FireBot is an AWS Lambda-powered Slack bot designed to streamline incident management for veterinary software teams. When Jira incident tickets are mentioned in Slack, FireBot automatically creates dedicated incident channels, provides AI-powered analysis, uploads relevant media, and guides reporters through providing complete investigation details.

• Smart Channel Creation: Automatically creates incident channels when Jira tickets (ISD-XXXXX) are mentioned
• Intelligent Naming: Channels follow the pattern incident-{ticket}-{date}-{hospital}
• User Invitation: Automatically invites ticket reporters and mentioning users to incident channels
• Deduplication: Prevents duplicate processing using both in-memory cache and DynamoDB
• Distributed Coordination: Uses DynamoDB for reliable incident processing across multiple instances

• Gemini Integration: Uses Google's Gemini AI to generate concise, actionable incident summaries
• Intelligent Parsing: Handles both plain text and Atlassian Document Format (ADF) descriptions
• Fallback Models: Automatic fallback between Gemini models (1.5-flash, 1.5-pro, pro) for reliability
• Model Mapping: Smart mapping of legacy model names to new versions

FireBot analyzes each ticket against 7 critical investigation items:

1. Issue replication in customer's application
2. Issue replication on Demo instance
3. Steps to reproduce
4. Screenshots provided
5. Problem start time
6. Practice-wide impact
7. Multi-practice impact

• Automatic Detection: Finds and downloads images/videos from Jira tickets
• Smart Upload: Uses modern Slack file upload API (files.getUploadURLExternal)
• Size Validation: Enforces file size limits (100MB) and validates image integrity
• Rich Context: Uploads include author information and source ticket references

• User Lookup: Finds ticket creators in Slack by email address
• Structured Requests: Provides specific, actionable requests for missing information
• Encouraging Tone: Uses supportive, collaborative messaging to reduce stress
• Contextual Analysis: Adapts requests based on available information

• Graceful Degradation: Individual feature failures don't break core functionality
• Comprehensive Logging: Detailed logging for troubleshooting and monitoring
• Duplicate Prevention: Smart caching with size management (1000 events max)
• Bot Message Filtering: Avoids processing its own messages and other bot responses

• Channel Summary: firebot summary - Generate comprehensive incident summaries using AI
• Duration Tracking: firebot time - Show how long the incident has been open
• Timeline Analysis: firebot timeline - Generate detailed timeline with response metrics
• Resolution Handling: firebot resolve - Mark incidents as resolved with automated Jira updates
• Smart Detection: Only responds to commands in incident channels
• AI-Powered Analysis: Uses Gemini to analyze channel history and provide insights

• AWS Lambda environment
• Slack workspace with bot permissions
• Jira Cloud instance with API access
• Google Cloud project with Gemini API access
• DynamoDB table for coordination (optional but recommended)

# Slack Configuration
SLACK_BOT_TOKEN=xoxb-your-slack-bot-token
SLACK_BOT_USER_ID=U1234567890  # Optional: helps prevent duplicate processing

# Jira Configuration  
JIRA_USERNAME=your-jira-email@company.com  # Legacy support
JIRA_API_TOKEN=your-jira-api-token        # Legacy support
FIREBOT_JIRA_USERNAME=your-jira-email@company.com  # Preferred
FIREBOT_JIRA_API_TOKEN=your-jira-api-token        # Preferred
JIRA_DOMAIN=yourcompany.atlassian.net
JIRA_HOSPITAL_FIELD=customfield_10297  # Hospital/practice field ID
JIRA_SUMMARY_FIELD=customfield_10250   # Summary field ID

# AI Configuration
GEMINI_API_KEY=your-gemini-api-key
GEMINI_MODEL=gemini-1.5-flash  # Optional: defaults to gemini-1.5-flash

# DynamoDB Configuration
DYNAMODB_TABLE_NAME=firebot-coordination  # Optional: defaults to firebot-coordination
DYNAMODB_REGION=us-east-2                # Optional: defaults to us-east-2

Your Slack app needs these OAuth scopes:

channels:read          # List channels
channels:write         # Create channels  
channels:manage        # Invite users to channels
chat:write            # Post messages
users:read.email      # Lookup users by email
users:read            # Get user information
files:write           # Upload media files
files:read            # Read file information
groups:history        # Read channel history for firebot commands
channels:history      # Read channel history for firebot commands

Create a DynamoDB table for distributed coordination:

# Deploy the CloudFormation template
aws cloudformation deploy \
  --template-file dynamodb-table.yaml \
  --stack-name firebot-coordination \
  --capabilities CAPABILITY_IAM

Add these permissions to your Lambda execution role:

{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Effect": "Allow",
      "Action": [
        "dynamodb:DescribeTable",
        "dynamodb:GetItem",
        "dynamodb:PutItem",
        "dynamodb:UpdateItem",
        "dynamodb:DeleteItem"
      ],
      "Resource": "arn:aws:dynamodb:*:*:table/firebot-coordination"
    }
  ]
}

Install the required Python packages:

pip install -r requirements.txt

FireBot uses a distributed, event-driven architecture to process incidents reliably:

graph TD
    A[Slack Event] -->|Message with ISD-XXXXX| B[AWS Lambda FireBot]
    B -->|Check Cache| C[In-Memory Cache]
    B -->|Check/Update Lock| D[DynamoDB]
    B -->|Fetch Ticket| E[Jira API]
    E -->|Ticket Data| B
    B -->|Generate Summary| F[Gemini AI]
    F -->|AI Analysis| B
    E -->|Media Files| G[Media Processing]
    G -->|Processed Files| B
    B -->|Create Channel| H[Slack API]
    B -->|Post Messages| H
    B -->|Upload Files| H
    B -->|Update Ticket| E
    I[FireBot Commands] -->|summary/time/timeline/resolve| B

Key Components:

• AWS Lambda: Serverless function that processes Slack events and coordinates incident response
• DynamoDB: Provides distributed locking and deduplication across multiple Lambda instances
• In-Memory Cache: Fast local cache for event deduplication within a Lambda instance
• Jira API: Source of incident ticket data and media attachments
• Gemini AI: Generates intelligent summaries and analyzes incident details
• Slack API: Creates channels, posts messages, and handles file uploads
• Media Processing: Validates and processes images/videos from Jira tickets

1. Trigger: User mentions a Jira ticket in any Slack channel

   "We have an issue with ISD-12345 affecting the login system"
   

2. Channel Creation: FireBot creates #incident-isd-12345-20250109-amc

3. AI Analysis: Generates comprehensive summary and checks investigation checklist

4. Media Processing: Downloads and uploads any screenshots/videos from the ticket

5. Creator Outreach: Invites ticket creator and provides specific guidance on missing information

Once in an incident channel, users can interact with FireBot:

firebot summary   # Generate comprehensive incident summary
firebot time      # Show incident duration
firebot timeline  # Generate detailed timeline with response metrics
firebot resolve   # Mark incident as resolved and post summary to Jira

Channel Creation Message:

🚨 **Welcome to the incident channel for ISD-12345!**

🔗 **Jira Ticket:** https://yourcompany.atlassian.net/browse/ISD-12345

I'm FireBot, your AI-powered incident management assistant. Here's what I can help you with:

🤖 **AI Commands Available:**
• `firebot summary` - Generate a comprehensive AI summary of the incident
• `firebot time` - Show how long the incident has been open
• `firebot timeline` - Generate a detailed timeline of events and response metrics
• `firebot resolve` - Mark incident as resolved and post summary to Jira ticket

Investigation Checklist Results:

@john Thanks for reporting incident ISD-12345! A developer is on the way to help. 
To help our development team investigate more efficiently, could you please provide:

• Steps to reproduce - Clear step-by-step instructions to reproduce this issue
• Problem start time - When did this issue first start occurring?
• Practice-wide impact - Is this affecting all users or specific team members?

This information will help us resolve the issue faster. Thanks for your collaboration! 🐾