Fuel your development journey with cutting-edge tools and insights that cater specifically to the needs of developers, enhancing productivity and innovation.
Azure and Sylabs announced today a new collaboration which enables Singularity container images to be stored in registries supporting the Open Container Initiative (OCI) Distribution Specification. Singularity version 3.0 defines a new secure Singularity Image Format (SIF).
Today’s announcement of the Token Taxonomy Initiative (TTI) is a milestone in the maturity of the blockchain industry.
Grafana is one of the popular and leading open source tools for visualizing time series metrics.
Designed for developers and solution architects who need to understand how to move business critical apps to the cloud, this online workshop series gets you hands-on with a proven process for migrating an existing ASP.NET based application to a container based application.
The QnA Maker service lets you easily create and manage a knowledge base from your data, including FAQ pages, support URLs, PDFs, and doc files.
In a few weeks, over 22,000 people from around the globe will converge in Orlando, Florida from May 7-9, 2019 for the SAP Sapphire NOW and ASUG Annual Conference.
Today, we want to call attention to the exciting news that Azure SQL Data Warehouse has again outperformed other cloud providers in the most recent GigaOm benchmark report.
We all want the truth. To properly assess your cloud analytics provider, ask them about the only three things that matter: independent benchmark results, company-wide access to insights, and security & privacy.
A few months ago, we released a blog post that provided guidance on how to deploy Apache Airflow on Azure.
When it comes to executing a machine learning project in an organization, data scientists, project managers, and business leads need to work together to deploy the best models to meet specific business objectives.
DevOps is the union of people, processes, and products to enable the continuous delivery of value to end users. DevOps for machine learning is about bringing the lifecycle management of DevOps to Machine Learning.
In the world of manufacturing, the Industrial Internet of Things (IIoT) has come, and that means data. A loT of data. Smart machines, equipped with sensors, add to the large quantity of data already generated from quality systems, MES, ERP and other production systems.
