Deep Dive Getting Started With Azure RTOS

Deep Dives are interactive technical live and on-demand events for developers, architects, or anyone building IoT solutions. Check out the Azure RTOS samples featured in Deep Dive here: https://aka.ms/azrtos-github Microsoft engineers and guest speakers do technical deep dives about a new feature or scenario. List of all upcoming Microsoft IoT Deep Dives: https://aka.ms/iotshow/deepdive

Azure RTOS is a small, fast, reliable, and easy-to-use real-time operating system. In this video introduction, we’ll discuss the major components that make up the Azure RTOS ecosystem: the ThreadX RTOS, NetX TCP/IP stack, FileX embedded file system, GUIX embedded GUI, and USBX embedded USB stack. We’ll also cover some tools to make development easier, such as GUIX Studio (a WYSIWYG GUI designer that auto-generates C code to run on embedded devices) and TraceX (an event trace tool that feels like a software logic analyzer).

Guest Speaker: Scott Larson - Azure IoT Senior Engineer
Deep Dive Host: Pamela Cortez - Azure IoT

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Deep Dive Getting Started With Azure RTOS
Ron  Cartwright

Ron Cartwright

1600624800

Getting Started With Azure Event Grid Viewer

In the last article, we had a look at how to start with Azure DevOps: Getting Started With Audit Streaming With Event Grid

In the article, we will go to the next step to create a subscription and use webhook event handlers to view those logs in our Azure web application.

#cloud #tutorial #azure #event driven architecture #realtime #signalr #webhook #azure web services #azure event grid #azure #azure event grid #serverless architecture #application integration

Eric  Bukenya

Eric Bukenya

1624713540

Learn NoSQL in Azure: Diving Deeper into Azure Cosmos DB

This article is a part of the series – Learn NoSQL in Azure where we explore Azure Cosmos DB as a part of the non-relational database system used widely for a variety of applications. Azure Cosmos DB is a part of Microsoft’s serverless databases on Azure which is highly scalable and distributed across all locations that run on Azure. It is offered as a platform as a service (PAAS) from Azure and you can develop databases that have a very high throughput and very low latency. Using Azure Cosmos DB, customers can replicate their data across multiple locations across the globe and also across multiple locations within the same region. This makes Cosmos DB a highly available database service with almost 99.999% availability for reads and writes for multi-region modes and almost 99.99% availability for single-region modes.

In this article, we will focus more on how Azure Cosmos DB works behind the scenes and how can you get started with it using the Azure Portal. We will also explore how Cosmos DB is priced and understand the pricing model in detail.

How Azure Cosmos DB works

As already mentioned, Azure Cosmos DB is a multi-modal NoSQL database service that is geographically distributed across multiple Azure locations. This helps customers to deploy the databases across multiple locations around the globe. This is beneficial as it helps to reduce the read latency when the users use the application.

As you can see in the figure above, Azure Cosmos DB is distributed across the globe. Let’s suppose you have a web application that is hosted in India. In that case, the NoSQL database in India will be considered as the master database for writes and all the other databases can be considered as a read replicas. Whenever new data is generated, it is written to the database in India first and then it is synchronized with the other databases.

Consistency Levels

While maintaining data over multiple regions, the most common challenge is the latency as when the data is made available to the other databases. For example, when data is written to the database in India, users from India will be able to see that data sooner than users from the US. This is due to the latency in synchronization between the two regions. In order to overcome this, there are a few modes that customers can choose from and define how often or how soon they want their data to be made available in the other regions. Azure Cosmos DB offers five levels of consistency which are as follows:

  • Strong
  • Bounded staleness
  • Session
  • Consistent prefix
  • Eventual

In most common NoSQL databases, there are only two levels – Strong and EventualStrong being the most consistent level while Eventual is the least. However, as we move from Strong to Eventual, consistency decreases but availability and throughput increase. This is a trade-off that customers need to decide based on the criticality of their applications. If you want to read in more detail about the consistency levels, the official guide from Microsoft is the easiest to understand. You can refer to it here.

Azure Cosmos DB Pricing Model

Now that we have some idea about working with the NoSQL database – Azure Cosmos DB on Azure, let us try to understand how the database is priced. In order to work with any cloud-based services, it is essential that you have a sound knowledge of how the services are charged, otherwise, you might end up paying something much higher than your expectations.

If you browse to the pricing page of Azure Cosmos DB, you can see that there are two modes in which the database services are billed.

  • Database Operations – Whenever you execute or run queries against your NoSQL database, there are some resources being used. Azure terms these usages in terms of Request Units or RU. The amount of RU consumed per second is aggregated and billed
  • Consumed Storage – As you start storing data in your database, it will take up some space in order to store that data. This storage is billed per the standard SSD-based storage across any Azure locations globally

Let’s learn about this in more detail.

#azure #azure cosmos db #nosql #azure #nosql in azure #azure cosmos db

Ruthie  Bugala

Ruthie Bugala

1620435660

How to set up Azure Data Sync between Azure SQL databases and on-premises SQL Server

In this article, you learn how to set up Azure Data Sync services. In addition, you will also learn how to create and set up a data sync group between Azure SQL database and on-premises SQL Server.

In this article, you will see:

  • Overview of Azure SQL Data Sync feature
  • Discuss key components
  • Comparison between Azure SQL Data sync with the other Azure Data option
  • Setup Azure SQL Data Sync
  • More…

Azure Data Sync

Azure Data Sync —a synchronization service set up on an Azure SQL Database. This service synchronizes the data across multiple SQL databases. You can set up bi-directional data synchronization where data ingest and egest process happens between the SQL databases—It can be between Azure SQL database and on-premises and/or within the cloud Azure SQL database. At this moment, the only limitation is that it will not support Azure SQL Managed Instance.

#azure #sql azure #azure sql #azure data sync #azure sql #sql server

Vern  Greenholt

Vern Greenholt

1595005500

Getting Started : Deep Learning Project

Deep Learning(DL) have got some serious traction in the past couple of years and many of us are fascinated by these technologies and want to start learning working in these…

Most of us are familiar with what DL is, so I won’t cover that in this article, rather I’d like to focus on how to start a DL project.

Research, research and more research :

Bet you thought I’d start with data pre-processing, but NO… And there’s a good reason for it. Before you start any project, you need to research about the project you’re about to undertake, the technologies and domain knowledge that is required for the same. DL projects revolve all around data, and proper dataset and it’s processing is the key to getting good results.

Points to consider while researching :

  1. Form of data_ :_
  2. Identifying the form of data (csv, image, audio, text, etc.) is very important as the pre-processing to be done on the data may require a lot of domain knowledge.
  3. For example : a typical csv dataset may be easily worked on, but for say audio data, one needs to have domain knowledge to select and process attributes from the audio to get best results
  4. Type of Network:
  5. Great, now that you’ve identified the form of data, it’s time to select an approach. In DL, one can select different type of networks amongst Artificial Neural Network(ANN), Convolutional Neural Network(CNN), Long-term Short-term Memory Networks(LSTM), etc. Reading research papers (Google Scholar_ is a great way to search) and approaches other developers have used will help to decide an approach of your own. Study the approach you select and different forms of it._
  6. Tools, libraries and environment:
  7. Select a deep learning library you’re familiar with (Tensorflow, PyTorch, Keras, etc.) and according to mode of deployment of your model. Personally, I love the simplicity of Keras and I’d recommend the same for beginners.
  8. _DL is computationally expensive, so if hardware is an issue, Google Colab is a great option where you can code your project from any device, and it runs on powerful hardware provided by Google (And its Free!). Completely online coding environments like __GitPod _are also useful and have Git integration built in with them.

#deep-learning #research #dataset #data-pre-processing #getting-started #deep learning

Fannie  Zemlak

Fannie Zemlak

1597500000

Getting started with Azure Static Web Apps | Azure Tips and Tricks

In this video, you’ll learn how to get started with Azure Static Web Apps.

#coding #azure #azure static #azure tips