Abel Wang explains the relationship between DevOps and Cloud-Native

Cloud-native is microservices containers and serverless apps that run in multi-cloud environments and are managed by DevOps processes. However, the relationship between these is not always clearly defined. Shayne Boyer, Principal Cloud Advocate, in a conversation with Abel Wang, Principal cloud Advocate, and DevOps lead discussed the relationship between DevOps and Cloud-Native on the Microsoft developer channel.

What is DevOps?

Abel starts off by saying, DevOps at Microsoft is the union of people, processes, and products to enable the continuous delivery of value to our end-users. The reason one should care about DevOps when it comes to cloud native apps is that the key here is continuously delivering value. One of the powers of Cloud Native is because all of your infrastructures is out in the cloud, you're able to iterate it very quickly. This is what DevOps helps you do as well, continuously deliver value to your end-users. These days the speed of business is so quick that if we can't iterate quickly and give value quickly, our competitors will and once they do it the rest will be obsolete. Hence, it is extremely important to iterate quickly which Cloud-Native helps enable.

The concept of continuously delivering value remains similar to the concept we carry out on our local machine during a standard deployment. Where Cloud-Native become completely unique is,

1. All your infrastructures are out in the cloud. Hence, deploying to the cloud is easier to do than deploying on to like a mobile app.
2. One of the most powerful things about cloud-native is that it is a microservice-based architecture.

With these advantages, we're able to iterate quickly because instead of deploying this massive model if we make one tiny little change, we can just deploy that one service. This will simplify and speed up the process. With this every developer check-in can go through our gates, can go through our pipeline, reach production at a quicker rate, and so we're able to give value even faster and better.

Key DevOps and Cloud-Native Apps concepts

Wang says to aim for a CI/CD pipeline that can process code as soon as somebody adds it in. The pipeline should further make it easy to build and then finally deploy it to the infrastructure present.

Wang demonstrates a cloud-native application with a slightly complicated infrastructure. The application consists of a static website that is held in Azure storage, it has a back-end written in .Net Core which is held in an Azure function and they both connect up to a Cosmos DB.

If microservices are deployed independently, the services need to be smart enough to realize what version the other services are on so that the entire application is not disturbed if additional service is uploaded. He further demonstrates an instance for deploying the entire infrastructure all at once. You can check out the video to know more about the demonstration in detail.

How to ensure quality across environments in a DevOps practice?

In a cloud-native application, we need not worry about deploying similar infrastructures while moving from one environment to the next. This is because the dev environment will be exactly the same as the QA environment and further the same throughout all the way out into production. This will be cost-effective because we can just spin it up to run whatever we need to and as soon as it's done, tear it down so we're not paying for anything.

Automating the Cloud Native processes include a few manual steps such as approving an email. Wang says one could technically automate everything, however, he prefers having manual approvers. Within Azure DevOps, there is a concept of an automated approval gate as well. So one can use automation to help decide if they should postpone approval or not. Wang says he uses an automated approval gate to conduct DNS checks that can inform him whether or not the DNS has propagated.

Wang says, trying to keep quality in your pipelines is really difficult to do. You can do things like run all of the automated UI tests for a particular environment. “so by the time let's say I deployed this into a QA environment by the time my QA testers even look at it it could have run through like hundreds of thousands of automated UI tests already. So there's a lot less that a human needs to do,” Wang adds.

To learn comprehensively how to develop Azure cloud architecture and a pipeline management system and also to know about some security best practices for your Azure deployment, you can check out the book, Azure for Architects - Second Edition by Ritesh Modi.

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