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Microsoft Announces Open Source Dapr

Dapr is an open source, portable, event-driven runtime that makes it easy for developers to build resilient, microservice stateless and stateful applications that run on the cloud and edge.

Red Hat OpenShift 4.2 Delivers New Developer Client Tools

Red Hat has introduced the latest version of its enterprise Kubernetes platform.

SAP Embraces Serverless Computing Frameworks

SAP has begun to make available extensions to its cloud platform that enable customers to leverage a framework running on top of Kubernetes to invoke serverless computing frameworks.

SIOS Offers SAP Certified High Availability And Disaster Recovery For SAP S/4HANA Environments In...

SIOS recently announced the latest releases of SIOS LifeKeeper 9.4 and SIOS DataKeeper 9.4, at the SAP TechEd event.

Why Linux Developers Should Reconsider IBM Mainframes

Why would Linux developers ditch the cloud or the omnipresent x86 platform and embrace Z?

Puppet’s New Cloud Native Continuous Delivery Tool Builds on the CDF’s Tekton

Puppet has released into public beta its Project Nebula, a cloud native tool that connects a DevOps team’s existing toolset into an end-to-end, continuous...

Trend Micro Partners With Snyk to Advance DevSecOps

Trend Micro today announced an alliance with Snyk through which alerts about vulnerabilities in open source code will be passed on to the tools...

Making the IoT More Open: A Common Framework for IoT Edge Computing with EdgeX...

The internet of things (IoT) is a diverse space, but it’s also fragmented by design, whether it’s consumer IoT or industrial IoT.

Open Source in VMware Tanzu

VMware today announced that the company is moving several of its key cloud native open source projects to a new GitHub organization.

Streamlit launches open source machine learning application development framework

Streamlit, a new machine learning startup from industry veterans, who worked at GoogleX and Zoox, launched today with a $6 million seed investment and a flexible new open source tool to make it easier for machine learning engineers to create custom applications to interact with the data in their models.