Friday, October 4, 2019

Azure Key Vault and App Configuration Together

Azure App Configuration provides a great set of options for the people who would like to store the configuration on cloud and manage through a central location. On the other hand, Azure Key Vault is a service that lets you manage all your Secrets, Keys and Certificates. There is a hint of both being connected, but for the time being they are working as two separate services. Connecting them would be great as it will help storing secured app configurations. 

This article focus on how the each service is available as of now. 

Think of an application that is hosted on Azure and distributed across multiple regions. If it is a large scale application, you may have divided different worker roles across the regions. Eg: An App Service along with a Database separate for the East US. Then another for Australia, while the load balancer and metadata information are geo replicated. 

Friday, September 6, 2019

Managing a simple Azure Container Registry

Azure Container Registry provides an excellent support for maintaining and distributing containers across multiple regions. But for this article, lets focus on a simpler container registry where my requirement is likely to host a few services on a Kubernetes Cluster. 

Publishing to Container Registry


You can simply use PowerShell. A sample code for uploading a local docker image to ACR can be done with the following command. 

First you need to login to Azure using az login command. Then,

az acr login -n <ContainerRegistryName>
docker tag <LocalImageName>:<LocalTag> <ACRName>.azurecr.io/<Repository>:<Tag>
docker push <ACRName>.azurecr.io/<Repository>:<Tag>


Wednesday, July 10, 2019

Serverless Apps with Azure Functions


Azure functions are getting updated and developed rapidly. The latest feature Microsoft has introduced to Azure function is to work with Serverless applications. Not all developers may like this. Some may fear or feel challenges when going Serverless. Azure functions can help them overcome these. 

Sunday, June 30, 2019

Using Azure DevOps to collaborate Data Scientists and App Developers


What is your most favorite IDE? A developer can mention various of IDE’s. How about data scientist?


Normally, the Developers develop the code and data scientists train develop and train the model. Tools such as VSCode come in handy as easy to install and use. Many have many preferences so the chances are that it can be a choice of the developer or the development team. Usually the trained model is handed over to the app developer for integrating it and build the final application. There are times where the mismatches in compatibility can cost both the app developer and the model developer. The resulting friction between app developers and data scientists to identify and fix the root cause can be a slow, frustrating, and expensive process
We often here organizations including managers continuously talking about Artificial Intelligence. People like to find solutions that are integrated with AI. So as the developers have a development lifecycle, the data scientists follow a data science lifecycle. 

The lifecycle includes processes such as,

Data Ingestion --> Data Preparation --> Model Development --> Model Deployment

There can be many iterations of this lifecycle as there can be requirements for changing the data labels, removing anomalies, changes upon user feedback and timely decision changes and many more. 

Friday, June 28, 2019

Serverless with Azure Kubernetes Service

As I have said before, Kubernetes is the future and organizations are migrating to containers. That makes Azure a top choice in the industry. Even non container based solutions right now are planned with intentions to get into cloud in future. 

Speed, reliability and portability are among the main reasons for people to move to containers. Those qualities make virtual machines a less preferred option. Self healing reduces maintenance overlook needs.

Monday, June 24, 2019

DevOps Integration with GitHub and Azure

Customers need faster, yet reliable solutions. Developers would love to relax the weekends after doing a deployment. Both these did not happen together very often. As a result, various iterative development methodologies such as Agile and Scrum are introduced. DevOps is the latest explanation introduced by Microsoft for such organizations where the team of developers and the requirement holders are connected very efficiently.

Microsoft made GitHub a friend by acquiring GitHub rather than sticking only with Visual Studio Teams services. Thanks to that decision, over 10,000 open source projects are handled with the support of both GitHub and Azure DevOps TOGETHER.


Sunday, June 16, 2019

Visual interface for Azure Machine Learning Service

Microsoft has been great with interfaces for visualizing workflows. SharePoint has it, Microsoft Flow has it and many other services including Logic Apps has it. The preview for the Azure ML visual interface was announced during Microsoft Build. 

Not only visualizing and understanding, drag and drop helps ease the processes of testing and deploying ML models as well. Nothing helps more than a visual diagram for a developer to understand the logic of, may be his own work sometime later. 

Source: Azure Blog