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.

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.

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.

Apache Spark is an open-source toolkit that helps users develop parallel, distributed data engineering and machine learning applications and run them at scale. In this webinar, Rob Gibbon – product manager, and Massimiliano Gori – senior information security lead, will survey the state of big data security best practices and outline both high level architectures and pragmatic steps that you can take to secure your Spark applications – wherever they may be running.

Canonical's Taiwan General Manager Tony Chiang was invited to join the Ampere event at Computex 2023 and had a great talk with Jeff Wittich, Chief Product Officer of Ampere Computing. Ampere and Canonical have been partnered to build sustainable and power-efficient computing solutions together and we can foresee more opportunities on the way from the cloud to the edge. Watch the video to learn more.

Apache Spark is an open source toolkit that helps users develop parallel, distributed data engineering and machine learning applications and run them at scale. In this webinar, Rob Gibbon – product manager, and Massimiliano Gori – senior information security lead, will survey the state of big data security best practices and outline both high level architectures and pragmatic steps that you can take to secure your Spark applications – wherever they may be running.

Open source is everywhere, but what’s its role in your company? According to Synopsys 2023 OSSRA research, around 96% of companies use open source in their codebases. From which at least 84% contained known vulnerabilities. Nowadays vulnerability exposure lasts for around 98 days, which means that the majority of companies are not fixing known vulnerabilities in their codebases for 3 months. This is simply not acceptable.