Break point: Visual Studio previews, Puppet moves, Amazon trains, and Tecton feasts

Break point: Visual Studio previews, Puppet moves, Amazon trains, and Tecton feasts

Microsoft has opened Visual Studio v16.10 preview 2 to the world and its dog. This pre-release version adds a number of new features, including C++20 ranges implementation, support for CMake preset files, and improved security for remote connections. The latter has been achieved by adding a prompt to accept or deny the host key fingerprint presented by the server, similar to OpenSSH client or PuTTY.

Redmond has also added customised warning levels for external headers. This allows developers to set stricter settings for their project’s code to enforce code quality without getting bogged down with warnings from headers beyond their control. EditorConfig also now has a user interface. The new UI will automatically open and display code style and code quality configuration options for both C# and Visual Basic. Full details of the changes can be found on the Microsoft blog.

Puppet enhances vulnerability remediation

Puppet has released Remediate 2.0, the latest version of its vulnerability management tool. This release delivers more clarity in how users can consume data from Tenable.io and Qualys, as well augment existing data with additional metadata. Full details are available in the release notes.

Users are now able to tag nodes within Puppet Remediate in order to group them in a way that makes sense to the user’s operations, differentiating production servers from staging servers to address vulnerabilities where they are the most critical, according to Puppet.

Remediate also now gives user organisations the ability to import tags that have already been created in their Qualys or Tenable.io vulnerability scanners. Tags that are imported this way are immutable, but they will get updated every time data is ingested by Remediate.

Amazon offers developer events and training

Amazon is offering a series of events about modern application development that will be live-streaming on Twitch in May. Modern Apps Live is a series of four virtual events covering serverless, containers, and mobile and front-end development. Amazon says these are for any developer, solutions architect, or IT and DevOps professional who wants to build and design modern applications.

Amazon is also offering free ML training for business and technical leaders. The series of three free digital courses are designed to help business and technical decision makers lacking machine learning experience to understand ML basics and develop the skills to plan an ML strategy for their organisation.

Jenkins Operator brought into the Jenkins fold

Jenkins Operator has now been made an official sub-project of the open source automation platform. Jenkins Operator is a Kubernetes Native Operator that manages operations for Jenkins on Kubernetes deployments. It has been built with immutability and declarative configuration as code in mind.

The Jenkins team said that making it an official part of the Jenkins project was a major step towards better alignment with the overall Jenkins roadmap, and offered more opportunities to increase adoption of the Jenkins Operator project. Full details can be found on the Jenkins blog.

Tecton machine learning feature store is a Feast

Tecton has announced Feast 0.10, an open source feature store aimed at making it easier build, deploy, and use features for machine learning. This allows developers to build training datasets from their batch data, automates the process of loading and serving features in an online feature store, and ensures the user’s models have a consistent view of feature data once in production.

In a blog post announcing the store, Tecton said that its vision for Feast was to provide a feature store that a single data scientist could use to deploy a single ML project, but could also scale up for use by large platform teams. According to the firm, it is possible to deploy a production-ready feature store into a cloud environment in 30 seconds, and operate a feature store without Kubernetes, Spark, or self-managed infrastructure.