Continue reading Testing Apicurio Registry’s performance and scalability
JupyterLab is a flexible and powerful tool for working with Jupyter notebooks. Its interactive user interface (UI) lets you use terminals, text editors, file browsers, and other components alongside your Jupyter notebook. JupyterLab 3.0 was released in January 2021.
Continue reading Managing Python dependencies with the Thoth JupyterLab extension
Ansible is an engine and language for automating many different IT tasks, such as provisioning a physical device, creating a virtual machine, or configuring an application and its dependencies. Ansible organizes these tasks in playbook files, which run on one or more remote target hosts. Inventory files maintain lists of these hosts and are formatted as YAML or INI documents. For example, a simple inventory file in INI format follows:
Continue reading Write your own Red Hat Ansible Tower inventory plugin
Red Hat Decision Manager helps organizations introduce the benefits of artificial intelligence to their daily operations. It is based on Drools, a popular open source project known for its powerful rules engine.
Continue reading Knowledge meets machine learning for smarter decisions, Part 2
Drools is a popular open source project known for its powerful rules engine. Few users realize that it can also be a gateway to the amazing possibilities of artificial intelligence. This two-part article introduces you to using Red Hat Decision Manager and its Drools-based rules engine to combine machine learning predictions with deterministic reasoning. In Part 1, we’ll prepare our machine learning logic. In Part 2, you’ll learn how to use the machine learning model from a knowledge service.
Continue reading Knowledge meets machine learning for smarter decisions, Part 1
One of the first tools we developed to help us with Project Thoth was Kebechet, which we named for the goddess of freshness and purification. As we separated our software into more and more repositories (each of our Python modules is in its own repository on GitHub), we needed help with releasing new versions and keeping all dependent modules up-to-date. In a team of two and with more than 35 repositories, our process was a major time-burner.
Continue reading Use Kebechet machine learning to perform source code operations
Odo is a developer-focused command-line interface (CLI) for OpenShift and Kubernetes. This article introduces highlights of the odo 2.0 release, which now integrates with Kubernetes. Additional highlights include the new default deployment method in odo 2.0, which uses devfiles for rapid, iterative development. We’ve also moved Operator deployment out of experimental mode, so you can easily deploy Operator-backed services from the
odo command line.
Continue reading “Kubernetes integration and more in odo 2.0”
Red Hat CodeReady Dependency Analytics is a hosted service on OpenShift that provides vulnerability and compliance analysis for your applications, directly from your IDE. It automatically analyzes your software composition and provides recommendations to address security holes and licensing issues. The 0.1 release of CodeReady Dependency Analytics includes access to the Snyk Intel Vulnerability Database, which is a curated database of both unique and known open source software security advisories.
Continue reading Vulnerability analysis with Red Hat CodeReady Dependency Analytics and Snyk Intel
Since the first Red Hat OpenShift release in 2015, Red Hat has put out numerous releases based on Kubernetes. Five years later, Kubernetes is celebrating its sixth birthday, and last month, we announced the general availability of Red Hat OpenShift Container Platform 4.5. In this article, I offer a high-level view of the latest OpenShift release and its technology and feature updates based on Kubernetes 1.18.
Continue reading OpenShift 4.5: Bringing developers joy with Kubernetes 1.18 and so much more
The Python interpreter shipped with Red Hat Enterprise Linux (RHEL) 8 is version 3.6, which was released in 2016. While Red Hat is committed to supporting the Python 3.6 interpreter for the lifetime of Red Hat Enterprise Linux 8, it is becoming a bit old for some use cases.
Continue reading Red Hat Enterprise Linux 8.2 brings faster Python 3.8 run speeds