And Tell, Peter Makowski, Senior Web Engineer at Canonical, shares insights and a real-world example of using LLM for a successful large-scale migration of hundreds of tests from enzyme to @testing-library/react.

In this video you will learn how to Install OpenStack in five simple steps. Looking for an easy OpenStack installation tutorial for beginners? Break the ice with OpenStack today by watching this video.

A MicroCloud is a new lightweight, featureful, and straightforward cloud for on-demand computing at the edge. MicroClouds differ from IoT which uses thousands of single machines or sensors to gather data, yet does not perform computing tasks. Instead, MicroClouds reuse proven cloud primitives with unattended, autonomous, and clustering features that resolve typical edge computing challenges.

In collaboration with Microsoft, Canonical introduces Ubuntu Pro update notifications into the Azure Update Management Center. This feature enables users to identify Ubuntu instances that aren't receiving all available security updates, including those delivered via Ubuntu Pro. Ubuntu Pro, a subscription by Canonical, provides enhanced security, maintenance, and compliance tools for organizations using Ubuntu on Azure.

With the rise of generative AI, enterprises are growing their AI budgets, looking for options to quickly set up the infrastructure and run the entire machine learning cycle. Cloud providers like AWS are often preferred to kick-start AI/ML projects as they offer the computing power to experiment without long-term commitments. Starting on the cloud takes away the burden of computing power, reducing start-up time and cost and allowing teams to iterate more quickly.

Ubuntu 18.04 LTS is out of standard support as of May 31, 2023. In order to easily receive security patches for your current running Ubuntu 18.04 Virtual Machines in Google Cloud, you can upgrade your Ubuntu 18.04 LTS to Ubuntu Pro by following this tutorial.

Learn the main differences between the MLOps tools of choice: Kubeflow and MLFlow Started by Google a couple of years ago, Kubeflow is an end-to-end MLOps platform for AI at scale. Canonical has its own distribution, Charmed Kubeflow, which addresses the entire machine-learning lifecycle. Charmed Kubeflow is a suite of tools, such as Notebooks for training, Pipeline for automation, Katib for hyperparameter tuning or KServe for model serving and more. Charmed Kubeflow benefits from a wide range of integrations with other tools such as MLFlow, Spark, Grafana or Prometheus.

Our own Devin Breen and Mark Lewis discussed Securing Open Source Software with the Chairman of Iron Bank at USAF Platform One Zachary Burke at AWS Summit Washington, DC. The topic includes: Securing Open Source Software, Secure Minimal Containers, and Software Security Scanning.