Microsoft Graph API integration from Pega V8.x

-

Brief idea on MS Graph API:

Microsoft Graph is a Microsoft developer platform that connects multiple services and devices. Initially released in 2015, the Microsoft Graph builds on Microsoft 365 APIs and allows developers to integrate their services with Microsoft products, including Windows, Microsoft 365, and Azure. The Microsoft Graph API offers a single endpoint, https://graph.microsoft.com, to provide access to rich, people-centric data and insights exposed as resources of Microsoft 365 services. Microsoft Graph exposes REST APIs and client libraries to access data on most of the Microsoft cloud services. 

The below diagram gives a high level idea.











The Microsoft Graph explorer is a tool that lets you make requests and see responses against the Microsoft Graph. To access this tool, we need to have access in Microsoft Azure Portal. I have free trial access with limited features from Azure. Here is the portal URL to get the access: https://portal.azure.com/ 

Here is the Graph Explorer tool and is same as our Postman/SOAP UI to test the connectivity. 













To access the Graph API from Pega or any other application, we need to generate the Access token using OAuth2. The main parameters to pass in Access token API: https://login.microsoftonline.com/{{TenantID}}/oauth2/v2.0/token are client_id,tenant_id,client_secret,etc. To get all these parameters, we need to login in Azure and use them. Access token is the key to access any other API's and is valid for an hour. 

To use this token API in Pega, we can create a REST Connector and import it from the connector wizard. We need to make sure to store/cache this token data in a DataPage.

Below snapshot gives an idea on capturing of these parameters.
















Based on our requirement, we need to create as many as REST connectors by consuming the token data from the DataPage. For some of the API's, we have full access privileges but for some of them we need the admin access permissions. If Pega gives a component on this API then we don't worry about all the connectors design logic.

To explore more on all the useful API's, import all the below mentioned Postman links given by Microsoft team.

https://raw.githubusercontent.com/microsoftgraph/microsoftgraph-postman-collections/master/Microsoft%20Graph.postman_collection.json 

https://raw.githubusercontent.com/microsoftgraph/microsoftgraph-postman-collections/master/Microsoft%20Graph.postman_environment.json 

Here are the YouTube videos on how to consume these API's from Postman. I like these videos and followed them well to understand the API's functionality.

https://www.youtube.com/watch?v=7Sx2pFY21YQ

https://www.youtube.com/watch?v=4tg-OBdv_8o

Bottomline is like MS Graph API works on one single endpoint with a single token for accessing multiple resources from the MS products easily.

References:

1) Google.com

2) https://docs.microsoft.com/

3) https://portal.azure.com/

4) https://developer.microsoft.com/en-us/graph/graph-explorer

Popular posts from this blog

Connecting Claude to Pega Infinity 25.1.3 via MCP — Step-by-Step

-
Image
Enable AI-powered access to your Pega Investigative Case Management data directly from Claude prompts using the Model Context Protocol (MCP) and OAuth 2.0. What is MCP and why connect Pega to Claude? The Model Context Protocol (MCP) is an open standard that lets AI assistants like Claude securely call tools and read data from external systems — all from a natural-language prompt. Think of it as a universal adapter between your enterprise systems and AI. Pega Infinity V25.1.3 ships with a first-class MCP service built on its existing REST framework. Once enabled, Claude can: Query and summarize investigative cases without switching apps Retrieve assignment details and case status on demand Trigger Pega workflows from conversational prompts Version requirement: This guide is based on Pega Infinity V25.1.3 (Community Edition) with the Rule-Service-MCP rule type. Earlier versions may not include native MCP support. Architecture overview The connection uses three layers: Claude as the AI c...
Read more

itextpdf API to generate PDF doc from an image file using Pega PE

-
Image
Probably some of the techies might have an idea on an opensource called " itextpdf " (earlier name is lowagie ) to convert an image file(png,jpeg,jpg,tiff,gif etc.) to a PDF file. It is very simple to use this API in Pega function to build the logic using java code. Moreover, this API comes in one single jar file and we need to import it in Pega before we start using it.  I see the conversion comes good in PDF file but not sure if any limitations of this API in terms of conversion is like formatting, font, images etc. So far so good and may be we can keep this API as one of our solutions while working on the requirements accordingly.  Heard that same API can be used to convert the text file to PDF but I didn't explore on it. Those who are interested to work on text -> PDF can take a look at the documentation. Don't hesitate to contact me offline for any further discussion in this context :) :) Prerequisites for doing this exercise: 1) itextpdf 5.4.0 jar file 2) Peg...
Read more

Understanding of Hugging Face platform for AI/ML platform

-
Image
Hugging Face is a platform that provides tools and libraries for natural language processing (NLP), machine learning, and artificial intelligence. It is known for its Transformers   library, which offers pre-trained models for tasks such as text classification, translation, question answering, and more. Hugging Face also hosts a model hub where users can share and discover pre-trained models. Hugging Face is useful in various domains, including: Natural language processing (NLP): Provides tools and pre-trained models for tasks like text classification, translation, sentiment analysis, and question answering. Machine learning research: Offers state-of-the-art models and datasets for researchers to experiment and innovate. Data science and analytics: Helps data scientists analyze and interpret large volumes of text data. AI application development: Enables developers to build AI-powered applications with ease using pre-trained models and APIs. A very simple exercise using the google...
Read more