Azure Networking Fall 2018 update
As enterprises move ever more demanding mission-critical workloads to the cloud, we strive to provide comprehensive networking services that are easy to deploy, manage, scale, and monitor.
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Azure Cosmos DB – database for Intelligent Cloud – Intelligent Edge era
Azure Cosmos DB is Microsoft’s globally distributed, multi-model database service for mission-critical workloads. -
Azure.Source – Volume 50
Keep current on what’s happening in Azure, including what’s now in preview, generally available, news & updates, and more. -
Getting AI/ML and DevOps working better together
Artificial Intelligence (AI) and machine learning (ML) technologies extend the capabilities of software applications that are now found throughout our daily life: digital assistants, facial recognition, photo captioning, banking services, and product recommendations. -
Jenkins Azure ACR Build plugin now in public preview
We are excited to announce the preview of ACR Build plugin for Jenkins so that you can build your Docker image in Azure Container Registry(ACR. -
Azure.Source – Volume 49
Keep current on what’s happening in Azure, including what’s now in preview, generally available, news & updates, and more. -
GPUs vs CPUs for deployment of deep learning models
Choosing the right type of hardware for deep learning tasks is a widely discussed topic. -
Helping Go developers build better cloud apps faster
As GopherCon kicks off today with nearly 2,000 gophers gathering in Denver, we’re excited to share our latest offerings and announcements for Go developers. -
Microsoft Azure Data welcomes attendees to VLDB 2018
Hello VLDB attendees! Welcome to Rio De Janeiro. -
Speech Services August 2018 update
We are pleased to announce the release of another update to the Cognitive Services Speech SDK (version 0. -
Azure Block Blob Storage Backup
Azure Blob storage is Microsoft’s object storage solution for the cloud. -
Azure #HDInsight Interactive Query: simplifying big data analytics architecture
Fast Interactive BI, data security and end user adoption are three critical challenges for successful big data analytics implementations.
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