What’s the point: Rook checks out v1.0, Red Hat beta’s odo, Datadog Hyper-V, Serverless Framework Enterprise

What's the point

Rook, an open source source cloud native Kubernetes orchestrator, has hit v1.0. Highlights of the latest version include support for Ceph Nautilus, while support for EdgeFS is now in beta. It also adds support for OpenStack Swift as well as a new iSCSI block storage CSI driver, while the project gets a new management GUI, and Prometheus support.  The project was first launched in 2016, hitting 0.9 late last year. The project was accepted into the CNCF incubator last year.

Red Hat does do odo beta

Red Hat has announced the first beta of odo, its source source CLI for “developers who write, build and iterate constantly on their source code”. As Red Hat puts it, odo – which stands for OpenShift Do and is hosted on the OpenShift GitHub repository – concentrates on the iterative inner loop cycle of coding, on code changes prior to committing to Git. The aim is to allow developers to focus on source code, rather than fretting about deployment scenarios. The tool supports multiple languages and frameworks including Node.js, Java, Ruby, Perl, PHP and Python. It promises to detect changes to local source , and push it to the cluster accordingly.

Datadog sees into Hyper-V

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Datadog has announced an integration for Microsoft’s Hyper-V virtualisation platform, which it promises will monitor the health of every layer of the Hyper-V stack, from physical hosts, up through virtual machines, and up to the applications and services they run. Standard features include alerts when available memory is too low as well as CPU utilisation monitoring. Datadog’s existing Windows integrations include IIS, SQL Server and Microsoft Azure.

Serverless serves up error features in Framework Enterprise

Serverless Inc has released v0.9.0 of its Serverless Framework Enterprise, which focuses on making error troubleshooting easier. Updates include a new error type alert on the dashboard, along with error metrics to track errors over time. Users can navigate from the error alert or error metrics views to view the stack trace of the service when the error occurred, and source maps can be uploaded to tools like Wedpack or Typescript.

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