The majority of monitoring and management solutions used in enterprises provide their customers with APIs (Application Programming Interfaces) and a CLI to facilitate DevOps type workflows. With IaC (Infrastructure as Code) becoming de facto and ubiquitous, decent APIs have long been a must have on product evaluation checklists; there are of course a few exceptions – namely products aimed only at SMB (Small and Medium Business), immature startups, or freeware.
March 31, London – Canonical today announced the general availability of OpenStack Yoga on Ubuntu 22.04 Long Term Support (LTS) Beta and Ubuntu 20.04 LTS. This new version of OpenStack sets a foundation for next-generation, highly performant infrastructure as needed by telco NFV, media streaming, traffic analysis and HPC services, using SmartNIC cards and integrating them with the Neutron Open Virtual Network (OVN) driver.
In this article, we will cover how you can combine some of the most powerful tools available to developers–VS Code and Git–to start making meaningful contributions to both open source and private projects. Before we get into driving Git with VS Code let’s start with some background.
As more and more organizations adopt cloud-native technologies, the need to align business objectives and end-user experience with IT infrastructure’s availability and performance is ever-growing. This trend requires infrastructure monitoring setups to ensure that all of your systems are active and working together across your cloud environments, host operating systems, storage systems, etc.
The DevOps and Platform Engineering space certainly is one that evolves fast. As new development paradigms get consumed, supporting the development pipeline is crucial. Pushing a public release of v0.2.x on March 30th, 2022, Dagger, from the creators of Docker, is another approach in portability and consistency in CI/CD pipelines. What the Docker Container has done applications, Dagger is hoping to achieve that with CI/CD pipelines.
Having multiple environments that can be dynamically configured has become akin to modern software development. This is especially true in an enterprise context where the software release cycles typically consist of separate compute environments like dev, stage and production. These environments are usually distinguished by data that drives the specific behavior of the application.
