Liquid Transformation As a Azure Function using DotLiquid

In this article, I would brief about achieving Liquid Template Transformation using DotLiquid in a Azure Function.

Using Azure SDK, I have create a simple HTTP Trigger function. This has two projects, LiquidTransformationApp(LiquidTransformation) and AzureFunctions.Helper.

In LiquidTransformation, we extract the request body, map name and map type from the query string and invoke utility helper for the transformation, as shown

Here is utility helper class with does the Parse and Render of the Liquid Template. I have embedded the liquid templates as as resource files and based on the MapName and MapType, we would dynamically execute the transformation and render the transformed result as HTTP Response to client. 

Here, we receive JSON request and JSON request would contain nested JObject/Array, thus to parse the JSON request as Dictionary Object, we use ParseJSONHelper and GenericInterface<T> and Generic<T> are used in Parse and Render stages of Liquid Templates to achieve support for dynamic objects.

Here are the Json To Json and Json To XML Transformation liquid templates.

Lets run and verify the Liquid Template Transformation

Migrating BizTalk Transformation To Azure using Azure Function as an API

In this article, I would brief about Migrating BizTalk Transformation As-Is to Azure Function(API) and this can be invoked from Logic App. Thus the transformation can be execute across different resource group, region and integration account.

Using Azure SDK, I have create a simple HTTP Trigger function. This has two projects, TrasformationHelper(TransformAPI) and AzureFunctionHelper.

In TransformAPI, we extract the request body and map name from the query string and invoke utility helper for the transformation.

In AzureFunctionHelper, I have embedded the XSLT and Extension Objects as resource files and based on the MapName, we would dynamically execute the transformation and render the transformed result as HTTP Response to client.

Here is the XSLT for one of the transformation and this invoke external assembly methods, as shown. External assembly method does DB Lookup. Lets add the reference of External Assembly to Azure Function Project.

Lets configure hybrid connection in Azure Function. select Networking and click on configure your hybrid connection endpoints. Click on Add hybrid Connection, 
Create a new or bind to existing Hybrid Connection. Refer my earlier article for configuring azure hybrid connection to access on-prem sql server.

Lets deploy and test the Azure function API. This can be invoked from Logic App to achieve dynamic transformation.

Note:- External Assembly would be package as part of Azure Function Package. This allows us to completely re-use BizTalk Transformation as-is.

Connecting On-Premise Service Using On-Premise Data Gateway

In this article, I would brief on connecting on-premise service(API/WCF service) using On-Premise Data Gateway.

Lets install and configure on-premise data gateway.

Configure the data gateway with your account id (must be domain user)

As shown below, configure the the gateway in appropriate location and provide the recovery key.

Post configuring the gateway in the on-premise system, lets connect to the Azure Portal and map the on-premise gateway with the Azure Gateway, as shown below. Make sure to choose the same region/location of on-premise gateway.

Now lets, create custom logic app connector.

Lets edit the custom connector and configure the on-premise service(for our eg we choose WebAPI) using swagger for API or WSDL for SOAP services.

Here we would connect to on-premise API, lets fill in the general information and enable the connectivity using on-premise data gateway as shown below

On the security tab, lets choose No Authentication to keep it simple and on the definition tab, configure each operations available on the API, which are available as part of Actions [Action Methods], finally update the connector. Now using this connector, we would be able to connect to on-premise services.

Lets create and connect to on-premise service using custom connector. Here, we will develop simple request response logic which would pull all the products information thru the on-premise API Service.

Lets add an action and choose custom connector and select relevant operation as shown below

Now, lets add a response and configure the response with the output body of custom connector.

Test and verify the logic app.

Logic App | Integrating with Azure Function

In this article, I will integrate Azure Generic Webhook function with Logic App.

Lets create a generic webhook function and generate a code from json request as shown and use it the function.

This function validates the JSON input and renders response based on the unit provided.

Lets create Logic App and choose a blank template,as shown below.

 Bring in a HTTP Request,

 Using Sample JSON, we can generate the JSON schema and the configure the HTTP verb as post and provide the relative path

Once HTTP request is configured, we can add a new step and then choose an action and configure the Azure Function. Then pass in the HTTP body to function as shown.

Now, we can validate the response using condition and control the flow for true and false path.

Save the logic app and push message using PostMan tool and validate the behavior

Logic Apps | Azure Integration | Server-less Compute

In this article, I would explain how to develop a simple Logic App.In Azure, Click on New-->Enterprise Integration-->Logic App, as shown below
Provide the Logic App Name and choose the subscription and resource group.

Once its created;we can develop the flow either from a blank template or using common template. Here, we would would develop a simple app that poll twitter for a specific keyword and process the tweet to an Azure SQL Server DB.

Lets sign-in and configure/authorise logic app to use that twitter account to use for polling; now configure the polling details and text keyword to poll for.

Let now add a new step to process the tweet to SQL DB, bring in a SQL Server -Insert row and provide the Azure SQL Server connection details as shown. Here we capture the user name and tweet in the Azure SQL DB table.

Lets run and verify the behaviour, for every 3 mins logic app polls and if any tweets are available those are processed to Azure SQL DB.