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Here is a list of reasons why Python is repeatedly ranked among the top five programming languages by organizations like TIOBE and GitHub.
The open-source framework now allows developers to share their code among different drivers for use with a wide range of Windows devices.
The Portability Analyzer tool will help enterprises more easily migrate their applications to the new .NET Core 3.0 specifications.
AutoML Vision, AutoML Natural Language, and AutoML Translation are part of a Google effort to help developers more easily integrate AI capabilities in apps.
Universal Acceptance (UA) is the concept of removing all technical barriers that might hinder a user from accessing any name in any top-level domain (TLD) from any web browser, email client or other internet application on a connected device.
Java developers can now use Spring to more easily build distributed applications that take advantage of Google's cloud services, company says.
By using a fully-managed Confluent streaming data service on Google Cloud, users can offload the operating burden of Apache Kafka and stream data at scale in real time to Google Cloud’s big data services, which including BigQuery, Cloud Machine Learning Engine and TensorFlow.
Despite the availability of other options, native should remain the first choice for mobile development. Native apps are faster and more efficient, because they work in tandem with the mobile device for which they are developed.
DAILY VIDEO: IBM and Google give birth to the Knative serverless cloud project, and NIST is updating its recommendations for mobile app security.
NEWS ANALYSIS: Utility company partners and suppliers used as pathways to break into supposedly secure networks affecting hundreds of victims.
Knative has the potential to redefine how serverless computing can be used to build cloud architectures and expand the use of the serverless genre beyond mere functions.
Cloud-native application development is an approach to building and running an application that can take full advantage of the cloud computing model based on four key tenets: services for architecture, APIs for communication, containers for infrastructure and DevOps for process.