Azure solution architectures

Architectures to help you design and implement secure, highly available, high-performance, resilient solutions on Azure.

Energy Supply OptimisationIn an energy grid, energy consumers are engaged with various types of energy supplying, trading and storage components such as substations, batteries, windfarms and solar panels, micro-turbines, as well as demand response bids, to meet their respective demands and minimise the cost of energy commitment. To do so, the grid operator must determine how much energy each type of the resources should commit over a time frame, given the prices of soliciting different types of resources and the capacities and the physical characteristics of them.

Energy Supply Optimization

In an energy grid, energy consumers are engaged with various types of energy supplying, trading, and storage components such as substations, batteries, windfarms and solar panels, micro-turbines, as well as demand response bids, to meet their respective demands and minimize the cost of energy commitment. To do so, the grid operator must determine how much energy each type of the resources should commit over a time frame, given the prices of soliciting different types of resources and the capacities and the physical characteristics of them.

Learn more
Big compute with Azure BatchBig compute and high performance computing (HPC) workloads are normally compute intensive and can be run in parallel, taking advantage of the scale and flexibility of the cloud. The workloads are often run asynchronously using batch processing, with compute resources required to run the work and job scheduling required to specify the work. Examples of Big Compute and HPC workloads include financial risk Monte Carlo simulations, image rendering, media transcoding, file processing and engineering or scientific simulations.123456

Big compute with Azure Batch

Big compute and high performance computing (HPC) workloads are normally compute intensive and can be run in parallel, taking advantage of the scale and flexibility of the cloud. The workloads are often run asynchronously using batch processing, with compute resources required to run the work and job scheduling required to specify the work. Examples of Big Compute and HPC workloads include financial risk Monte Carlo simulations, image rendering, media transcoding, file processing, and engineering or scientific simulations.

Learn more
Build high availability into your BCDR strategyVirtual machines (VMs) are physically separated across zones, and a virtual network is created using load balancers at each site. These locations are close enough for high availability replication, so your applications stay running, despite any issues at the physical locations.1234567

Build high availability into your BCDR strategy

Virtual machines (VMs) are physically separated across zones, and a virtual network is created using load balancers at each site. These locations are close enough for high availability replication, so your applications stay running, despite any issues at the physical locations.

Learn more
Campaign Optimisation with Azure HDInsight Spark ClustersThis solution demonstrates how to build and deploy a machine learning model with Microsoft R Server on Azure HDInsight Spark clusters to recommend actions to maximise the purchase rate of leads targeted by a campaign. This solution enables efficient handling of big data on Spark with Microsoft R Server.

Campaign Optimization with Azure HDInsight Spark Clusters

This solution demonstrates how to build and deploy a machine learning model with Microsoft R Server on Azure HDInsight Spark clusters to recommend actions to maximize the purchase rate of leads targeted by a campaign. This solution enables efficient handling of big data on Spark with Microsoft R Server.

Learn more