Armon Dadgar (@armon), HashiCorp CTO and co-founder joins Aaron Schlesinger (@arschles) to school him on all things service meshes. You’ll understand what a service mesh actually does, when and why it makes sense to use them, the role of observability, and the differences between data planes and control planes (and what’s relevant to app developers).
Armon makes concepts real with specific examples and analogies, Aaron sees how to easily apply it to his favorite project (Kubernetes, of course) and they sign off with their favorite resources, so you can apply to your apps.
Learn about how to send a message to your Microsoft Teams channel when a rule is fired in your IoT Central app using Microsoft Flow. We’ll cover what is Microsoft Flow, and go through how to build workflows easily using the hundreds of connectors available.
In this video, Noelle La Charite talks about the work we are doing to simplify the use of Cognitive Services in your applications. Now you can have a single key, which eliminates having to reference and manage many keys per service for a single application.
In 2016, I started the Microsoft Professional Program in Data Science when it was released to the public. At the time, I was changing my career vector from an ace Windows app developer to the Data Science and AI world. The program, the first of its kind for Microsoft, provided me with the means and the tools to achieve ninja status quickly and reboot my career. They are also, when compared to university programs, much more affordable.
In the years since, Microsoft has added more professional programs, from Cybersecurity to DevOps. Naturally, I took and completed the tracks for AI and Big Data. You can hear Andy Leonard and I talk about our experiences with the program and how they differ from traditional MCP programs in this episode of Data Driven. Or click on the play button below.
Now, the team has added an IoT track to the list, which can help accelerate anyone’s career in this fast-growing and world changing field: IoT.
This new program will teach you the device programming, data analytics, machine learning, and solution design skills you need for a successful career in IoT. Learn the skills necessary to start or progress a career working on a team that implements IoT solutions.
This video from the Microsoft Developer YouTube channel gives a thorough overview of CosmosDB, a globally distributed multi-model database-as-a-service. It provides NoSQL foundation with comprehensive SLAs on throughput, availability, consistency and latency and exposes data through SQL, MongoDB, Cassandra, Table and Gremlin APIs. Learn how to take advantage of it in your apps today and leverage the economy of scale tomorrow!
This video introduces the use of IPFS (Interplanatory File System) in a consortium setting. The concepts of how this technology can be helpful to remove centralization of storage that is not part of the block in the blockchain is shown. Along with this is a short demonstration of how the marketplace offering for IPFS in Azure can make creating these storage networks simple is shown.
Winvision has leveraged the spatial intelligence capabilities of Azure Digital Twins to build BeSense, a smart building application that provides realtime data that optimizes space utilization and occupant experience.
Ever wondered what breed that dog or cat is? In this show, you’ll learn how to train, optimize and deploy a deep learning model using Azure Notebooks, Azure Machine Learning Service, and Visual Studio Code using Python. Using transfer learning to retrain a mobilenet model via Tensorflow to recognize dog and cat breeds using the Oxford IIIT Pet Dataset.
Next, watch how to optimize that model using the Azure Machine Learning Service HyperDrive service, and improve the accuracy of our model to over 90%. Finally, we’ll put on our developer hat, and use Visual Studio Code and our Python Extension to deploy and test our model. Along the way you’ll see cool features like our new Jupyter-powered interactive programming experience in VS Code, our AI powered IntelliSense feature called Intellicode, and our Azure Machine Learning extension.
HyperDrive service, and improve the accuracy of our model to over 90%. Finally, we’ll put on our developer hat, and use Visual Studio Code and our Python Extension to deploy and test our model. Along the way you’ll see cool features like our new Jupyter-powered interactive programming experience in VS Code, our AI powered IntelliSense feature called Intellicode, and our Azure Machine Learning extension.
Learn about how to connect other IoT clouds like Sigfox, Particle, and The Things Network to IoT Central with the IoT Central device bridge open-source solution. Learn what the device bridge is and how it works, and demo a device connected to The Things Network use the device bridge to connect to your IoT Central app.
In a previous post, covering Python on Azure, Nina Zakharenko and Carlton Gibson showed us how to set up a Python application with Django REST Framework and develop with Visual Studio Code. Now they are back to teach us how to deploy a Python app built on Django to the cloud using Azure Web Apps.
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