Vídeos de Azure
Feeling the pressure to keep up with customers and competitive demand in the market? Or the squeeze to deliver more business value at an increasingly fast pace? While the cloud, containerization, and microservices offer efficiency and scaling, many organizations aren’t quite prepared for that additional complexity of cloud-native technologies and demands. AI, automation, and monitoring facilitate the management of complex modern delivery platforms and help build resiliency into your deployment to enable better performance. In the context of software delivery pipelines. In this session, we will review how AI, automation and monitoring can facilitate the management of complex modern delivery platforms and help build resiliency into your deployment to enable better performance while increasing feature velocity. We will also review key performance indicators for gauging your agile practices and automation, key capabilities to strive to, and an implementation road map to get there.
Rolling out an IoT platform in a retail enterprise is a complex journey. There are numerous business and practical opportunities to solve for, in addition to successfully launching the hardware and software. After encountering a number of hurdles at the inception of the IoT program, the cross-functional team at Starbucks created 10 principles to guide the design and deployment of their IoT platform. Randy Carlson and Venkat Venkatakrishnan will share this IoT platform design and deployment journey through the lens of design principles.
The presentation introduces the journey that we have faced and challenged in adopting widely distributed software systems and Microservices-based architectures in our project. Firstly, we focus on how a full-blown service mesh solution fixes perfectly into our hard use cases in the real world Microservices project. Secondly, we show you how can we resolve interesting challenges such as connect, secure, control and observe services with Istio on the powerful Azure cloud platform with a fully managed Azure Kubernetes Service (AKS). Lastly, we give you a practical understandable demo which puts it all together, to sum up, what we did.
Workflows have moved beyond traditional mouse and keyboard interactions. As such, “input” is no longer confined to the typed word, extending far beyond to include digital ink and images. Join us to learn how you can infuse AI to enable your existing applications to process the input sources modern workflows require.
This session will talk about how various Azure technologies like Azure Event Hubs, Azure Cosmos DB and Node.js can be used to process telematics data. We'll do a code demo of how sample telematics data are ingested into Event Hubs and processed by multiple processes and stored in Azure Cosmos DB.
Your app canvas is no longer limited to a 2D environment; the world in now your app canvas, backed by spatial intelligence from things like IoT sensors, mixed reality, and computer vision. So, what now, and what’s next? In this session, you’ll learn how IoT and mixed reality are driving innovation and business impact in real industry scenarios like manufacturing and AEC. We’ll cover why spatial intelligence is valuable and beneficial to your apps and market, problems and solutions from customers, and the tools and architectures to keep in mind when build spatially intelligent apps.
Using QnA Maker, you can easily create a bot using your existing data – like FAQ pages, support websites, product manuals or documentation. QnA Maker extracts Q&A pairs from your data and represents them in an easy to manage knowledge base. It now also understands relationships between the Q&A pairs in your data and creates multi-turn dialogs. You can edit, delete and author more dialogs in the easy to use UI and quickly test it to see how your bot will work. To give your bot a dash of personality- you can add curated chit-chat data from 5 pre-defined personalities. Once you have trained, tested and published your knowledge base- you can deploy it to a bot with a few clicks using a pre-built bot framework template. Your bot will get smarter with time and usage, by getting feedback with the Active learning feature.
Watch the Azure Keynote from Microsoft Build, by Scott Guthrie.
Postgres is a powerful open source database with different features and tooling. If you are new to Postgres, how do you ensure it’s performant and scale? We’ll start with the basics you need to know as an app developer, then dig into how to optimize apps and database to achieve optimal performance. We’ll look at things like cache hit ratio, index hit ratio and sharding with Citus as you scale your apps. This session will also include learnings from an architect of a leading banking institute who were able to successfully build a highly performing and scalable app. If you're coming from a SQL server we'll cover how things differ and the equivalent options of Postgres, including the rich set of Postgres extensions for deployment experience.
Scenarios that require real-time insights to drive key decisions continue to grow rapidly. Many instances require running some of these analytics close to the data at the edge, and large-scale analytics in the cloud. This session will demonstrate how customers can create these streaming pipelines in minutes by leveraging IoT Hub and Event Hubs (including Kafka client) for massive scale data ingestion; Stream Analytics for real-time analytics; Azure SQL for stream augmentation and data archiving; Power BI for dashboarding & Azure Databricks for downstream batch processing. Downer group of Australia will showcase how they address scenarios such as remote monitoring and predictive maintenance with Azure Stream Analytics.
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