Azure solution architectures

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

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.

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Big Compute med Azure BatchArbejdsbelastninger i forbindelse med Big Compute og højtydende databehandling er normalt databehandlingskrævende og kan køres samtidigt, så cloudmiljøets skalerbarhed og fleksibilitet udnyttes. Arbejdsbelastningerne køres ofte asynkront vha. batchbehandling, mens databehandlingsressourcer er påkrævet for at udføre arbejdet, og jobplanlægning er påkrævet for at angive selve arbejdet. Eksempler på arbejdsbelastninger i forbindelse med Big Compute og højtydende databehandling inkluderer Monte Carlo-simuleringer med økonomisk risiko, billedgengivelse, medieomkodning, filbehandling og tekniske eller videnskabelige simuleringer.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.

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Arkitektur af chatrobot til ofte stillede spørgsmålQnA Maker-værktøjet gør det nemt for indholdsejerne at vedligeholde deres vidensbase med spørgsmål og svar. Kombineret med robottjenesten og Language Understanding er det nemt at oprette en chatrobot til ofte stillede spørgsmål, som svarer fra forskellige vidensbaser baseret på hensigten med forespørgslen.1234567

FAQ Chatbot Architecture

The QnA Maker tool makes it easy for the content owners to maintain their knowledge base of Questions and Answers. Combined with Bot Service and Language Understanding, it becomes simple to setup a FAQ chatbot which responds from different knowledge bases depending on the intent of the query.

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Optimización del suministro de energíaEn una red energética, se coordinan consumidores de energía con varios tipos de componentes de suministro, comercialización y almacenamiento de energía, como subestaciones, baterías, granjas eólicas, paneles solares y microturbinas, así como ofertas en respuesta a la demanda, para satisfacer sus respectivas demandas y minimizar el costo de la planificación energética. Para ello, el operador de la red debe determinar qué cantidad de energía debe planificarse para cada tipo de recurso para un período de tiempo determinado, teniendo en cuenta los precios de solicitar diferentes tipos de recursos y la capacidad y las características físicas de cada uno de ellos.

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.

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