Azure Devops provides multiple development collaboration tools. For this Workshop we will be using the following tools to create a high performant, resilient, self- healing pipeline:
Azure Pipelines: Creating CI/CD pipelines for deploying the test application. You can read more on Azure Devops Pipelines here.
Dynatrace is a Software Intelligence Platform for the Enterprise Cloud. Dynatrace provides automated, full stack monitoring powered by Artificial Intelligence. You can read more about Dynatrace here
The goal of this tutorial is having a full end-to-end Azure DevOps Pipeline (Staging, Approval, Production) that is fully monitored with Dynatrace. With Dynatrace injected into the pipeline we implement the following use cases:
- FullStack Monitor your Staging Environment
- Shift-Left: Automate Approve/Reject Promotion from Staging to Production based on Performance Data captured while running continuous performance tests
- FullStack Monitor your Production Environment
- Self-Healing: Automatic Deploy of previous revision in case Dynatrace detected problems in Production
Pre Reqs
- Sign up for Azure account. You can do it here.
- Sign up for Azure Devops. You can do it here.
- Sign up for Dynatrace trial (Free for 15 days). You can do it here.
Concepts
Quality Gate To effectively Shift Left and prevent sub optimal code from making it downstream in a pipeline.
Remediation as Code To fix / handle sub optimal code before it impacts users
Sample Application To demonstrate the Unbreakable Pipeline concept we use a simple node.js Sample application with a single webpage and some service endpoints. The application is coded to exibit different behavior for different Builds. Throughout the course of the workshop we will update the Build Name by changing the SimulateBuildNumber Variable in the pipelines.
| Build Number | Behavior |
|---|---|
| 1 | Run Normally without any issues |
| 2 | 50% of the requests return HTTP 500 |
| 3 | Run Normally without any issues |
| 4 | if Environment is Staging run normally, if Environment = Production 10% requests return HTTP 500 |
The workshop is self paced and the follow is:
1. Initial Preparation
2. Import the Project into Azure DevOps
3. Update name in Function Arm Template
4. Continous Integration (Build Pipeline)
5. Continous Deployment (Release Pipeline)
6. Remediation as Code