Azure DevOps Integration With Railtown.ai Ticketing System

by

Marwan Haddad

October 7, 2022

5 min

reads

Introduction

Are you sick of switching between tools when trying to keep track of customer support tickets?

With Railtown.ai, you can integrate your Azure DevOps records together with your customer support tickets to keep track of all relevant bugs, customer queries, and debugging efforts in one simple interface. Both your developer and customer support teams can work more efficiently and easily communicate while improving application performance and customer satisfaction.

Key Insights

In this guide, we will cover the following topics:

  • Benefits of Integrating Azure DevOps With railtown.ai Ticketing System
  • Keep Track of All Bugs
  • View Customer Support Conversations
  • Create a Single Source of Truth
  • Get More Comprehensive Insight for Debugging Errors
  • How To Integrate Azure DevOps With Railtown.ai Ticketing System

Benefits

By integrating your Azure DevOps together with Railtown.ai’s ticketing system and error monitoring, you can increase your team’s productivity and gather intelligent insights to improve your code.

Let’s take a look at some key ways in which this integration could improve your workflow.

Benefit 1 - Keep Track of All Bugs

By combining your engineering team’s work items in one place, you can make sure that no bugs slip through the cracks.

Railtown.ai can pull all of your development ticket information and add it into one simple and comprehensive interface. Once tickets are in the system, you can match each ticket to any other related inquiries and to the relevant code that’s producing errors within your applications.

Then, you can leverage Railtown.ai’s AI capabilities to gain full visibility into what may actually be going wrong with your code. Instead of depending on isolated incident reports, you can see all the connections between different error reports and customer complaints. That way, your engineers can push fixes to address the underlying causes of individual bugs.

Benefit 2 - View Customer Support Conversations

By integrating developer work items with customer support tickets, you can ensure that both departments are communicating to deliver the best outcomes to your end users.

Railtown.ai integrates with Azure DevOps to provide both your Engineering and Support Teams with full visibility and transparency onto ongoing progress and issues. Now your customer support team members can notify developers of bugs by creating corresponding Azure DevOps work items. At the same time, your developers can see all customer conversations associated with a bug or issue.

Through this enhanced communications your teams can truly collaborate to resolve issues as quickly as possible, without either team having to leave their familiar tools.

Benefit 3 - Create a Single Source of Truth

By synchronizing all the relevant information between your tools, your team can create a single source of truth while addressing any issues within your code.

Your team can judge the quality of your code with information such as:

  • Builds and deployments
  • Delivered tickets
  • Current bugs
  • New errors 
  • Repeated errors
  • Error rate.

With this comprehensive overview into the state of your application, your team can take any corrective measures that they need to resolve issues.

The whole resolution process becomes simpler as you can adapt Railtown.ai’s insights to your existing workflows. For example, you could:

  • Share comments or updates with other tools (such as Azure Boards) or parts of the Railtown.ai dashboard.
  • Track task status and edit other task details.
  • Auto-close support tickets once the DevOps work item is completed.

Benefit 4 - Get More Comprehensive Insight for Debugging Errors

Figure out the root cause of bugs and resolve issues with better insights.

Railtown.ai can pull together DevOps work items, error logs, and customer support tickets to then analyze how each error impacts your application and prioritizes them as they appear. These AI-generated insights can help you faster pinpoint the root cause of any error and its full scope within your code.

Our machine learning can help you figure out:

  • Whether an error is first-time or repeated
  • Which parts of your application are affected
  • Which environment an error originally came from
  • What is the full error history across deployments
  • Where the code may break.

Using this information, you can identify the source of an error in minutes instead of hours, all without leaving Railtown.ai’s dashboard.

How to Integrate

Screenshot of Railtown.ai showing an error bucket and how it is connected to active tickets that are related to this error / bug.


This is how error buckets are connected to both tickets for fixing it but also tickets that produced errors. Shows ticket name, assigned team member, status, change match.

Integration Steps

  1. Create a new “Service” hook under “Project Settings”
  1. Choose “Web Hooks” service
  2. Choose the Build completed trigger, your Build pipeline and a Build Status of Succeeded
  3. Go to your railtown.ai Project settings CI/CD section and expand the Azure DevOps CI/CD section
  4. Copy the Build Webhook
  5. Paste the Build Webhook into the Azure DevOps service hook URL
  6. Choose 2.0-preview.2 for the Resource Version and Finish creating your service hook
  1. Create a Service Connection
  1. create a new Service connection under Project Settings
  2. Choose the Generic service connection type
  3. Go to your railtown.ai Project settings CI/CD section and expand Azure DevOps CI/CD section and scroll down to the Deployment Integration section
  4. Copy the Deployment Webhook URL
  5. Paste the Deployment Webhook URL into the Server URL field in the New Generic service connection, enter a Service connection name and click Save
  1. Create a Release Post-deployment Gate
  1. Edit your release pipeline and click the icon to the right of your pipeline stage
  2. Turn on the switch for Gates
  3. Click the Add button and choose Invoke REST API
  4. copy the Headers and Body content from project configuration
  5. Go back to your post-deployment gate setup and choose Task version 1.*
  6. Enter a Display name
  7. Select the service connection you created earlier
  8. Paste in the Headers you copied from the railtown.ai configuration
  9. copy the Body from the railtown.ai configuration ensuring that you selected the environment that matches with your pipeline deployment
  10. Repeat the above steps for creating the post-deployment gate above for any other environments in your pipeline.

Conclusion

A full view into any bugs affecting your application as well as the customer complaints submitted can help both your engineering and support teams address issues faster and more efficiently. By integrating your Azure DevOps with Railtown’s ticketing system you can make sure that every bug is recorded, traced, and resolved once and for all.

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