With Azure IoT Edge Provider for Virtual Kubelet, you can deploy and configure a variety of modules on multiple IoT devices using your familiar Kubernetes tools, utilities, and reusable configurations (yaml).
Run Hyperledger Fabric on Azure Kubernetes Service (Tutorial)
By using “Hyperledger Fabric on Azure Kubernetes Service” (HLF on AKS) template in Azure, you can soon start Hyperledger Fabric without spending time building out the infrastructure.
In this post, I show you both architecture and usage (how to use) for this template.
Build Quorum Application with Azure Blockchain Service
In this post, I show you how to build blockchain applications working with Quorum ledger, by using Azure Blockchain Service, with ease of provision and configuration for beginners.
Building Azure IoT Edge Module with Message Routing
In this post, we build and deploy custom modules from scratch (without Visual Studio Code) with message routing. If you are new to Azure IoT, you will find how Azure IoT Edge module works and how to build it through this post.
Optimized Read-Throughput by Azure Cosmos DB Spark Connector
In this post, we see how it efficiently works behind Azure Cosmos DB Spark Connector (azure-cosmosdb-spark). By knowing the mechanism of connector, please optimize the read throughput with Apache Spark and Cosmos DB.
Run benchmark for Apache Hive LLAP on Microsoft Azure
In this post, I show you benchmarks for Apache Hive LLAP on Azure HDInsight. You can quickly start and see how LLAP is different with regular Hive (container on Tez) using managed service cluster.
Spark ML Serving with Azure Machine Learning
Using Azure Machine Learning service, you can train the model on the Spark-based distributed platform (Azure Databricks) and serve your trained model (pipeline) on Azure Container Instance (ACI) or Azure Kubernetes Service (AKS).
In this post, I show you this step and background using AML Python SDK.
MXNet Distributed Training with Azure ML (Custom Configuration Sample)
In this post, I proceed to more advanced topics by showing you how to set up (customize) your Azure Machine Learning Compute (AmlCompute) for the practical training. In the last part of this post, I’ll show you Apache MXNet distributed training example with Azure Machine Learning service.
Azure Machine Learning : Walkthrough of Key Features
In this post, I’ll show you how Azure ML helps your ML/AI workloads with overall features and code examples.
First look at Azure Dev Spaces – Collaborate in shared AKS cluster
With Azure Dev Spaces, you can build and debug microservices in Kubernetes cluster without installing entire system in your local desktop.
In this post I introduce Azure Dev Spaces using command line, and see how it works.
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