Detect and react intelligently to changes in data with Drasi
This introductory post will focus on the core concepts of Drasi, and its major components such as Sources.
Tag: Microsoft Azure
Microsoft at Open Source Summit Europe 2024: Driving collaboration and innovation
Connect with other open source enthusiasts at Open Source Summit Europe 2024 in Vienna, Austria.
Join Microsoft at Open Source Summit North America 2024
Join Microsoft at Open Source Summit North America 2024, taking place in Seattle, Washington from April 16 to 18, 2024.
See how Azure is empowering cloud-native development and AI innovation with Kubernetes at KubeCon Europe 2024
Microsoft is excited to be able to support and contribute to the cloud-native and open-source communities at KubeCon Europe 2024.
Kubernetes at scale with GitOps and Cluster API
As the requirements and software surrounding Kubernetes clusters grow along with the required number of clusters, the administrative overhead becomes overwhelming and unsustainable without an appropriate architecture and supportive tooling.
Empowering you to achieve more with open source on Azure
At Microsoft, we are taking cloud architecture to the next level and our open cloud reduces the friction for developers to get applications up and running. We give autonomy and control to the developers to flexibly choose their infrastructure and give them options to build, migrate, and deploy across multiple environments on-premises, in the cloud, or at the edge. Our philosophy is to give developers the best technology as quickly as possible.
Introducing the Cluster API Provider for Azure (CAPZ) for Kubernetes cluster management
Managing Kubernetes clusters is hard. Managing Kubernetes clusters at scale across a variety of infrastructures is—well—even harder. The Kubernetes community project Cluster API (CAPI) enables users to manage fleets of clusters across multiple infrastructure providers.
.NET for Apache Spark hits v1.0
About two years ago, we heard an increasing demand from the .NET community for an easier way to build big data applications with .NET, outside of needing to learn Scala or Python. Thus, in a collaboration between Azure Data and .NET teams, we started the .NET for Apache® Spark™ open source project.
How to optimize Azure Machine Learning for IoT production usage
Introduction Over the last few years IoT devices, machine learning (ML), and artificial intelligence (AI) have become very popular and now a lot of companies are moving forward to use them in production. All cloud providers, including Microsoft Azure, provide services on how to deploy developed ML algorithms to edge devices.
How to deploy Elastic Cloud on Microsoft Azure
From startups to the global 2000, Elastic powers search solutions for thousands of companies worldwide to find documents, monitor infrastructure, protect against security threats, and more. With Elastic Cloud managed services on Azure, you have the power of Elastic Enterprise Search, Elastic Observability, and Elastic Security.
Announcing Dapr integration in Azure API Management Service
Dapr integration in the Azure API Management (APIM) service is now available. This new capability enables operations teams to directly expose Dapr microservices as APIs and make those APIs discoverable and easily consumable by developers with proper controls across multiple Dapr deployments—whether in the cloud, on-premises, or on the edge.
Announcing the Terraform AzureRM 2.0 Provider release
On behalf of HashiCorp and Microsoft, I am excited to announce the release of version 2.0 of the Azure Provider for Terraform. Version 2.0 is a major version upgrade that incorporates a number of features that customers have been asking for, as well as a whole host of smaller but impactful changes.
Data Accelerator for Apache Spark adds Azure Databricks support and more
Earlier this year, we released Data Accelerator for Apache Spark as open source to simplify working with streaming big data for business insight discovery. Data Accelerator is tailored to help you get started quickly, whether you’re new to big data, writing complex processing in SQL, or working with custom Scala or Azure functions.