AI News, Microsoft Weekly Data Science News for September 07, 2018

Microsoft Weekly Data Science News for September 07, 2018

Data Scientists do more than build fancy AI and machine learning models.

These tasks fall to the data scientist to solve (unless there is a data engineer willing to help).

More formally stated, Azure Functions are serverless computing which allows code to run on-demand without the need to manage servers or hardware infrastructure.

Without having to configure servers or virtual machines, the following tasks become much simpler: As of August 2018, full support is provided for C#, Javascript, and F#.

This would allow someone to quickly create an endpoint for running machine learning models via scikit-learn or another python module.

Next time you have a data science task which requires a little coding, consider using an Azure Function to run the code.

Use Azure Functions to connect to an Azure SQL Database

This topic shows you how to use Azure Functions to create a scheduled job that cleans up rows in a table in an Azure SQL Database.

The new C# script function is created based on a pre-defined timer trigger template in the Azure portal.

To have your function process individual create, read, update, and delete (CRUD) operations in a Mobile Apps table, you should instead use Mobile Apps bindings.

Azure Functions C# script (.csx) developer reference

This article is an introduction to developing Azure Functions by using C# script (.csx).

Argument names are specified in a function.json file, and there are predefined names for accessing things like the function logger and cancellation tokens.

This compilation step means things like cold start may take longer for C# script functions compared to C# class libraries.

The folder structure for a C# script project looks like the following: There's a shared host.json file that can be used to configure the function app.

The binding extensions required in version 2.x of the Functions runtime are defined in the extensions.csproj file, with the actual library files in the bin folder.

Input or output data is bound to a C# script function parameter via the name property in the function.json configuration file.

In the following example, a logging routine named MyLogger is shared in myLogger.csx and loaded into run.csx using the #load directive: Example run.csx: Example mylogger.csx: Using a shared .csx file is a common pattern when you want to strongly type the data passed between functions by using a POCO object.

In the following simplified example, an HTTP trigger and queue trigger share a POCO object named Order to strongly type the order data: Example run.csx for HTTP trigger: Example run.csx for queue trigger: Example order.csx: You can use a relative path with the #load directive: The #load directive works only with .csx files, not with .cs files.

To write multiple values to an output binding, or if a successful function invocation might not result in anything to pass to the output binding, use the ICollector or IAsyncCollector types.

This example writes multiple queue messages into the same queue using ICollector: To log output to your streaming logs in C#, include an argument of type TraceWriter.

The following namespaces are automatically imported and are therefore optional: For framework assemblies, add references by using the #r "AssemblyName"

The following assemblies are automatically added by the Azure Functions hosting environment: The following assemblies may be referenced by simple-name (for example, #r "AssemblyName"): To reference a custom assembly, you can use either a shared assembly or a private assembly: For information on how to upload files to your function folder, see the section on package management.

Here is an example project.json file that adds a reference to Microsoft.ProjectOxford.Face version 1.1.0: In Azure Functions 1.x, only the .NET Framework 4.6 is supported, so make sure that your project.json file specifies net46 as shown here.

To get an environment variable or an app setting value, use System.Environment.GetEnvironmentVariable, as shown in the following code example: The System.Configuration.ConfigurationManager.AppSettings property is an alternative API for getting app setting values, but we recommend that you use GetEnvironmentVariable as shown here.

How to Use Azure Functions to Effortlessly Run Small Applications

Serverless computing is the word of the day, and Microsoft Azure Functions acts a modern serverless architecture delivering event driven cloud computing and configured to comply with application development.

To build the apps themselves, the developers can use their own choice of programming language, giving them the freedom to work optimally.

Intuitive, browser-based user interface — You can write code in the easy-to-use web interface or use your favorite development tool to build and debug.

You can utilize the programming model for a number of activities such as building HTTP-based API, communicating with other servers or orchestrating complex workflows.

Capabilities for implementing code — Being event driven, the application platform has capabilities to implement code triggered by events occurring in any third-party service or on-premise system.

Deploying the Azure Function App Easy integration with Azure and 3rd-party services — Azure Functions offers integration with a number of Azure services apart from several third-party services (like Azure Notification Hubs, Azure Event Grid, Azure Event Hub, Azure Service Bus, Azure CosmosDB, Azure Storage, etc.) in many of the services where you need to run code snippets.

Implement custom features — It is easier to implement custom features with this platform because runtime, templates, UI and underlying WebJobs SDK are all open source projects.

Developers can save time deploying apps by uploading pre-compiled executables because they don’t have to write the code from scratch.

It helps the developers to simply interact with the data sources and services and not worry about the flow of data ‘to and from’ the function.

Developers can send data like queueing message for instance, with the help of the return value of the function, a collector object or an out parameter.

Other functions include: update an external issue tracker, update a backup mirror, trigger CI builds and deploy to your production server.

Once CosmosDBTrigger listens for updates and updates across various partitions, the change feed would publish inserts and updates, but not deletions.

ServiceBusQueueTrigger — Through the service bus queue trigger, the developer can execute the code in the function every time the service bus received a message.

ServiceBusTopicTrigger — When the function is triggered with service bus topic message, the developer can publish and push messages to the topic.

Azure Functions integrates with a number of third-party services, on-premises services and several Azure services to trigger the functions or serve as input/output for the code.

These are the integrations supported by Azure Functions: Azure Cosmos DB, Azure Event Hubs, Azure Event Grid, Azure Mobile Apps (tables), Azure Notification Hubs, Azure Service Bus (queues and topics), Azure Storage (blob, queues, and tables), GitHub (webhooks), On-premises (using Service Bus), Twilio (SMS messages).

It is possible to monitor and troubleshoot functions with the logging capabilities provided within this compute-on demand, event driven experience.

It helps in processing data, coordinating with different systems for IoT, integrating various processes and systems and building simple APIs and microservices.

Whenever you need to scale your app during peak seasons and high demand hours, this platform would manage it easily, and you don’t have to worry about capacity planning concerns.

Hence, developers can make full use of Azure Functions to build HTTP based end points that can be seamlessly accessed by a varied selection of applications, mobile and IoT devices.

Once the data transfer happens, another function is triggered wherein notifications about the data are sent to the mobile app using Notifications Hub.

This is a far cry from traditional application development as it requires complex IT infrastructure that was often unwieldy, expensive and time consuming.

Cloud computing improved things a bit, but with serverless computing, the latest buzzword in the world of app development, there was a sea of change in the way things moved.

Through Azure Functions serverless architecture, it is possible to stop worrying about all the infrastructure considerations you once faced, and just focus on creating and uploading proper code.

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