Building an Automated Incident Intake & Tracking Pipeline for Enterprise Platforms
Role: Senior Systems Engineer / Platform Lead
Focus: Incident intake, platform reliability, operational clarity
Tools: Microsoft Forms, Power Automate, Jira (Cloud), Microsoft 365
The Problem
As our third-party platform ecosystem grew, incident reporting became increasingly fragmented.
Issues were being reported through:
- Ad hoc emails
- Slack/Teams messages
- Direct pings to engineers
- Inconsistent Jira tickets created manually (if at all)
This created several problems:
- No consistent intake format
- Missing critical details (impact, system, timelines)
- Delayed visibility for stakeholders
- Manual effort to create and route Jira tickets
- Limited traceability and reporting
We needed a single, reliable intake mechanism that balanced speed, structure, and low friction—without forcing users to learn Jira.
The Objective
Design and implement a lightweight but enterprise-ready incident intake pipeline that would:
- Capture incidents in a consistent format
- Automatically create structured Jira stories
- Apply governance (epic, labels, formatting) by default
- Notify the platform team immediately
- Reduce manual overhead while improving visibility
All while remaining simple enough for non-technical users.
The Solution
I designed and implemented an automated incident intake pipeline using Microsoft Forms and Power Automate, integrated directly with Jira via REST APIs.
High-Level Flow
- Microsoft Forms serves as the single intake point
- Power Automate orchestrates processing and validation
- Jira REST API creates standardized Story tickets
- Email notifications provide immediate team visibility
Intake Design Principles
The form was intentionally opinionated:
- Required: Summary, description, impact, affected system, contact
- Structured choices: Severity and system dropdowns for consistency
- Optional but encouraged: Business impact and attachments
- Low friction: No Jira knowledge required by submitters
This ensured every incident started with enough context to act.
Jira Automation Details
When a form is submitted, the flow:
- Authenticates securely to Jira using API tokens
- Creates a Story in the designated platform project
- Automatically associates the ticket with a predefined Epic
- Applies standardized labels for reporting
- Builds a structured description using Jira’s Atlassian Document Format (ADF), including:
- Reporter
- Impact
- Affected system
- Summary
- Detailed description
Ownership and assignment remain intentionally PM-controlled, preserving existing governance while eliminating intake friction.
Notification & Visibility
Once the Jira issue is created, the flow sends a notification email to the platform team containing:
- Incident summary
- Description
- Impact level
- Affected system
- Reporter
- Confirmation that a Jira ticket has been created
This ensures:
- Immediate awareness
- A single source of truth (Jira)
- No dependency on manual follow-ups
Why This Worked
This solution succeeded because it focused on operational clarity, not tooling novelty.
Key design decisions:
- Automate the boring, enforce the important
- Centralize intake, decentralize ownership
- Optimize for humans first, systems second
- Default to structure without adding friction
The result was higher-quality incident data, faster triage, and reduced cognitive load on engineers.
Business Impact
- Eliminated manual Jira ticket creation for incidents
- Improved consistency and completeness of incident data
- Reduced time-to-visibility for platform issues
- Enabled better reporting on incidents by system and severity
- Increased trust in the incident process across teams
Most importantly, the platform team could focus on resolution, not administration.
What I’d Extend Next
If scaling this further, the next logical enhancements would include:
- Automated attachment linking or ingestion into Jira
- Failure handling and alerting for API errors
- Duplicate detection and correlation
- SLA-based routing or prioritization
- Metrics dashboards (volume, severity trends, MTTR)
The foundation is intentionally flexible.
Why This Matters
At scale, platform reliability isn’t just about uptime—it’s about how fast the organization can see, understand, and respond to issues.
This system didn’t just automate a workflow.
It created clarity, consistency, and trust across teams.
That’s platform engineering.