Dylan  Iqbal

Dylan Iqbal

1617845819

CONA Services optimizes SAP HANA landscape on Microsoft Azure with Azure NetApp Files

In this video, hear from CONA Services on how moving their SAP landscape to Microsoft Azure benefited the Coca-Cola companies by increasing scale, reducing costs, and increasing productivity. Azure NetApp Files was critical in allowing this digital transformation to happen.

To learn more, read the technical white paper here: https://azure.microsoft.com/mediahandler/files/resourcefiles/cona-optimizes-sap-landscape-on-azure-by-moving-sap-bw-on-hana-to-azure-virtual-machines/CONA-TCS.pdf

#azure #microsoft

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CONA Services optimizes SAP HANA landscape on Microsoft Azure with Azure NetApp Files
Dylan  Iqbal

Dylan Iqbal

1617845819

CONA Services optimizes SAP HANA landscape on Microsoft Azure with Azure NetApp Files

In this video, hear from CONA Services on how moving their SAP landscape to Microsoft Azure benefited the Coca-Cola companies by increasing scale, reducing costs, and increasing productivity. Azure NetApp Files was critical in allowing this digital transformation to happen.

To learn more, read the technical white paper here: https://azure.microsoft.com/mediahandler/files/resourcefiles/cona-optimizes-sap-landscape-on-azure-by-moving-sap-bw-on-hana-to-azure-virtual-machines/CONA-TCS.pdf

#azure #microsoft

Ssekidde  Nat

Ssekidde Nat

1624912860

Developing Middleware With Microsoft Azure Service Bus And Functions

Introduction

A middleware is a software service that glues together multiple services. In today’s business needs, multiple software services and technologies need to work together and communicate with each other. It is not necessary that these distributed software services are compatible with each other and will be able to communicate.

Example Business Case

We have to develop a software service in which we have geo-coordinates of a location and we need to get weather information of the city based on those coordinates. We have a system X that needs to communicate with another system Y. These are distributed systems. System X has information about geo coordinates and system Y will store weather information of the city based on those coordinates.

Solution

We will develop a middleware between system X and system Y.

Middleware Architecture

  1. System X will send geo coordinates to the receiver service (Http Triggered Azure Function) of the middleware in JSON format.
  2. Receiver service will call reverse geocoder API and will extract city name from the response and finally sends the city name to the Service Bus queue.
  3. Sender service will receive city name from service and call weather API and send weather data to System Y (Service Bus Queue Triggered Function).
  4. System Y will receive weather information from the sender service and store it (For sake of simplicity, we will log the information at Sender Service).

Prerequisites

  1. Microsoft Azure Subscription.
  2. Deployed Service Bus resource on Microsoft Azure Portal.
  3. Postman for testing
  4. Visual Studio 2019
  5. .NET Core 3.1

#functions #microsoft azure service #microsoft azure #azure

Aisu  Joesph

Aisu Joesph

1624327316

Securing Microsoft Active Directory

Clustering

K-means is one of the simplest unsupervised machine learning algorithms that solve the well-known data clustering problem. Clustering is one of the most common data analysis tasks used to get an intuition about data structure. It is defined as finding the subgroups in the data such that each data points in different clusters are very different. We are trying to find the homogeneous subgroups within the data. Each group’s data points are similarly based on similarity metrics like a Euclidean-based distance or correlation-based distance.

The algorithm can do clustering analysis based on features or samples. We try to find the subcategory of sampling based on attributes or try to find the subcategory of parts based on samples. The practical applications of such a procedure are many: the best use of clustering in amazon and Netflix recommended system, given a medical image of a group of cells, a clustering algorithm could aid in identifying the centers of the cells; looking at the GPS data of a user’s mobile device, their more frequently visited locations within a certain radius can be revealed; for any set of unlabeled observations, clustering helps establish the existence of some structure of data that might indicate that the data is separable.

What is K-Means Clustering?

K-means the clustering algorithm whose primary goal is to group similar elements or data points into a cluster.

K in k-means represents the number of clusters.

A cluster refers to a collection of data points aggregated together because of certain similarities.

K-means clustering is an iterative algorithm that starts with k random numbers used as mean values to define clusters. Data points belong to the group represented by the mean value to which they are closest. This mean value co-ordinates called the centroid.

Iteratively, the mean value of each cluster’s data points is computed, and the new mean values are used to restart the process till the mean stops changing. The disadvantage of k-means is that it a local search procedure and could miss global patterns.

The k initial centroids can be randomly selected. Another approach of determining k is to compute the entire dataset’s mean and add _k _random co-ordinates to it to make k initial points. Another method is to determine the principal component of the data and divide it into _k _equal partitions. The mean of each section can be used as initial centroids.

#ad #microsoft #microsoft-azure #azure #azure-functions #azure-security

Make Your Business Popular On the Internet with search engine optimization services India

As a small business owner, you should never think that SEO services are not for you. The search engine optimization services India from this digital marketing agency offer SEO services for small businesses and enterprises to make sure that they get in competition with bigger websites. They deliver on-page, off-page, local SEO and ecommerce SEO services.

#search engine optimization services india #seo services india #affordable seo services india #seo services provider #website seo services #outsource seo services india

Shawn  Durgan

Shawn Durgan

1602776460

Implement Azure AD Client credentials flow using Client Certificates for service APIs

This post shows how to implement an Azure client credential flows to access an API for a service-to-service connection. No user is involved in this flow. A client certificate (Private Key JWT authentication) is used to get the access token and the token is used to access the API which is then used and validated in the API. Azure Key Vault is used to create and provide the client certificate.

Code: https://github.com/damienbod/AzureADAuthRazorUiServiceApiCertificate

Create a client certificate in Azure Key Vault

A self signed certificate with a key size of at least 2048 and key type RSA is used to validate the client requesting the access token. In your Azure Vault create a new certificate.

Download the .cer file which contains the public key. This will be uploaded to the Azure App Registration.

Setup the Azure App Registration for the Service API

A new Azure App Registration can be created for the Service API. This API will use a client certificate to request access tokens. The public key of the certificate needs to be added to the registration. In the Certificates & Secrets, upload the .cer file which was downloaded from the Key Vault.

No user is involved in the client credentials flow. In Azure, scopes cannot be used because consent is required to use scopes (Azure specific). Two roles are added to the access token for the application access and these roles can then be validated in the API. Open the **Manifest **and update the “appRoles” to include the required roles. The **allowedMemberTypes **should be Application.

#app service #asp.net core #aspnet5 #azure key vault #7523 #azpacr #azure #azure app registration #client credentials #jwt #key vault #microsoft.identity.client #microsoft.identity.web #oauth #oauth2 #private key jwt authentication #rfc7523