Improving your code quality by linking Azure DevOps with SonarCloud

Introduction

In a customer workshop earlier this week, Hans mentioned a very nice tool (SonarCloud). He used it “in his previous life and was very enthusiastic about it. So this immediately triggered my curiosity… 😉 As it is free for public projects, I investigated how easy it was to integrate into my existing pipelines. Which turned out to be quite easy! After browsing around a bit on how to integrate it into a YAML pipeline, I can proudly say that VMchooser is now fully hooked up with SonarCloud.

However, it did confirm my suspicion, that I am a lousy developer! 😉 Though better lousy code fulfilling a purpose than having no alternative at all?!?

Anyhow, today’s post is about the experience of moving existing pipelines to SonarCloud and investigate the results you get out of it.

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Is Azure a tier 3 datacenter? And what about Service Levels in a broader sense…

Introduction

Everyone who has been working with cloud, and involved with tenders, has had the follow question (in one form or another) ; “Has the cloud datacenter achieved a tier 3 (or higher) classification? In today’s post we will delve into the specifics linked to the ask ; Why do organizations ask the question, and how does it related to cloud?

What is a “Tier 3 Datacenter”?

To better understand the concept of data-center tiers, it is important to understand that several organizations (like the Telecommunications Industry Association (TIA) and the Uptime Institute) have defined standards for data-centers.

Uptime Institute created the standard Tier Classification System as a means to effectively evaluate data center infrastructure in terms of a business’ requirements for system availability. The Tier Classification System provides the data center industry with a consistent method to compare typically unique, customized facilities based on expected site infrastructure performance, or uptime. Furthermore, Tiers enables companies to align their data center infrastructure investment with business goals specific to growth and technology strategies.
Source ; https://uptimeinstitute.com/tiers

Which typically consists of several tiers…

Four tiers are defined by the Uptime Institute :

  • Tier I : lacks redundant IT equipment, with 99.671% availability, maximum of 1729 minutes annual downtime
  • Tier II : adds redundant infrastructure, with 99.741% availability (1361 minutes)
  • Tier III : adds more data paths, duplicate equipment, and that all IT equipment must be dual-powered, with 99.982% availability (95 minutes)
  • Tier IV : all cooling equipment is independently dual-powered; adds Fault-tolerance, with 99.995% availability (26 minutes)

Source ; https://en.wikipedia.org/wiki/Data_center#Uptime_Institute_-_Data_Center_Tier_Standards 

So it is a classification for organizations to understand the quality of the data-center, and be able to take a given availability into account. Though it is important to understand, that this relates to “datacenter housing” (colocation) and not to the cloud service models! Why is this statement important? As on top of that housing, additional services will be delivered by cloud providers to achieve service models like IaaS, PaaS, SaaS, …

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Azure DevOps : Operational validation with Approval Gates & Azure Monitor Alerts

Introduction

After having migrated VMchooser from a fully Serverless infrastructure to Containers, I am currently doing the opposite move. As I can start off the same code base to basically run different deployment options in Azure. Where I found that the serverless deployment added more value for me compared to a lower cost profile. That being said, one of the big learnings I had this week is that while having an automated landscape with Terraform, some changes are rather intrusive… Where I should have checked the output of the terraform plan stage, I failed to do so. Which resulted in downtime for VMchooser. So I  was looking for way to do operational validation in the least intrusive and re-usable way. This led me to a solution where the Azure DevOps pipelines would leverage the health-check used in the Traffic manager deployment. This was already part of the deployment of course and in this a key aspect of understanding if the deployment was healthy or not.

 

Gates

In order to add validation steps in our deployment process, we can leverage the concept of Gates in Azure DevOps ;

Gates allow automatic collection of health signals from external services, and then promote the release when all the signals are successful at the same time or stop the deployment on timeout. Typically, gates are used in connection with incident management, problem management, change management, monitoring, and external approval systems.

As most of the health parameters vary over time, regularly changing their status from healthy to unhealthy and back to healthy. To account for such variations, all the gates are periodically re-evaluated until all of them are successful at the same time. The release execution and deployment does not proceed if all gates do not succeed in the same interval and before the configured timeout. The following diagram illustrates the flow of gate evaluation where, after the initial stabilization delay period and three sampling intervals, the deployment is approved.

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Cloud Native Options – Personal experience when moving from Serverless to Containers

Introduction

Over the last months I have migrated VMchooser from a purely serverless implementation towards a container based one. The main reason for me to do this, was (like always) the learning effect that comes with such a refactoring. This post will run you through the various aspects that I encountered and hopefully give you a better understanding between both implementation options of a CloudNative architecture. I will divert a bit from the pure “X vs Y” comparison and also touch topics that typically come with the business discussions when thinking about both in terms of a strategic approach.

 

CloudNative?

First of all… In terms of semantics, there are some definitions floating around. When you look at the CNCF, then it seems to solely revolve around containers. Though when you look at Azure, the definition broadens up a bit… In reality, it depends a lot on the context of the person/organization you are speaking too. So do not be surprised if for some organizations the scope of CloudNative is “limited” to containers. Where for others this might be about leveraging the PaaS cloud services in a “Serverless” manner.

 

It kinda makes me think about the following “cartoon” (Source ; Simon Wardley) from a few years ago ;

Anyhow, be aware that there are different views on the semantics of “Cloud Native” and be crisp on your own when making conscious decisions.

 

Strategic Design Principle ; Portability

The design principle of software portability is high on the radar with about every organization I talk to. Here I always highlight two dimensions to take into consideration ;

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