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Azure DevOps

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Reconcile Azure DevOps releases with ServiceNow change requests
Report
Cross-Connector

Check every release had an approved change

For operations teams who want Azure DevOps deployments matched to ServiceNow change requests, by asking their AI assistant.

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Reconcile Azure DevOps releases with ServiceNow change requests
Reconcile the Contoso Web production deployments from the last 30 days with ServiceNow change requests.
6 production deployments in 30 days. 4 had an approved change. - Covered: 4 deployments, for example CHG0030211, high confidence - Unapproved change: 1, CHG0030245, state New - No change found: 1, deployed 22 Oct Want the dates, deployers and release numbers for the last 2?
Azure DevOps
Sample figures. Your results come from your own account.
azure-devops-get-deployment
azure-devops-get-release
servicenow-get-change-request

On this page

The problem

The problem

The prompt

Who it's for

How it works

Tools used

Connector

Azure DevOps

Azure DevOps
Run it on your own Azure DevOps data.

Connect Azure DevOps, pick your AI tool and paste the prompt.

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The problem

Unapproved deployments are found late

Checking that every deployed release had an approved change is a manual cross check between Azure DevOps and ServiceNow. It takes time and tends to be skipped, so unapproved deployments are found late.

Without PopdockAI

  • Export deployments from Azure DevOps
  • Search ServiceNow for each change request
  • Check approval status by hand
  • Skip the check when time is short

With PopdockAI

  • Deployments and change requests are read for the window
  • Each deployment is paired with a change request
  • Rows are marked covered, unapproved or missing
  • Each match states its confidence, and nothing is created or edited

The prompt

Use this prompt

Copy it into any AI tool connected to PopdockAI. Swap the values in braces for your own.

Prompt
**Objective:** For Azure DevOps releases in project `{project}` deployed in the last `{lookback-days}` days (default 14), confirm a matching ServiceNow change request exists and was approved. If `{release-name}` is given, check only that release.

**Step 1: Read the deployments (azure-devops server)**

Call `azure-devops-get-deployment` with `project` = {project} and, if provided, `release-name` = {release-name}. Keep deployments with `completed-on` inside the lookback. Call `azure-devops-get-release` with `project` and `name` for each distinct release to get `description` and `created-by`.

**Step 2: Find the change request (servicenow server)**

For each release call `servicenow-get-change-request` with `short-description.contains` = the release name. Also search the release `description` text for a CHG number and fetch it with `number`. Check `planned-start-date`, `state` and `approval`.

**Step 3: Report**

A table: release, environment (`environment-name`), deployed on, `deployment-status`, change `number`, change `state`, `approval`, and a verdict: covered, change not approved, deployed outside the planned window, or no change found. Put unverdicted-as-covered rows first.

**Rules & Guidelines:**

* `azure-devops-get-deployment` and `azure-devops-get-release` are on the azure-devops server. `servicenow-get-change-request` is on the servicenow server.
* Read-only. Do NOT call `servicenow-add-change-request` or `servicenow-update-change-request`.

**Validation:**

* If no deployments are found, say so and stop.
* A name match alone is probable, not confirmed. State which kind of match each row has.

Who it's for

One answer, three teams that use it

Change managers

Catch deployments without approval

Unapproved and missing changes are listed, so they are dealt with before the next audit.

Which Fabrikam API production deployments this month had no approved change?

IT auditors

Evidence change control

A covered, unapproved and missing list with match confidence supports your audit testing.

Reconcile Northwind Portal deployments from last quarter with ServiceNow change requests.

Release managers

Check your releases followed process

Confirm each deployment you ran had its change approved.

Did every Contoso Web staging deployment in the last 14 days have a ServiceNow change?

How it works

What PopdockAI does when you ask

You give a release definition and window, and your AI assistant checks every deployment for an approved change. Change requests are never created or edited.

01

Ask

You give the release definition and the time window.

Your AI tool

02

Read

It reads the deployments and the ServiceNow change requests.

azure-devops-get-deployment
azure-devops-get-release
servicenow-get-change-request

03

Match

It pairs each deployment with a change request and rates the match.

No items found.

04

Report

You get covered, unapproved and missing, with confidence per row.

Your AI tool

What PopdockAI provides

The tools behind the answer

Ready made tools for Azure DevOps and one secure connection to your AI tool. No code, no exports.

get-data

azure-devops-get-deployment

Returns deployments records from the Azure DevOps connector. Use it to read and filter deployments across your Azure DevOps projects.
get-data

azure-devops-get-release

Returns releases records from the Azure DevOps connector. Use it to read and filter releases across your Azure DevOps projects.
get-data

servicenow-get-change-request

Returns change request records (type, state, risk, approval and planned window) from ServiceNow. Filter by number, type, state, risk, assignment group, assignee, short description text and planned start date range.
Read only.Nothing in Azure DevOps Changes

This report is built from Get data tools only. PopdockAI applies the row, field and parameter rules your admin sets, and every query is written to the audit trail.

How Popdock AI secures your data

The outcome

Every deployment checked for an approved change

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Related use cases

More ways to put this data to work

All Ramp use cases

One prompt template with infinite possibilities.

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Your AI assistant adapts its approach, tone, and capabilities to match each unique context while you maintain a single, manageable workflow.

Join forward-thinking companies that are transforming their operations with intelligent, secure AI automation.

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See Documentation