Webhook and Jira Software integration

This AI-powered workflow transcribes Zoom/Google Meet recordings, extracts decisions and tasks using AI, then creates tickets in Jira/ClickUp/Linear and assigns them to team members automatically. How it works Trigger - Receives meeting recording URL via webhook or schedule Download Recording - Fetches audio/video file from Zoom/Google Meet Audio Extraction - Converts video to audio if needed using FFmpeg Transcription - Uses Whisper API to transcribe meeting audio Wait & Process - Allows transcription to complete Parse Transcript - Cleans and formats the transcription text AI Analysis - Claude extracts action items, decisions, owners Team Member Matching - Maps names to user IDs in project tools Create Tasks - Generates tickets in Jira/ClickUp/Linear Assign & Notify - Assigns tasks to team members and sends notifications Meeting Summary - Saves full summary to Google Drive/Notion Response - Returns processed action items and task links Setup Steps Import this workflow into your n8n instance Configure credentials: Zoom OAuth - For downloading Zoom recordings Google OAuth - For Google Meet recordings and Drive storage OpenAI API - For Whisper transcription service Anthropic API - For Claude AI analysis Jira/ClickUp/Linear API - For task creation Slack/Teams - For notifications (optional) Set up team member mapping in the config node Configure your project management tool preferences Activate the workflow Sample Trigger Payload { "meetingSource": "zoom", "recordingUrl": "https://zoom.us/rec/share/...", "meetingTitle": "Q1 Planning Meeting", "meetingDate": "2024-01-15", "attendees": ["[email protected]", "[email protected]", "[email protected]"], "projectKey": "PROJ-123", "taskTool": "jira", "defaultPriority": "medium", "autoAssign": true, "sendNotifications": true, "saveToNotion": false, "saveToDrive": true, "extractDecisions": true, "extractRisks": true, "dueDate": "2024-01-22" } Features Multi-platform support** (Zoom, Google Meet, MS Teams recordings) Accurate transcription** using OpenAI Whisper API AI-powered extraction** of action items, decisions, risks, and next steps Automatic task creation** in Jira, ClickUp, or Linear Smart assignment** - maps attendee names to task assignees Meeting summaries** - saves comprehensive notes to Drive/Notion Slack/Teams notifications** - alerts team members of new tasks Duplicate detection** - prevents creating duplicate tickets Priority detection** - AI assigns urgency levels to tasks

📘 Description This workflow is an AI-powered style look transfer and quality control pipeline designed for VFX and editorial production. It transforms a new shot brief and a hero reference image into multiple style-locked video variants, evaluates them against a predefined show style profile, and delivers only approved outputs to editorial—bridging the gap between creative direction consistency and automated production validation. ⚙️ Step-by-Step Flow The workflow begins with a webhook trigger that acts as the style transfer request intake layer, receiving a POST request containing the shot code, shot description, hero reference image, and optional show-specific style parameters. This input flows into a validation and normalization stage, where required fields are verified and a structured show style profile is extracted, including attributes such as color grading, contrast levels, grain texture, lighting mood, atmospheric style, and color temperature, along with QC thresholds for evaluation. The system then performs prompt engineering and expands the single shot brief into three distinct style-locked variants: a primary composition designed for editorial use, an alternate framing option offering a different perspective, and a stress test variant that pushes style boundaries to validate consistency limits. Each variation is tightly anchored to the hero reference image and enriched with detailed cinematic instructions to ensure strict adherence to the approved show look. At the core of the pipeline, an image-to-video generation layer constructs structured API requests and submits each variant as an independent job to the Seedance AI model, ensuring that all outputs remain visually consistent with the reference style. A polling mechanism continuously monitors each job at fixed intervals, allowing the workflow to proceed only after successful completion. Once rendering is complete, an automated QC engine evaluates each variant using measurable metrics such as contrast score, color match accuracy, and brightness variance, comparing them against predefined thresholds from the show style profile. Each variant is then assigned a QC grade and classified as either approved for editorial delivery or rejected for further review. A decision routing layer ensures that only approved variants move forward, while failed outputs trigger alerts for review without disrupting the pipeline. An aggregation layer then compiles all QC results into a structured report, summarizing approved and rejected variants along with their performance metrics and visual references. Finally, a multi-channel delivery system distributes the QC report and outputs to key stakeholders: a Slack message provides a quick overview for the team, a detailed HTML email is sent to editorial with full QC breakdown and style profile context, and a Jira task is created for tracking and review—ensuring transparency, consistency, and alignment across creative and production teams. 🚨 Error Handling • Global error trigger across the workflow • Instant Slack alerts with error details and timestamps • Prevents silent failures and ensures production reliability 🧩 Prerequisites • Seedance API (AI video generation) • Webhook integration (input trigger) • Slack OAuth2 (QC reporting) • Gmail OAuth2 (editorial delivery) • Jira API (task tracking) • Optional Telegram Bot (QC failure alerts) 💡 Key Benefits ✔ Ensures strict style consistency using hero reference anchoring ✔ Automated QC validation using measurable visual metrics ✔ Multiple style-locked variants for editorial flexibility ✔ Prevents incorrect outputs from reaching editorial ✔ Fully automated reporting and task tracking ✔ Scalable pipeline for episodic and film production 👥 Perfect For VFX supervisors and creative directors Editorial and finishing teams Look development and color grading pipelines Film and episodic production workflows AI-assisted style consistency and QC systems

Smart Partner API Usage Monitoring with Slack, Jira & Gmail Alerts This workflow monitors partner API usage in real time and triggers alerts based on usage thresholds. It validates incoming data, calculates usage percentage and routes actions using a Switch node. Slack notifications are sent at 80%, Jira tickets are created at 90% and critical alerts (Email + Jira + Slack) are triggered at 100%. Quick Implementation Steps Import the workflow into n8n Configure the Webhook node and test with sample data Add credentials for Slack, Jira and Gmail Update Slack channel ID, Jira project and email recipient Activate the workflow Send test payloads to verify all alert levels What This Workflow Does This workflow helps monitor partner API usage automatically and ensures timely alerts when usage reaches defined thresholds. It starts by receiving usage data through a webhook, validating the payload and calculating the usage percentage based on quota and consumption values. Once calculated, the workflow routes the data using a Switch node. At 80% usage, it sends an early warning Slack notification. At 90%, it escalates by creating a Jira ticket and notifying via Slack. When usage reaches 100%, it triggers a critical alert by sending an email, creating a Jira ticket and sending a Slack notification. This approach ensures better visibility, timely action and helps prevent service disruption. Who’s This For? SaaS platforms with API-based billing DevOps and Engineering teams Product and Platform teams Customer Success managers Businesses managing partner integrations Requirements n8n (Cloud or Self-hosted) Slack account with API access Jira Software Cloud account Gmail account (OAuth configured in n8n) API or system to send usage data via webhook How It Works & Setup Guide Setup Steps Webhook Setup Configure the Incoming Partner Usage Data node Accept POST requests Required fields: partner_id partner_name quota consumed timestamp Validate Payload The workflow checks for missing fields and invalid values Calculate Usage Calculates usage percentage from quota and consumed values Stops execution if usage is below 80% Switch Routing Routes workflow based on usage: 80% → Slack alert 90% → Jira + Slack 100% → Gmail + Jira + Slack Configure Integrations Slack: Set channel ID Jira: Set project and issue type Gmail: Set recipient email Test Workflow Send sample data to webhook Verify all alert paths Activate Enable workflow after testing How To Customize Nodes Webhook Node** → Change endpoint path or add authentication Validation Node** → Add more fields like plan or email Calculation Node** → Modify threshold logic Switch Node** → Adjust percentage ranges Slack Node** → Customize message format and channel Jira Node** → Update ticket structure Gmail Node** → Modify email subject, HTML, recipients Add-ons & Enhancements Add deduplication to avoid repeated alerts Store usage data in database or Google Sheets Send alerts to multiple email recipients Integrate with CRM or billing systems Add cooldown or rate limiting Enrich partner data using external APIs Use Case Examples Monitor API usage for partners in SaaS platforms Prevent service downtime due to overuse Trigger internal review processes automatically Automate partner upgrade discussions Improve operational visibility for teams This workflow can be adapted for many other automation use cases as well. Troubleshooting Guide | Issue | Possible Cause | Solution | | ----------------------- | -------------------------------- | ----------------------------------- | | Workflow not triggering | Webhook not called | Verify webhook URL and method | | Invalid payload error | Missing fields | Ensure required fields are included | | Slack message not sent | Incorrect channel or credentials | Reconfigure Slack node | | Jira ticket not created | Wrong project or API issue | Verify Jira credentials | | Email not sent | Gmail OAuth issue | Reconnect Gmail account | | Incorrect usage % | Invalid data format | Ensure numeric values | Need Help? If you need help setting up or customizing this workflow, our n8n workflow development team at WeblineIndia can assist you in building scalable automation solutions, integrating APIs and optimizing workflows using n8n. Whether you need custom workflow development, advanced automation features or production-ready deployment, we are here to help you build reliable automation systems.

📘 Description This workflow is an end-to-end AI video generation, review, and delivery pipeline. It takes a plain-text creative prompt via webhook, generates a video using an AI model, continuously checks job status until completion, and then automates the entire post-production workflow—metadata creation, Jira ticketing, Slack notifications, and final email delivery with the video attached. It ensures zero manual coordination between creative, ops, and delivery teams. The process begins with a webhook trigger that acts as the input layer, receiving a request containing the prompt text, record ID, and user email. This input is then passed through a prompt sanitisation step using a code node, where the text is cleaned and escaped to prevent API errors or malformed payloads. Once sanitised, the system submits a video generation request via an HTTP call to the AI video model (Seedance API). A polling loop is then initiated, which waits for 20 seconds between each cycle and repeatedly checks the job status using HTTP requests until the status is marked as “succeeded.” After completion, the system extracts the video output through a metadata builder, parsing the response to structure key details such as the video URL, job ID, resolution, duration, timestamp, and AI-generated tags including review status. Following this, a Jira review ticket is automatically created to log the generated video within the review workflow. Simultaneously, a Slack notification is sent to the VFX supervisor, containing the Jira ticket reference, video URL, status, and associated metadata. The system then downloads the final video file from the generated URL and completes the process by sending a professional email via Gmail to the requester, including the video as an attachment along with job details and the Jira reference. 🚨 Error Handling Flow • Global error trigger catches failures • Sends Slack alert instantly • Prevents silent pipeline breakdown 🧩 Prerequisites • AI video API (Seedance or similar) • Jira Cloud credentials • Slack OAuth2 • Gmail OAuth2 • Webhook endpoint integration 💡 Key Benefits ✔ Fully automated creative pipeline (idea → video → delivery) ✔ Async job handling with polling loop ✔ Built-in review workflow (Jira + Slack) ✔ Zero manual coordination required ✔ Production-ready structure with metadata tracking ✔ Fault-tolerant with global error alerts 👥 Perfect For AI video production teams Content studios / VFX pipelines Marketing creative automation UGC/ad generation workflows Internal media ops systems

Eliminate the manual chaos of HR and legal document management. This workflow automates the transition from a raw document upload to a structured, audit-ready archive by combining UploadToURL for instant CDN hosting, Google Drive for long-term storage, and Airtable for status tracking and database management. 🎯 What This Workflow Does Transforms loose document scans into a structured corporate filing system: 📝 Captures Legal Assets - Receives signed contracts or IDs via mobile scan (binary) or remote URL. 🛡️ Duplicate Prevention - Checks Airtable first to ensure a contract isn't already filed for that specific Employee ID. ☁️ Instant CDN Hosting - UploadToURL hosts the document to provide a high-speed link for immediate HR review. 📁 Smart Folder Logic - Automatically navigates or creates a structured Google Drive path: HR/Contracts/{Year}/{Department}/{EmployeeName}/. 🗃️ Database Synchronization - Updates (or creates) an Airtable record to tick "Contract Received," logging both the Drive URL and the CDN backup. 📧 Automated Confirmation - Sends a professional HTML email to HR and the employee with access links and filing metadata. ✨ Key Features UploadToURL Integration**: Provides a redundant, accessible CDN link stored alongside your primary Drive storage for total data reliability. Auto-Nomenclature**: Renames files using a strict audit-ready format: {EmployeeID}{LastName}{Type}_{Date}.pdf. Intelligent Folder Creation**: Never manually create a folder again; the workflow builds the entire hierarchy on the fly. Audit Trail Generation**: Captures "Filed By," "Filed At," and unique "Upload IDs" for every document. Conflict Handling**: Built-in 409 Conflict logic prevents accidental overwrites or double-filing of critical legal papers. 💼 Perfect For HR Teams**: Managing onboarding documents and employment contracts at scale. Legal Departments**: Archiving NDAs, vendor agreements, and compliance certifications. Small Businesses**: Moving away from "loose files in folders" to a searchable, automated database. Remote Teams**: Enabling employees to "upload and forget" their paperwork via a simple link. 🔧 What You'll Need Required Integrations UploadToURL** - To host documents and provide public CDN backup links. n8n Community Node** - n8n-nodes-uploadtourl must be installed. Google Drive** - OAuth2 credentials for secure document storage. Airtable** - Personal Access Token to manage your employee/document database. Gmail / SMTP** - To send automated filing confirmations. Configuration Variables GDRIVE_ROOT_FOLDER_ID: The ID of your main HR folder in Google Drive. AIRTABLE_BASE_ID: Your specific Airtable base for HR/Legal tracking. 🚀 Quick Start Import Template - Copy the JSON and import it into your n8n workspace. Install Node - Ensure the UploadToURL community node is active. Set Credentials - Link your UploadToURL, Google Drive, Airtable, and Gmail accounts. Define Variables - Set your Root Folder ID and Airtable Base details in n8n variables. Test the Pipeline - Send a test POST with a sample PDF to the Webhook URL. Activate - Enable the workflow to begin hands-free archiving. 🎨 Customization Options Expiration Alerts**: Add a node to calculate 1-year expiry dates and set an automated reminder in Slack. OCR Processing**: Integrate an OCR step to read the content of scans and verify names automatically. Watermarking**: Add a "Confidential" or "Draft" watermark to documents before they are uploaded to the CDN. Multi-Base Routing**: Route documents to different Airtable bases depending on the "Department" field. 📈 Expected Results 100% Consistency** in file naming and folder structures across the entire organization. Zero manual data entry**—employee records and checkboxes update automatically. Audit-ready in minutes**: Every file has a timestamped trail and redundant storage links. Instant Accessibility**: HR can view documents via the CDN link before Drive permissions even propagate. 🏆 Use Cases High-Growth Onboarding A startup hiring 20 people a month can automate all contract filings, ensuring the "Contract Received" flag is always accurate for payroll. Compliance Audits When auditors ask for specific contracts, use the Airtable "Structured Filename" column to find and share the relevant Drive or CDN links in seconds. Field Service Scans Technicians in the field can upload signed site reports via a mobile app; the workflow handles the filing and notifies the office immediately. 💡 Pro Tips Folder IDs**: You can find your GDRIVE_ROOT_FOLDER_ID by looking at the last string in the URL when you are inside that folder in your browser. Structured JSON**: Use the returned auditTrail object to build a log of all uploads in a separate "Master Audit" spreadsheet. Employee IDs**: If no ID is provided, the workflow generates a temporary one using a timestamp to ensure the archive never breaks. Ready to secure your document pipeline? Import this template and connect UploadToURL to build a world-class archiving system in under 20 minutes. Need help with Airtable field mapping? The workflow includes detailed sticky notes explaining the exact field names required for the automation to run.

⚖️ HR Sovereign: AI-Powered Onboarding Hub A high-fidelity employee onboarding engine: Intake → Role-Based Enrichment → AI Personalization → IT Provisioning. ⚙️ Core Sovereign Logic Enrichment:** Auto-classifies Tech, Sales, and Leadership roles to drive specific logic tracks. Intelligence:* Uses AI Agent (GPT-4)* to generate personalized welcome messaging based on job DNA. Atomization:* Merge PDF* node assembles role-specific policies and benefits into a single high-res package. Provisioning:* Dynamically generates Jira hardware/access tickets and Notion* tracking dashboards. Delivery:* Sends branded HTML emails via Gmail and announces hires on Slack*. 📋 Setup & Prerequisites Intake: Connect your HRIS (BambooHR/Workday) to the Webhook URL. Assets: Organize Drive folders into "Technical", "Leadership", and "Standard" templates. Tracking: Connect your Notion Onboarding Database and Jira IT Project. Metrics: Time_to_Provision, Engagement_Score, Document_Integrity_Hash.

Complete security workflow from vulnerability detection to automated remediation, with severity-based routing and full organizational context from Port's catalog. This template provides end-to-end lifecycle management including automatic Jira ticket creation with appropriate priority, AI-powered remediation planning, and Claude Code-triggered fixes for critical vulnerabilities. The full guide is available here. How it works The n8n workflow orchestrates the following steps: Webhook trigger**: Receives vulnerability alerts from security scanners (Snyk, Wiz, SonarQube, etc.) via POST request. Port context enrichment**: Uses Port's n8n node to query your software catalog for service metadata, ownership, environment, SLA requirements, and dependencies related to the vulnerability. AI remediation planning**: OpenAI analyzes the vulnerability with Port context and generates a remediation plan, determining if automated fixing is possible. Severity-based routing**: Routes vulnerabilities through different paths based on severity level: Critical: Jira ticket (Highest priority) → Check if auto-fixable → Trigger Claude Code fix → Slack alert with fix status High: Jira ticket (High priority) → Slack notification to team channel Medium/Low: Jira ticket only for tracking Jira integration**: Creates tickets with full context including vulnerability details, affected service information from Port, and AI-generated remediation steps. Claude Code remediation**: For auto-fixable critical vulnerabilities, triggers Claude Code via Port action to create a pull request with the security patch, referencing the Jira ticket. Slack notifications**: Sends contextual alerts to the appropriate team channel (retrieved from Port) with Jira ticket reference and remediation status. Prerequisites You have a Port account and have completed the onboarding process. Services and repositories are cataloged in Port with ownership information. Your security scanner (Snyk, Wiz, SonarQube) can send webhooks. You have a working n8n instance (Cloud or self-hosted) with Port's n8n custom node installed. Jira Cloud account with appropriate project permissions. Slack workspace with bot permissions to post messages. OpenAI API key for remediation planning. Setup Register for free on Port.io if you haven't already. Create the Context Retriever Agent in Port following the guide. Import the workflow and configure credentials (Port, Jira, Slack, OpenAI, Bearer Auth). Select your Jira project in each Jira node (Critical, High, Medium/Low). Update default-organization/repository with your default repository for Claude Code fixes. Point your security scanner webhook to the workflow URL. Test with a sample vulnerability payload. ⚠️ This template is intended for Self-Hosted instances only.

Description Automatically detect and escalate Product UAT critical bugs using AI, create Jira issues, notify engineering teams, and close the feedback loop with testers. This workflow analyzes raw UAT feedback submitted via a webhook, classifies it with an AI model, validates severity, and automatically escalates confirmed critical bugs to Jira and Slack. Testers are notified, and the original webhook receives a structured response for full traceability. It is designed for teams that want fast, reliable critical bug handling during UAT without manual triage. Context During Product UAT and beta testing, critical bugs are often buried in unstructured feedback coming from forms, Slack, or internal tools. Missing or delaying these issues can block releases and create friction between Product and Engineering. This workflow ensures: Faster detection of critical bugs Immediate escalation to engineering Clear ownership and visibility Consistent communication with testers It combines AI-based classification with deterministic routing to keep UAT feedback actionable and production-ready. Who is this for? Product Managers running UAT or beta programs Project Managers coordinating QA and release readiness Engineering teams who need fast, clean bug escalation Product Ops teams standardizing feedback workflows Any team handling high-volume UAT feedback Perfect for teams that want speed, clarity, and traceability during UAT. Requirements Webhook trigger (form, Slack integration, internal tool, etc.) OpenAI account (for AI triage) Jira (critical bug tracking) Slack (engineering alerts) Gmail or Slack (tester notifications) How it works Trigger The workflow starts when UAT feedback is submitted via a webhook. Normalize & Clean Incoming data is normalized (tester, build, page, message) and cleaned to ensure a consistent, AI-ready structure. AI Triage & Validation An AI model analyzes the feedback and returns a structured triage result (type, severity, summary, confidence), which is parsed and validated. Critical Bug Escalation Validated critical bugs automatically: create a Jira issue with full context trigger an engineering Slack alert Closed Loop The tester is notified via Slack or email, and the workflow responds to the original webhook with a structured status payload. What you get Automated critical bug detection during UAT Instant Jira ticket creation Real-time engineering alerts in Slack Automatic tester communication Full traceability via structured webhook responses About me : I’m Yassin a Product Manager Scaling tech products with a data-driven mindset. 📬 Feel free to connect with me on Linkedin

Description Automatically triage Product UAT feedback using AI, route it to the right tools and teams, and close the feedback loop with testers, all in one workflow. This workflow analyzes raw UAT feedback, classifies it (critical bug, feature request, UX improvement, or noise), validates AI confidence, escalates when human review is needed, and synchronizes everything across Jira, Slack, Notion, Google Sheets, and email. Context Product teams often receive unstructured UAT feedback from multiple sources (forms, Slack, internal tools), making triage slow, inconsistent, and error-prone. This workflow ensures: Faster bug detection Consistent categorization Zero feedback lost Clear accountability between Product, Engineering, and Design It combines AI automation with human-in-the-loop control, making it safe for real production environments. Who is this for? Product Managers running UAT or beta programs Project Managers coordinating QA and release validation Product Ops / PMO teams Engineering teams who want faster, cleaner bug escalation Any team managing high-volume UAT feedback Perfect for teams that want speed without sacrificing control. Requirements Webhook trigger (form, internal tool, Slack integration, etc.) OpenAI account (for AI triage) Jira (bug tracking) Slack (team notifications) Notion (product roadmap / UX backlog) Google Sheets (UAT feedback log) Gmail (tester & manual review notifications) How it works Trigger The workflow starts when UAT feedback is submitted via a webhook (form, Slack, or internal tool). Normalize & Clean Incoming data is normalized into a consistent structure (tester, build, page, message) and cleaned to be AI-ready. AI Triage An AI model analyzes the feedback and returns: Type (Critical Bug, Feature Request, UX Improvement, Noise) Severity & sentiment Summary and suggested title Confidence score Quality Control If the AI output is unreliable (low confidence or parsing error), the feedback is automatically routed to manual review via email and Slack. Routing & Actions If confidence is sufficient: Critical Bugs → Jira issue + Engineering Slack alert Feature Requests → Notion roadmap UX Improvements → Design / UX tracking Noise → Archived but traceable Closed Loop The tester is notified via Slack or email, and the workflow responds to the original webhook with a structured status payload. What you get One unified UAT triage system Faster bug escalation Clean product and UX backlogs Full traceability of every feedback Automatic tester communication Safe AI usage with human fallback About me : I’m Yassin a Product Manager Scaling tech products with a data-driven mindset. 📬 Feel free to connect with me on Linkedin

Provision new employee accounts to Google Workspace, Slack, Jira, and Salesforce This workflow streamlines the employee onboarding process by automatically provisioning user accounts across your organization's tech stack. By connecting HR input to IT operations, it eliminates manual data entry, reduces errors, and ensures new hires have access to the right tools from day one. Depending on the employee's department, the workflow intelligently routes the provisioning process to create specific accounts (e.g., Jira for Engineering, Salesforce for Sales) alongside standard company-wide access. Who is it for IT Administrators** looking to automate identity management and access provisioning. HR Operations Managers** who want to speed up the onboarding handover process. Startup Founders** needing a scalable way to manage new hire accounts without expensive SaaS management tools. How it works Data Intake: The workflow is triggered by a Webhook (connected to a form like Typeform, Google Forms, or BambooHR) containing the new hire's details. Configuration: A central "Set" node establishes global variables, such as the default temporary password, welcome email subject, and the main Slack channel ID. Core Provisioning: It simultaneously creates a Google Workspace account and invites the user to a general Slack channel. Department Routing: A generic logic switch checks the department field: If Engineering: It creates a Jira user. If Sales: It creates a Salesforce user. Notification: Once all accounts are successfully provisioned, the workflow uses a generic email service (Gmail node) to send a welcome email to the new employee with their login details. How to set up Credentials: You will need to configure credentials for the following nodes: Google Workspace Admin, Slack API, Jira Software, Salesforce, and Gmail (or your preferred email provider). Configuration: Open the node named ⚙️ CONFIGURATION. Update the Slack_Channel_ID (where new users are invited) and the Default_Password to match your company's security policy. Webhook: Copy the Webhook URL from the start node and add it to your HR form or applicant tracking system. Requirements n8n:** Version 1.0 or later recommended. Access:** Admin privileges for Google Workspace, Slack, Jira, and Salesforce to generate the necessary API keys/tokens. How to customize the workflow Add Departments:** Edit the "Check Department" Switch node to add routes for Marketing, Finance, etc., and connect them to relevant apps (e.g., HubSpot, Xero). Change Notification:** Swap the Gmail node for Microsoft Outlook or Slack DM depending on how you notify managers. Enhance Security:** Add a step to force a password reset on the first login if the identity provider supports it.

Real-Time Uptime Alerts to Jira with Smart Slack On-Call Routing This workflow automatically converts uptime monitoring alerts received via webhook into Jira incident tasks and intelligently notifies an available on-call team member on Slack based on their real-time presence status. It ensures critical service outages never go unnoticed by selecting an active responder and sending a detailed direct message immediately. ⚡ Quick Implementation Steps Import the workflow JSON into n8n. Configure your Webhook, Slack, and Jira credentials. Update the IF node to filter for status = down (already configured). Set the Jira project and issue type as required. Connect your Slack on-call channel. Activate the workflow and send a test alert using Postman or your monitoring tool. What It Does This automation listens for incoming alerts from any uptime monitoring service. When a system or service goes down, the workflow instantly validates whether the alert is critical (status = down). Once validated, it automatically creates a detailed Jira Task containing all relevant service details such as timestamp, downtime duration, error code, customer impact and priority. After the Jira incident is created, the workflow retrieves a list of all members from a dedicated Slack on-call rotation channel. It checks each member’s Slack presence (active, away, offline) and uses smart selection logic to choose the best person to notify. The selected team member then receives a richly formatted direct Slack message containing all incident details and a link to the Jira ticket. This ensures the alert is not only logged properly but also reaches the right responder at the right time. Who’s It For This workflow is perfect for: DevOps teams managing uptime & system reliability. Support teams responsible for incident response. SRE teams using Jira and Slack. Organizations with an on-call rotation setup. Teams wanting automated escalation for downtime alerts. Requirements to Use This Workflow n8n installed** (self-hosted or cloud) Slack API credentials** with permission to read user presence and send direct messages Jira Software Cloud** credentials allowing issue creation A monitoring system** capable of sending webhook alerts (e.g., UptimeRobot, Uptime Kuma, StatusCake, custom system, etc.) Access to a Slack channel that includes your on-call rotation members How It Works & How to Set Up Step 1: Receive Alert from Uptime Monitoring Tool The workflow starts with the Webhook node (Receive Uptime Alert). Your monitoring tool must send a POST request with JSON payload including fields like: serviceName status timestamp customerImpact errorCode priority etc. Step 2: Filter for Critical Status The IF node (Filter for Critical Status) checks: Only when the service is down does the workflow continue to create a Jira incident. Step 3: Create Jira Incident Task The Create New Jira Incident node generates a Jira Task with: Summary: serviceName + timestamp Description: dynamic fields based on the alert payload Set your Jira Project and Issue Type as needed. Step 4: Fetch Slack On-Call Channel Members The workflow calls Slack API to retrieve all user IDs in a designated channel (e.g., #on-call-team). Step 5: Loop Through Each Member Split In Batches Node** loops each Slack member individually. For each user, their Slack presence is fetched using: Step 6: Build Final Data for Each User The Set node (Collect & Set Final Data) stores: presence member ID service details Jira ticket ID downtime info and more Step 7: Select the Best On-Call User A custom Code node uses presence-based logic: Selection Logic If one or more users are active → randomly pick one active user. If only one user is active → pick that user. If no users are active → default to the first member from the channel. This ensures you always get a responder. Step 8: Notify Selected User The Slack Notify Node sends a formatted direct message with: service status downtime duration error code customer impact Jira ticket link priority The selected on-call responder receives everything they need to act immediately. How to Customize Nodes Webhook Node Change the path to something meaningful (e.g., /uptime-alerts). Customize expected fields based on your monitoring tool's payload. IF Node Modify status condition for: "critical" "error" or multiple conditions Jira Node You can customize: Issue type (Incident, Bug, Task) Priority field mapping Project ID Custom fields or labels Slack Retrieval Node Change the channel to your team's actual on-call rotation channel. Slack Message Node Modify message formatting, tone, emojis, or add links. Add @mentions or tags. Include escalation instructions. Add-Ons (Optional Extensions) Enhance the workflow by adding: Escalation Logic If the selected user doesn’t respond within X minutes, notify next user. PagerDuty / OpsGenie Integration Trigger paging systems for SEV-1 incidents. Status Page Updates Automatically update public status pages. Auto-Resolution When service status returns to up, automatically: Update Jira ticket Notify the team Close the incident Logging & Analytics Store incidents in Google Sheets, Notion, or a database. Use Case Examples This workflow can support multiple real-world scenarios: Website Uptime Monitoring If your main website goes down, instantly create a Jira incident and notify your on-call engineer. API Downtime Alerting When an API endpoint fails health checks, alert active developers only. Microservices Monitoring Each microservice alert triggers a consistent, automated incident creation and notification. Infrastructure Failure Detection When servers, containers, or VMs become unreachable, escalate to your infrastructure team. Database Performance Degradation If DB uptime drops or error rate spikes, create a Jira ticket and ping the database admin. And many more variations of outage, error, and performance monitoring events. Troubleshooting Guide | Issue | Possible Cause | Solution | |-------|----------------|----------| | Workflow not triggering | Webhook URL not updated in monitoring tool | Copy n8n webhook URL and update in monitoring source | | No Jira ticket created | Invalid Jira credentials or missing project permissions | Reauthorize Jira credentials and verify permissions | | Slack users not found | Wrong channel ID or bot not added to channel | Ensure bot is invited to the Slack channel | | Slack presence not returning | Slack app lacks presence permission (users:read.presence) | Update Slack API scopes and reinstall | | No user receives notification | Presence logic always returns empty list | Test Slack presence API and verify real-time presence | | Wrong user selected | Intended selection logic differs | Update the JS logic in the code node | | Jira fields not populated | Alert payload fields missing | Verify webhook payload structure and match expected fields | Need Help? If you need assistance setting up this workflow, customizing integrations, building escalations or extending the logic with add-ons — WeblineIndia is here to help. We can assist with: Custom Slack/Jira/Monitoring automation On-call rotation logic enhancements Cloud deployment & workflow optimization Any custom n8n automation Production-grade monitoring workflows 👉 Contact WeblineIndia for professional support, implementation and custom workflow development.

Complete incident workflow from detection through resolution to post-mortem, with full organizational context from Port's catalog. This template handles both incident triggered and resolved events from PagerDuty, automatically creating Jira tickets with context, notifying teams via Slack, calculating MTTR, and using Port AI Agents to schedule post-mortem meetings and create documentation. How it works The n8n workflow orchestrates the following steps: On Incident Triggered: PagerDuty webhook — Receives incident events from PagerDuty via POST request. Event routing — Routes to triggered or resolved flow based on event type. Port context enrichment — Uses Port's n8n node to query your software catalog for service context, on-call engineers, recent deployments, runbooks, and past incidents. AI severity assessment — OpenAI assesses severity based on Port context and recommends investigation actions. Escalation routing — Critical incidents automatically escalate to leadership Slack channel. Jira ticket creation — Creates incident ticket with full context, investigation checklist, and recommended actions. Team notification — Notifies the team's Slack channel with incident details and resources. On Incident Resolved: Port context extraction — Gets post-incident context from Port including stakeholders and documentation spaces. MTTR calculation — Calculates mean time to resolution from incident timestamps. Post-mortem generation — AI generates a structured post-mortem template with timeline. Port AI Agent scheduling — Triggers Port AI Agent to schedule post-mortem meeting, invite stakeholders, and create documentation. Resolution notification — Notifies team with MTTR, post-mortem document link, and meeting details. Metrics logging — Logs MTTR metrics back to Port for service reliability tracking. Setup [ ] Register for free on Port.io [ ] Configure Port with services, on-call schedules, and deployment history [ ] Set up Port AI agents for post-mortem scheduling [ ] Connect PagerDuty webhook for incident events [ ] Configure Jira project for incident tickets (use project key 'INC' or customize) [ ] Set up Slack channels for alerts (#incidents and #leadership-alerts) [ ] Add OpenAI credentials for severity assessment [ ] Test with a sample incident event [ ] You should be good to go! Prerequisites You have a Port account and have completed the onboarding process. Port's integrations are configured (GitHub, Jira, PagerDuty if available). You have a working n8n instance (Cloud or self-hosted) with Port's n8n custom node installed. PagerDuty account with webhook capabilities. Jira Cloud account with appropriate project permissions. Slack workspace with bot permissions to post messages. OpenAI API key for severity assessment and post-mortem generation. ⚠️ This template is intended for Self-Hosted instances only.

Webhook from IoT Devices → Jira Maintenance Ticket → Slack Factory Alert This workflow automates predictive maintenance by receiving IoT machine-failure webhooks, creating Jira maintenance tickets, checking technician availability in Slack and sending the alert to the correct Slack channel. If an active technician is available, the system notifies the designated technician channel; if not, it escalates automatically to your chosen emergency/escalation channel. ⚡ Quick Implementation: Start Using in 10 Seconds Import the workflow JSON into n8n. Add Slack API credentials (with all required scopes). Add Jira Cloud credentials. Select Slack channels for: Technician alerts Emergency/escalation alerts Deploy the webhook URL to your IoT device. Run a test event. What It Does This workflow implements a real-time predictive maintenance automation loop. An IoT device sends machine data — such as temperature, vibration and timestamps — to an n8n webhook whenever a potential failure is detected. The workflow immediately evaluates whether the values exceed a defined safety threshold. If a failure condition is detected, a Jira maintenance ticket is automatically created with all relevant machine information. The workflow then gathers all technicians from your selected Slack channel and checks each technician’s presence status in real time. A built-in decision engine chooses the first available technician. If someone is active, the workflow sends a maintenance alert to your technician channel. If no technicians are available, the workflow escalates the alert to your chosen emergency channel to avoid operational downtime. This eliminates manual monitoring, accelerates response times and ensures no incident goes unnoticed — even if the team is unavailable. Who’s It For This workflow is ideal for: Manufacturing factories Industrial automation setups IoT monitoring systems Warehouse operations Maintenance & facility management teams Companies using Jira + Slack Organizations implementing predictive maintenance or automated escalation workflows Requirements to Use This Workflow You will need: An n8n instance (Cloud or Self-hosted) Slack App with the scopes: users:read users:read.presence channels:read chat:write Jira Cloud credentials (email + API token) Slack channels of your choice for: Technician alerts Emergency/escalation alerts IoT device capable of POST webhook calls Machine payload must include: machineId temperature vibration timestamp How It Works & How To Set Up 🔧 High-Level Workflow Logic IoT Webhook receives machine data. IF Condition checks whether values exceed safety thresholds. Jira Ticket is created with machine details if failure detected. Slack Channel Members are fetched from your selected technician channel. Loop Through Technicians to check real-time presence. Code Node determines: first available (active) technician or fallback mode if none available IF Condition checks technician availability. Slack Notification is sent to: your chosen technician channel if someone is available your chosen emergency/escalation channel if no one is online 🛠 Step-by-Step Setup Instructions Import Workflow: n8n → Workflows → Import from File → Select JSON. Configure Slack: Add required scopes (users:read, users:read.presence, channels:read, chat:write) and reconnect credentials. Select Slack Channels: Choose any Slack channels you want for technician notifications and emergency alerts—no fixed naming is required. Configure Jira: Add credentials, select project and issue type, and set priority mapping if needed. Deploy Webhook: Copy the n8n webhook URL and configure your IoT device to POST machine data. Test System: Send a test payload to ensure Jira tickets are created and Slack notifications route correctly based on technician availability. This setup allows real-time monitoring, automated ticket creation and flexible escalation — reducing manual intervention and ensuring fast maintenance response. How To Customize Nodes Webhook Node Add security tokens Change webhook path Add response message IF Node (Threshold Logic) Lower/raise temperature threshold Change OR to AND Add more conditions (humidity, RPM, pressure) Jira Node Customize fields like summary, labels or assign issues based on technician availability Slack Presence Node Add DND checks Treat “away” as “available” during night shift Combine multiple channels Code Node Randomly rotate technicians Pick technician with lowest alert count Keep a history log Add-Ons SMS fallback notifications (Twilio) WhatsApp alerts Telegram alerts Notify supervisors via email Store machine failures into Google Sheets Push metrics into PowerBI Auto-close Jira tickets after normalizing machine values Create a daily maintenance report Use Case Examples Overheating Machine Alert – Detect spikes and notify technician instantly. Vibration Pattern Anomaly Detection – Trigger early maintenance before full breakdown. Multi-Shift Technician Coverage – Automatically switch to emergency mode when no technician is online. Factory Night-Shift Automation – Night alerts automatically escalate without manual verification. Warehouse Robotics Malfunction – Sends instant Slack + Jira alerts when robots overheat or jam. Troubleshooting Guide | Issue | Possible Cause | Solution | | ----------------------------- | ----------------------------------- | -------------------------------------------- | | Webhook returns no data | Wrong endpoint or method | Use POST + correct URL | | Slack presence returns error | Missing Slack scopes | Add users:read.presence | | Jira ticket not created | Invalid project key or credentials | Reconfigure Jira API credentials | | All technicians show offline | Wrong channel or IDs | Ensure correct channel members | | Emergency alert not triggered | Code node returning incorrect logic | Test code with all technicians set to “away” | | Slack message fails | Wrong channel ID | Replace with correct Slack channel | Need Help? If you need help customizing this workflow, adding new automation features, connecting additional systems or building enterprise IoT maintenance solutions, our n8n automation development team at WeblineIndia team can help. We can assist with: Workflow setup Advanced alert logic Integrating SMS / WhatsApp / Voice alerts Custom escalation rules Industrial IoT integration Reach out anytime for support or enhancements.

Snyk Vulnerability Automation Workflow with Webhook, Jira, Slack & Airtable This workflow receives vulnerability data(e.g., Snyk, Dependabot or any security scanner) from Snyk through a webhook, standardizes and validates the payload, checks Jira for duplicates using a unique vulnerability key, and either updates an existing Jira issue or creates a new one. It also sends real-time alerts to Slack and stores every new vulnerability in Airtable for reporting and auditing. The workflow ensures fast triage, prevents duplicate Jira tickets and centralizes all data for easy tracking. Quick Start – Implementation Steps Add the n8n Webhook URL to Snyk. Configure Jira, Slack and Airtable credentials in n8n. Adjust severity rules or Jira fields if required. Activate the workflow — vulnerability triage becomes fully automated. What It Does This workflow automates how your team processes vulnerabilities reported by Snyk. When a new vulnerability arrives, the system first normalizes the payload into a clean, consistent format. It then validates required fields such as the vulnerability ID, CVSS score, title and URL. If anything is missing, the workflow instantly sends a Slack alert so the team can review. If the payload is valid, the workflow assigns a severity level and generates a unique “vulnerability key.” This key is used to search Jira for existing issues. If a match is found, the workflow updates the existing Jira ticket and notifies the team. If no match exists, the workflow creates a brand-new Jira issue, sends a Slack alert and also writes the data into Airtable for centralized tracking and analytics. This ensures accurate documentation, avoids duplicates and gives teams visibility through both Jira and Airtable. Who’s It For This workflow is ideal for: DevOps and platform engineering teams Security engineers QA and development teams Companies using Snyk for vulnerability scanning Teams needing automated Jira creation and Airtable reporting Requirements to Use This Workflow To fully use this workflow, you need: An n8n instance (cloud or self-hosted) A Snyk webhook configured to send vulnerability notifications A Jira Software Cloud account A Slack workspace with bot permissions An Airtable base and personal access token Basic understanding of JSON fields How It Works Receive Vulnerability – Snyk posts data to an n8n webhook. Normalize Payload – Converts inconsistent Snyk formats into a standard structure. Validate Required Fields – Missing fields trigger a Slack alert. Assign Severity – CVSS score is mapped to Low/Medium/High/Critical. Generate Vulnerability Key – Used for deduplication (e.g., vuln-SNYK-12345). Check Jira for Matches – Searches by label to detect duplicates. Duplicate Handling – Updates existing Jira issue and sends Slack notification. Create New Issue – If no duplicate exists, creates a new Jira ticket. Store in Airtable – Adds a new vulnerability row for reporting and history. Slack Alerts – Notifies the team of new or updated vulnerabilities. Setup Steps Import the workflow JSON file into n8n. Configure credentials: Jira Slack Airtable Add the generated webhook URL inside your Snyk project settings. Update Jira project ID, issue type, or description fields as needed. Map Airtable fields (Title, CVSS, Severity, URL, Key, etc.). Update Slack channel IDs. Activate the workflow. How To Customize Nodes Customize Severity Rules Modify the node that maps CVSS score ranges: Change thresholds Add custom severity levels Map severity to Jira priority Customize Jira Fields Inside the Create or Update Jira Issue nodes, you can modify: Project ID Issue type Labels Description template Assigned user Customize Slack Messages Adjust Slack text blocks to: Change formatting Add emojis or styling Mention specific users or teams Send different messages based on severity Customize Airtable Storage Update the Airtable node to: Add new columns Save timestamps Link vulnerabilities to other Airtable tables Store more metadata for reporting Add-Ons (Optional Enhancements) You can extend this workflow with: Auto-close Jira tickets when Snyk marks vulnerabilities as “fixed”. Severity-based Slack routing (e.g., Critical → #security-alerts). Email notifications for high-risk vulnerabilities. Google Sheets or Notion logging for long-term tracking. Weekly summary report generated using OpenAI. Mapping vulnerabilities to microservices or repositories. Automated dashboards using Airtable Interfaces. Use Case Examples Automatic Vulnerability Triage – Instantly logs new Snyk findings into Jira. Duplicate Prevention – Ensures every vulnerability is tracked only once. Slack Alerts – Real-time notifications for new or updated issues. Airtable Reporting – Creates a central, filterable database for analysis. Security Team Automation – Reduces manual reviews and saves time. Troubleshooting Guide | Issue | Possible Cause | Solution | |-----------------------------|--------------------------------------------------|--------------------------------------------------------| | Slack alert not sent | Wrong API credentials or channel ID | Re-check Slack configuration | | Jira issue not created | Incorrect project ID / issue type | Update Jira node details | | Duplicate detection not working | Vulnerability key or label mismatch | Confirm key generation and JQL settings | | Airtable row not added | Wrong base or field mapping | Reconfigure Airtable node | | Webhook not triggered | Snyk not pointing to correct URL | Re-add the n8n webhook in Snyk | | Severity not correct | CVSS parsing error | Check normalization and mapping node | Need Help? If you need help setting up this workflow, customizing the logic, integrating new nodes or adding advanced reporting, feel free to reach out to our n8n automation development team at WeblineIndia. We can help automate with advanced security processes, build dashboards, integrate additional tools or expand the workflow as per your business needs.

Webhook → OpenAI → Jira “Bug Suspicion” → Slack QA Escalation This workflow ingests bug reports via a webhook, uses OpenAI to triage and tag them, creates a Jira Bug in project APP with AI-driven labels and alerts QA in Slack. Import the JSON, add OpenAI + Jira + Slack credentials, set the webhook path, choose your Slack channels and activate. Quick Start – Implement in 60 Seconds Import the JSON into n8n. Add credentials to AI Bug Analysis (OpenAI), Create Jira nodes and both Slack Alert nodes. Set webhook path advanced-bug-triage; test with a POST body containing priority, summary and category. Adjust Slack channels qa-alerts-high and qa-general if needed. Activate and verify a test POST flows through Jira and Slack. That’s it. Jira issue gets created and Slack gets notified instantly. What It Does The workflow acts as an AI-assisted bug triage bridge. A webhook receives incoming bug suspicions, which are then analyzed by OpenAI to determine priority and category. Based on the AI output, the flow routes to the appropriate Jira creation path and applies standardized labels for consistent reporting. After creating the Jira Bug in project APP, the workflow escalates to Slack: high-priority items go to qa-alerts-high, while normal items go to qa-general. The result is a fast, low-friction path from external bug signals to actionable Jira issues with immediate QA visibility. Who’s It For QA teams wanting automated Jira escalation. Developers integrating external systems with Jira. Product teams capturing automated “bug suspicion” signals. Monitoring or Sentry-like pipelines. Companies wanting lightweight reporting without building custom infrastructure. Pre-Requisites n8n (cloud or self-hosted). Jira account with permission to create Bug issues. Jira project key: APP (or customize). OpenAI credentials (for AI Bug Analysis) Slack Workspace + Bot token. Ability to send POST request to n8n Webhook endpoint. How It Works & Setup Instructions Webhook Trigger** (advanced-bug-triage): Accepts POST payloads (e.g., summary, description, priority, category). AI Bug Analysis** (OpenAI): Analyzes the payload for sentiment/priority/category (configure your prompt/fields as needed). Priority Switch**: Routes items to the correct Jira creation path (High/Medium/Low). Create Jira (High/Medium/Low)**: Creates Bug issues in project APP, labeling with ai-triaged and the AI-detected category. Slack Alert (High / Normal)**: Notifies QA with the Jira key; high priority goes to qa-alerts-high, others to qa-general. Step 1: Configure Webhook Node Method: POST Path: bug-suspicion Endpoint example: https://YOUR-N8N-URL/webhook/bug-suspicion Step 2: Add OpenAI Credentials Open OpenAI node Select credentials Modify the prompts as needed Step 3: Add Jira Credentials Open Create Jira Bug node Select credentials Ensure access to project APP Ensure permission to create Bug issue type Step 4: Add Slack Credentials Open Slack QA Escalation node Choose Slack Bot credentials Set QA channel Slack message uses: Issue is created in jira for this key <ISSUE-KEY> Step 5: Test Webhook { "title": "Login button unresponsive" } Step 6: Activate Workflow Enable Active toggle. How to Customize Nodes Webhook Trigger Add API keys, tokens or Basic Auth Add JSON validation Jira Node You may add: "additionalFields": { "labels": "bug-suspicion,auto-detected", "description": "={{$json["details"]}}" } Slack Node Customize formatting, attachments, mentions or channels. AI Node for Bug Analysis Tune the prompt, map input fields or adjust model parameters for stricter/looser triage. Priority Switch Modify routing thresholds, add more branches or change default fallback. Add-ons (Optional Enhancements) Email alerts. Severity scoring using AI. Push bug data to Notion or Google Sheets. Add screenshots/logs. Multi-channel notifications. Auto-assign Jira issues based on category or component. Add a fallback email notification for high-priority tickets. Push payloads to a data store (e.g., Sheets/DB) for analytics. Add a secondary Slack DM to on-call for P1. Enrich tickets with logs/links/screenshots from the payload. Use Case Examples Automated QA test failures → Jira + Slack. Monitoring system detects abnormal activity. Browser extension for internal bug reporting. CI/CD pipeline error → instant QA alert. External scripts or tools triggering bug reports. Monitoring alerts auto-create Jira bugs with AI-prioritized severity and Slack escalation. Customer support form pushes suspected bugs directly into Jira with category labels. QA automation failures stream into Jira with priority-based Slack alerts. SRE on-call receives P1 Slack alerts while lower priorities route to the general QA channel. Product beta feedback is categorized by AI and logged as Jira bugs for triage. Troubleshooting Guide | Issue | Cause | Solution | |-------|--------|-----------| | Webhook not receiving data | Wrong URL/method | Use POST + correct path | | Jira issue not created | Wrong credentials/project | Verify Jira credentials + APP project | | Slack message not sent | Bot not allowed in channel | Invite bot to channel | | Jira fields empty | Missing JSON field | Ensure payload includes "title" | | Slack shows undefined | Jira response changed | Add Debug node to inspect output | | Workflow not running | Not activated | Turn ON "Active" | Need Help? If you want help customizing this workflow or building similar n8n workflow automations, the WeblineIndia team can assist with: Jira integrations Slack automation API-based bug pipelines DevOps automation AI-driven severity scoring And so much more. Reach out anytime for implementation or enhancements.

Landing Page Lead Intake via Webhook to Zoho CRM, Jira Task & Slack Alerts This n8n workflow captures lead data from a landing-page webhook, validates required fields and then processes the lead by creating a Zoho CRM Lead, generating a Jira Task and notifying a Slack channel. If required fields are missing, the workflow skips CRM + Jira creation and instead notifies Slack with available lead details. ⚡ Quick Start: 5-Step Fast Implementation Import this workflow JSON into n8n. Configure credentials: Zoho CRM OAuth2, Jira Cloud, Slack OAuth2. Copy the webhook URL and connect it to your landing page form. Ensure your form sends: first_name, last_name, company_name, email, phone, title, description, referrer. Activate workflow → send test POST → verify Zoho, Jira & Slack outputs. What It Does This workflow works as an automated lead pipeline. When the landing page sends JSON to the webhook, the workflow checks if last_name and company_name are present. If both fields exist, it proceeds to create a Zoho CRM lead, then generates a Jira task using the same data. A detailed Slack message is then posted with all lead information and the newly created Jira task ID. If any of the required fields are missing, the workflow does not create CRM or Jira entries. Instead, it sends a Slack notification with available details so teams can intervene manually without incorrect CRM data entry. Who’s It For Marketing teams capturing leads from landing pages. Sales teams using CRM and Jira for task tracking. Internal teams who want Slack alerts for new leads. Agencies and startups handling inbound lead flow. Anyone requiring automated lead routing without manual work. Prerequisites n8n instance Zoho CRM OAuth2 credential Jira Software Cloud credential Slack OAuth2 credential A landing page that sends POST JSON payloads Required payload fields: first_name last_name company_name email phone title description referrer How to Use & Setup Step 1: Import Workflow Go to n8n → Workflows → Import workflow JSON. Step 2: Configure Credentials Add your credentials in: Zoho CRM (Create a lead) Jira Software Cloud (Create an issue) Slack (Send a message & Send a message1) Step 3: Connect Webhook Copy the Webhook URL from the Webhook node and configure your landing page to send POST JSON to it. Step 4: Field Validation The If node checks: last_name exists company_name exists If both exist → CRM + Jira + Slack If missing → Slack-only alert Step 5: Test Workflow Send sample JSON using your landing page or Postman. Check Zoho CRM, Jira task creation, and Slack messages. Step 6: Activate Workflow Enable workflow after verification. How To Customize Nodes? Webhook Node Add/remove expected fields Modify payload structure If Node Add more validations Switch to OR logic Zoho CRM Lead Node Add additional fields Modify CRM field mapping Jira Task Node Change project, issue type, priority, assignee Modify description template Slack Nodes Change channel Rewrite notification messages Add Slack formatting Add-ons (Optional Enhancements) Email notification to lead Google Sheets entry logging Duplicate lead detection Lead scoring system CRM sync extensions (Contact, Account, etc.) Use Case Examples Marketing campaign lead automation. Instant Slack alerts for new inbound leads. Customer inquiry → Jira task workflow. Data quality enforcement (avoid CRM pollution). Trigger for larger lead qualification workflow. (And many more possible use cases.) Troubleshooting Guide | Issue | Possible Cause | Solution | |-------|----------------|----------| | Webhook not triggered | Wrong webhook URL or wrong HTTP method | Check URL and ensure POST is used | | Zoho lead not created | Invalid credentials or missing required mapping | Reconnect Zoho credentials and verify fields | | Jira task not created | Wrong project/issue/assignee config | Verify project, issue type & permissions | | Slack message not sent | Token expired or incorrect channel ID | Re-authenticate Slack and confirm channel | | Workflow stops at If node | last_name or company_name missing | Update landing page form to include fields | | Slack message missing values | Wrong field names in payload | Ensure JSON fields match expected structure | Need Help? For assistance with setup, customization or building enhanced automation workflows, our n8n team at WeblineIndia can help you build & optimize your automations. We support: Workflow customization Add-on development Integration with other CRMs or apps Advanced automation logic

Webhook from Payment Provider → Jira Finance Ticket → Slack Invoice Follow-up Automation This workflow automates failed subscription renewal processing by validating webhook data, using AI to analyze urgency and churn risk, creating a Jira Finance Task and notifying the finance team via Slack. If required fields are missing, it sends an error alert for manual review instead. ⚡ Quick Implementation Steps (Start Using in 60 Seconds) Import workflow JSON into n8n. Add Jira & Slack credentials. Configure webhook URL /payment-failed-renewal in payment provider. Test with: { "customerId": "C-101", "customerEmail": "[email protected]", "subscriptionId": "S-500", "amount": 39.99 } Activate workflow. What It Does This automation connects your payment system with your financial operations. When a subscription renewal fails, the payment provider sends a webhook. The workflow validates the fields, uses OpenAI to analyze the payment failure reason (determining urgency & churn risk), routes high-value failures to high priority, creates a Jira task with an AI-drafted recovery email and alerts the finance team on Slack. If required data is missing, the workflow prevents incomplete Jira tickets by routing the event to an error handler and sending a detailed Slack alert listing all missing fields and full payload for manual inspection. Who’s It For Finance & billing departments SaaS companies with recurring billing Teams using Jira for billing operations Slack-based financial support teams Companies wanting automated revenue recovery workflows Requirements to Use This Workflow n8n instance OpenAI API Key (or compatible LLM credential) Jira Software account with permissions for FIN project Slack bot token with channel posting rights Payment provider that supports POST JSON webhooks Webhook configured to: https://YOUR-N8N-URL/webhook/payment-failed-renewal How It Works & How To Set Up Step-by-Step Flow Webhook receives payment failure payload. Validation node checks required fields: customerId customerEmail subscriptionId amount AI Analysis: OpenAI analyzes failure reason, sets urgency, and drafts email. Logic: Switch node routes High Value (>$500) to 'High' priority. Jira Finance Task created (with AI draft). Slack message sent (with Churn Risk score). Setup Steps Step 1 — Webhook Setup Method: POST Path: payment-failed-renewal Step 2 — Jira Setup Select Jira credentials in Create Jira Finance Ticket node. Ensure: Project: FIN Issue type: Task Step 3 — Slack Setup Add Slack credentials to both Slack nodes. Select finance alert channel. Step 4 — OpenAI Setup Add OpenAI credentials in the AI Analysis node. Step 5 — Test { "customerId": "CUST-001", "customerEmail": "[email protected]", "subscriptionId": "SUB-1001", "amount": 19.99 } Step 6 — Activate Enable the workflow. How To Customize Nodes Webhook Add Basic Auth Add token-based security Add JSON schema validation Validate Payload Enhance with: Email format validation Numeric validation for amount Auto-fallback values Jira Node Customize: Ticket summary structure Labels (billing-recovery, urgent, etc.) Add custom fields Change issue type or project Slack Nodes Enhance: Mentions: @finance-team Threads instead of channel posts Rich blocks, buttons, or attachments Add-ons (Optional Enhancements) Automated email to customer for payment recovery Retry count–based escalation (e.g., retry ≥ 3 → escalate to manager) Log data to Airtable / Google Sheets Sync events into CRM (HubSpot, Salesforce, Zoho) Notify Sales for high-value customer failures Use Case Examples Stripe renewal payment fails → Create Jira task → Slack finance alert. Chargebee retry attempts exhausted → Notify billing team immediately. Declined credit card → Jira ticket with failure reason. Razorpay/PayPal renewal failure → Automated follow-up. Webhook missing data → Slack error alert ensures nothing is silently ignored. Troubleshooting Guide | Issue | Possible Cause | Solution | |-------|----------------|----------| | Webhook not triggering | Wrong URL / method | Use POST + correct endpoint | | Jira ticket missing | No permissions or invalid payload | Check Jira permissions + required fields | | Slack shows undefined values | Missing fields in payload | Confirm payload structure | | Error alert triggered incorrectly | Field names mismatch | Match exact names: customerId, customerEmail, subscriptionId, amount | | Payment provider not sending events | Firewall/CDN blocking | Whitelist the n8n webhook URL | | Workflow silent | Not activated | Turn workflow ON | Need Help? If you want help customizing this workflow or extending it into a complete revenue recovery automation suite: WeblineIndia can support you with: Jira & Slack automation pipelines Payment provider webhook integrations Finance workflow optimization AI-based billing insights End‑to‑end automation solutions Reach out anytime for expert implementation or enhancements.

Product Price Monitor with Slack and Jira ⚠️ COMMUNITY TEMPLATE DISCLAIMER: This is a community-contributed template that uses ScrapeGraphAI (a community node). Please ensure you have the ScrapeGraphAI community node installed in your n8n instance before using this template. This workflow automatically scrapes multiple e-commerce sites, analyses weekly seasonal price trends, and notifies your team in Slack while opening Jira tickets for items that require price adjustments. It helps retailers plan inventory and pricing by surfacing actionable insights every week. Pre-conditions/Requirements Prerequisites n8n instance (self-hosted or n8n cloud) ScrapeGraphAI community node installed Slack workspace & channel for notifications Jira Software project (cloud or server) Basic JavaScript knowledge for optional custom code edits Required Credentials ScrapeGraphAI API Key** – Enables web scraping Slack OAuth Access Token** – Required by the Slack node Jira Credentials** – Email & API token (cloud) or username & password (server) (Optional) Proxy credentials – If target websites block direct scraping Specific Setup Requirements | Resource | Purpose | Example | |----------|---------|---------| | Product URL list | Seed URLs to monitor | https://example.com/products-winter-sale | | Slack Channel | Receives trend alerts | #pricing-alerts | | Jira Project Key | Tickets are created here | ECOM | How it works This workflow automatically scrapes multiple e-commerce sites, analyses weekly seasonal price trends, and notifies your team in Slack while opening Jira tickets for items that require price adjustments. It helps retailers plan inventory and pricing by surfacing actionable insights every week. Key Steps: Webhook Trigger**: Kicks off the workflow via a weekly schedule or manual call. Set Product URLs**: Prepares the list of product pages to analyse. SplitInBatches**: Processes URLs in manageable batches to avoid rate limits. ScrapeGraphAI**: Extracts current prices, stock, and seasonality hints from each URL. Code (Trend Logic)**: Compares scraped prices against historical averages. If (Threshold Check)**: Determines if price deviations exceed ±10%. Slack Node**: Sends a formatted message to the pricing channel for each deviation. Jira Node**: Creates/updates a ticket linking to the product for further action. Merge**: Collects all batch results for summary reporting. Set up steps Setup Time: 15-20 minutes Install Community Nodes: In n8n, go to Settings → Community Nodes, search for “ScrapeGraphAI”, and install. Add Credentials: a. Slack → Credentials → New, paste your Bot/User OAuth token. b. Jira → Credentials → New, enter your domain, email/username, API token/password. c. ScrapeGraphAI → Credentials → New, paste your API key. Import Workflow: Upload or paste the JSON template into n8n. Edit the “Set Product URLs” Node: Replace placeholder URLs with your real product pages. Configure Schedule: Replace the Webhook Trigger with a Cron node (e.g., every Monday 09:00) or keep as webhook for manual runs. Map Jira Fields: In the Jira node, ensure Project Key, Issue Type (e.g., Task), and Summary fields match your instance. Test Run: Execute the workflow. Confirm Slack message appears and a Jira issue is created. Activate: Toggle the workflow to Active so it runs automatically. Node Descriptions Core Workflow Nodes: Webhook** – Default trigger, can be swapped with Cron for weekly automation. Set (Product URLs)** – Stores an array of product links for scraping. SplitInBatches** – Limits each ScrapeGraphAI call to five URLs to reduce load. ScrapeGraphAI** – Crawls and parses HTML, returning JSON with title, price, availability. Code (Trend Logic)** – Calculates percentage change vs. historical data (stored externally or hard-coded for demo). If (Threshold Check)** – Routes items above/below the set variance. Slack** – Posts a rich-format message containing product title, old vs. new price, and link. Jira* – Creates or updates a ticket with priority set to *Medium and assigns to the Pricing team lead. Merge** – Recombines batch streams for optional reporting or storage. Data Flow: Webhook → Set (Product URLs) → SplitInBatches → ScrapeGraphAI → Code (Trend Logic) → If → Slack / Jira → Merge Customization Examples Change Price Deviation Threshold // Code (Trend Logic) node const threshold = 0.05; // 5% instead of default 10% Alter Slack Message Template { "text": ${item.name} price changed from $${item.old} to $${item.new} (${item.diff}%)., "attachments": [ { "title": "Product Link", "title_link": item.url, "color": "#4E79A7" } ] } Data Output Format The workflow outputs structured JSON data: { "product": "Winter Jacket", "url": "https://example.com/winter-jacket", "oldPrice": 129.99, "newPrice": 99.99, "change": -23.06, "scrapedAt": "2023-11-04T09:00:00Z", "status": "Below Threshold", "slackMsgId": "A1B2C3", "jiraIssueKey": "ECOM-101" } Troubleshooting Common Issues ScrapeGraphAI returns empty data – Verify selectors; many sites use dynamic rendering, require a headless browser flag. Slack message not delivered – Check that the OAuth token scopes include chat:write; also confirm channel ID. Jira ticket creation fails – Field mapping mismatch; ensure Issue Type is valid and required custom fields are supplied. Performance Tips Batch fewer URLs (e.g., 3 instead of 5) to reduce timeout risk. Cache historical prices in an external DB (Postgres, Airtable) instead of reading large CSVs in the Code node. Pro Tips: Rotate proxies/IPs within ScrapeGraphAI to bypass aggressive e-commerce anti-bot measures. Add a Notion or Sheets node after Merge for historical logging. Use the Error Trigger workflow in n8n to alert when ScrapeGraphAI fails more than X times per run.

ETL Monitoring & Alert Automation: Jira & Slack Integration This workflow automatically processes ETL errors, extracts important details, generates a preview, creates a log URL, classifies the issue using AI and saves the processed data into Google Sheets. If the issue is important or needs attention, it also creates a Jira ticket automatically. The workflow reduces manual debugging effort, improves visibility and ensures high-severity issues are escalated instantly without human intervention. Quick Start – Implementation Steps Connect your webhook or ETL platform to trigger the workflow. Add your OpenAI, Google Sheets and Jira credentials. Enable the workflow. Send a sample error to verify Sheets logging and Jira ticket creation. Deploy and let the workflow monitor ETL pipelines automatically. What It Does This workflow handles ETL errors end-to-end by: Extracting key information from ETL error logs. Creating a short preview for quick understanding. Generating a URL to open the full context log. Asking AI to identify root cause and severity. Parsing the AI output into clean fields. Saving the processed error to Google Sheets. Creating a Jira ticket for medium/high-severity issues. This creates a complete automated system for error tracking, analysis and escalation. Who’s It For DevOps & engineering teams monitoring data pipelines. ETL developers who want automated error reporting. QA teams verifying daily pipeline jobs. Companies using Jira for issue tracking. Teams needing visibility into ETL failures without manual log inspection. Requirements to Use This Workflow n8n account or self-hosted instance. ETL platform capable of sending error payloads (via webhook). OpenAI API Key. Google Sheets credentials. Jira Cloud API credentials. Optional: log storage URL (S3, Supabase, server logs). How It Works & Setup Steps Get ETL Error (Webhook Trigger) Receives ETL error payload and starts the workflow. Prepare ETL Logs (Code Node) Extracts important fields and makes a clean version of the error.Generates a direct link to open the full ETL log. AI Severity Classification (OpenAI / AI Agent) AI analyzes the issue, identifies cause and assigns severity. Parse AI Output (Code Node) Formats AI results into clean fields: severity, cause, summary, recommended action. Prepare Data for Logging (Set / Edit Fields) Combines all extracted info into one final structured record. Save ETL Logs (Google Sheets Node) Logs each processed ETL error in a spreadsheet for tracking. Create Jira Ticket (Jira Node) Automatically creates a Jira issue when severity is Medium, High or Critical. ETL Failure Alert (Slack Node) Sends a Slack message to notify the team about the issue. ETL Failure Notify (Gmail Node) Sends an email with full error details to the team. How to Customize Nodes ETL Log Extractor Add/remove fields based on your ETL log structure. AI Classification Modify the OpenAI prompt for custom severity levels or deep-dive analysis. Google Sheets Logging Adjust columns for environment, job name or log ID. Jira Fields Customize issue type, labels, priority and assignees. Add-Ons (Extend the Workflow) Send Slack or Teams alerts for high severity issues Store full logs in cloud storage (S3, Supabase, GCS) Add daily/weekly error summary reports Connect monitoring tools like Datadog or Grafana Trigger automated remediation workflows Use Case Examples Logging all ETL failures to Google Sheets Auto-creating Jira tickets with AI-driven severity Summarizing large logs with AI for quick analysis Centralized monitoring of multiple ETL pipelines Reducing manual debugging effort across teams Troubleshooting Guide | Issue | Possible Cause | Solution | |-------|----------------|----------| | Sheets not updating | Wrong Sheet ID or missing permission | Reconnect and reselect the sheet | | Jira ticket fails | Missing required fields or invalid project key | Update Jira mapping | | AI output empty | Invalid OpenAI key or exceeded usage | Check API key or usage limits | | Severity always “low” | Prompt too broad | Adjust AI prompt with stronger rules | | Log preview empty | Incorrect error field mapping | Verify the structure of the ETL error JSON | Need Help? For assistance setting up this workflow, customizing nodes or adding additional features, feel free to contact our n8n developers at WeblineIndia. We can help configure, scale or build similar automation workflows tailored to your ETL and business requirements.

Automated Social Media Lead Processing with AI Summaries, Slack Alerts & Jira Ticketing This workflow automatically collects new lead messages from social media platforms, LinkedIn or web forms, filters relevant marketing inquiries using keywords, classifies and summarizes the lead with AI, logs it to Google Sheets, creates a Jira task and sends Slack notifications. Additionally, it generates weekly lead reports for team insights. It reduces manual triage, ensures no valid inquiry is missed and keeps your team updated with both immediate notifications and summary reports. Quick Start – Implementation Steps Connect your webhook to your social media inbox, LinkedIn, Twitter or web form. Add your OpenAI, Google Sheets, Jira and Slack credentials. Enable the workflow. Send a test message to confirm Google Sheets logging, Slack notification and Jira task creation. Activate the scheduler for weekly reports to track lead performance. What It Does This workflow performs the following key tasks: Filters incoming messages for marketing-related keywords like ad request, promo request, collaboration, partnership or social media inquiry. Uses OpenAI GPT to classify the lead into categories such as Sales, Support, Partnership, Influencer Inquiry or General Lead. Generates a short AI summary of the message. Logs structured lead data to Google Sheets, including username, source, category, summary and timestamp. Creates a Jira task automatically with summary, description, category and received time. Sends a Slack notification to alert the team instantly. Runs a scheduled workflow that aggregates weekly leads and sends a weekly report to Slack. This ensures a structured, automated pipeline for capturing, summarizing and assigning leads efficiently. Who’s It For Marketing and sales teams managing leads from social media and web forms. Agencies handling client campaigns and inquiries. Businesses that want automated notifications and ticketing. Teams using Slack and Jira for daily operations. Requirements to Use This Workflow n8n account or self-hosted instance. Webhook-enabled social media inbox or lead form. OpenAI API Key. Slack Bot Token with channel posting permission. Jira Software Cloud API credentials. Google Sheets credentials. Predefined keyword list for filtering messages. How It Works & Setup Steps Get DM (Webhook Trigger) Receives new messages from social media or web forms and starts the workflow. Lead Keyword Filter (Code Node) Filters incoming messages for predefined marketing keywords and removes irrelevant or spam messages. AI Lead Classifier (OpenAI Node) Classifies the lead into categories (Sales, Support, Partnership, Influencer Inquiry, General Lead) and generates a one-line summary using GPT-4.1. AI Output Parser (Code Node) Parses AI JSON output and merges it with original message data, adding timestamp and structured fields. Store Lead (Google Sheets Node) Logs structured lead data to Google Sheets including username, source, category, summary and timestamp. Create Task (Jira Node) Automatically creates a Jira story or task in your selected project with the AI summary, category and timestamp. Send a Summary (Slack Node) Sends a formatted message to your selected Slack channel, alerting your team of the new lead. Weekly Reporting Schedule Trigger** – triggers the weekly reporting workflow. Extract Lead Data** – fetches all logged leads from Google Sheets. Weekly Lead Filter** – filters data to include leads from the last week. Report Data Formatter** – calculates total leads, category counts, source counts and example leads. Weekly Report Slack** – sends a formatted weekly lead summary to Slack. How to Customize Nodes Keyword Filter Add or remove keywords in the JavaScript code to match your specific lead types or campaigns. AI Classification Update the OpenAI prompt for different summary lengths, tones, or lead categories. Google Sheets Logging Map additional columns like email, phone or campaign source as needed. Jira Fields Customize summary, description, labels, priority or assignees based on your project requirements. Slack Message Format Modify emojis, line breaks and formatting to suit your team’s Slack notifications. Add-Ons (Extend the Workflow) Send email alerts for high-priority leads. Trigger WhatsApp replies using an API provider. Integrate with CRMs like HubSpot, Zoho or Salesforce. Add sentiment analysis to detect frustrated or VIP users. Automate daily or weekly analytics reports to Slack. Use Case Examples Collecting Instagram, LinkedIn and Twitter DMs and logging them to Google Sheets. Creating automated Jira tickets for marketing inquiries. Sending instant Slack notifications for new leads. Filtering out irrelevant messages and only processing valid marketing leads. Generating weekly lead summary reports for team review. Troubleshooting Guide | Issue | Possible Cause | Solution | |-------|----------------|----------| | No leads appearing | Webhook not receiving messages | Check webhook URL and ensure messages are sent correctly | | AI summary empty | OpenAI API key invalid or model limit reached | Regenerate API key / check usage | | Jira task not created | Missing required Jira fields or incorrect project ID | Add required fields or update Jira project settings | | Slack message not sent | Wrong channel ID or missing permissions | Reconnect Slack credentials | | Filter passes 0 items | Keywords do not match | Update or expand keyword list in filter node | Need Help? If you need assistance setting up this workflow, customizing nodes, building add-ons or automating more processes, our n8n workflow development team at WeblineIndia is happy to help. We can guide you through integrations, scaling or building end-to-end automation systems tailored to your business.

Automated Failed Login Detection with Jira Security Tasks, Slack Notifications Webhook: Failed Login Attempts → Jira Security Case → Slack Warnings This n8n workflow monitors failed login attempts from any application, normalizes incoming data, detects repeated attempts within a configurable time window and automatically: Sends detailed alerts to Slack, Creates Jira security tasks (single or grouped based on repetition), Logs all failed login attempts into a Notion database. It ensures fast, structured and automated responses to potential account compromise or brute-force attempts while maintaining persistent records. Quick Implementation Steps Import this JSON workflow into n8n. Connect your application to the failed-login webhook endpoint. Add Jira Cloud API credentials. Add Slack API credentials. Add Notion API credentials and configure the database for storing login attempts. Enable the workflow — done! What It Does Receives Failed Login Data Accepts POST requests containing failed login information. Normalizes the data, ensuring consistent fields: username, ip, timestamp and error. Validates Input Checks for missing username or IP. Sends a Slack alert if any required field is missing. Detects Multiple Attempts Uses a sliding time window (default: 5 minutes) to detect multiple failed login attempts from the same username + IP. Single attempts → standard Jira task + Slack notification. Multiple attempts → grouped Jira task + detailed Slack notification. Logs Attempts in Notion Records all failed login events into a Notion database with fields: Username, IP, Total Attempts, Attempt List, Attempt Type. Formats Slack Alerts Single attempt → lightweight notification. Multiple attempts → summary including timestamps, errors, total attempts, and Jira ticket link. Who’s It For This workflow is ideal for: Security teams monitoring authentication logs. DevOps/SRE teams maintaining infrastructure access logs. SaaS platform teams with high login traffic. Organizations aiming to automate breach detection. Teams using Jira + Slack + Notion + n8n for incident workflows. Requirements n8n (Self-Hosted or Cloud). Your application must POST failed login data to the webhook. Jira Software Cloud credentials (Email, API Token, Domain). Slack Bot Token with message-posting permissions. Notion API credentials with access to a database. Basic understanding of your login event sources. How It Works Webhook Trigger: Workflow starts when a failed-login event is sent to the failed-login webhook. Normalization: Converts single objects or arrays into a uniform format. Ensures username, IP, timestamp and error are present. Prepares a logMessage for Slack and Jira nodes. Validation: IF node checks whether username and IP exist. If missing → Slack alert for missing information. Multiple Attempt Detection: Function node detects repeated login attempts within a 5-minute sliding window. Flags attempts as multiple: true or false. Branching: Multiple attempts → build summary, create Jira ticket, format Slack message, store in Notion. Single attempts → create Jira ticket, format Slack message, store in Notion. Slack Alerts: Single attempt → concise message Multiple attempts → detailed summary with timestamps and Jira ticket link Notion Logging: Stores username, IP, total attempts, attempt list, attempt type in a dedicated database for recordkeeping. How To Set Up Import Workflow → Workflows → Import from File in n8n. Webhook Setup → copy the URL from Faield Login Trigger node and integrate with your application. Jira Credentials → connect your Jira account to both Jira nodes and configure project/issue type. Slack Credentials → connect your Slack Bot and select the alert channel. Notion Credentials → connect your Notion account and select the database for storing login attempts. Test the Workflow → send sample events: missing fields, single attempts, multiple attempts. Enable Workflow → turn on workflow once testing passes. Logic Overview | Step Node | Description | |---------------------------------|-----------------------------------------------| | Normalize input | Normalize Login Event — Ensures each event has required fields and prepares a logMessage. | | Validate fields | Check Username & IP present — IF node → alerts Slack if data is incomplete. | | Detect repeats | Detect Multiple Attempts — Finds multiple attempts within a 5-minute window; sets multiple flag. | | Multiple attempts | IF - Multiple Attempts + Build Multi-Attempt Summary — Prepares grouped summary for Slack & Jira. | | Single attempt | Create Ticket - Single Attempt — Creates Jira task & Slack alert for one-off events. | | Multiple attempt ticket | Create Ticket - Multiple Attempts — Creates detailed Jira task. | | Slack alert formatting | Format Fields For Single/Multiple Attempt — Prepares structured message for Slack. | | Slack alert delivery | Slack Alert - Single/Multiple Attempts — Posts alert in selected Slack channel. | | Notion logging | Login Attempts Data Store in DB — Stores structured attempt data in Notion database. | Customization Options Webhook Node** → adjust endpoint path for your application. Normalization Function** → add fields such as device, OS, location or user-agent. Multiple Attempt Logic** → change the sliding window duration or repetition threshold. Jira Nodes** → modify issue type, labels or project. Slack Nodes** → adjust markdown formatting, channel routing or severity-based channels. Notion Node** → add or modify database fields to store additional context. Optional Enhancements: Geo-IP lookup for country/city info. Automatic IP blocking via firewall or WAF. User notification for suspicious login attempts. Database logging in MySQL/Postgres/MongoDB. Threat intelligence enrichment (e.g., AbuseIPDB). Use Case Examples Detect brute-force attacks targeting user accounts. Identify credential stuffing across multiple users. Monitor admin portal access failures with Jira task creation. Alert security teams instantly when login attempts originate from unusual locations. Centralize failed login monitoring across multiple applications with Notion logging. Troubleshooting Guide | Issue | Possible Cause | Solution | |-------------------------------|---------------------------------------------------|-------------------------------------------------------------| | Workflow not receiving data | Webhook misconfigured | Verify webhook URL & POST payload format | | Jira ticket creation fails | Invalid credentials or insufficient permissions | Update Jira API token and project access | | Slack alert not sent | Incorrect channel ID or missing bot scopes | Fix Slack credentials and permissions | | Multiple attempts not detected| Sliding window logic misaligned | Adjust Detect Multiple Attempts node code | | Notion logging fails | Incorrect database ID or missing credentials | Update Notion node credentials and database configuration | | Errors in normalization | Payload format mismatch | Update Normalize Login Event function code | Need Help? If you need help setting up, customizing or extending this workflow, WeblineIndia can assist with full n8n development, workflow automation, security event processing and custom integrations.

Customer Feedback Automation Workflow with Webhook, OpenAI, Jira & Slack This workflow collects customer feedback from a webhook, validates the incoming data, analyzes the sentiment using OpenAI and creates Jira tasks for negative or feature-request feedback. It also generates an automated weekly summary using OpenAI and delivers it to Slack. It helps teams stay informed, skip manual reviews and act quickly on customer issues. Quick Start – Implementation Steps Set up the Webhook URL in your application to send customer feedback. Configure Slack, Jira and OpenAI credentials in n8n. Adjust sentiment rules or Jira fields if needed. Activate the workflow — you’re ready to collect and process feedback automatically. What It Does This workflow automates the entire lifecycle of customer feedback handling. When someone submits feedback, the system checks if the required information (feedback text and sentiment) is present. If the payload is invalid or incomplete, the team immediately receives a Slack notification to take action. If the feedback is valid, OpenAI analyzes the content and identifies the sentiment as positive, negative, neutral or a feature suggestion. Based on this result, the system automatically creates a Jira issue for negative feedback or feature requests, ensuring nothing important is missed. Alongside real-time processing, the workflow also compiles a weekly summary. Every week, it gathers all Jira issues created through feedback and sends them to OpenAI for summarization. The summary is then posted to Slack so the team gets a clean, easy-to-read review of customer sentiment trends. Who’s It For This workflow is ideal for: Customer support teams Product managers QA and development teams Companies collecting user feedback Businesses wanting automated sentiment analysis and reporting Requirements to Use This Workflow To fully use this workflow, you need: An n8n instance (self-hosted or cloud) A Webhook endpoint to receive customer feedback A Slack workspace with API access A Jira Software Cloud account An OpenAI API key with access to GPT-4.1 or similar Basic understanding of JSON payloads How It Works Collect Feedback – Receives customer data through an n8n webhook. Validate Payload – Checks required fields; bad input triggers Slack alerts. Determine Sentiment – Sends feedback text to OpenAI for sentiment classification. Conditional Routing – Negative or feature-request items move forward; others are ignored. Create Jira Task – Automatically logs an issue for follow-up. Weekly Summary – A scheduled trigger collects all Jira issues created during the week. Generate Report – Sends all issues to OpenAI for a clean weekly summary. Delivered to Slack – The summary is posted for the team to review. Setup Steps Import the workflow JSON file into n8n. Configure your credentials: Slack Jira OpenAI Update the webhook URL in your application. Edit Jira project ID or fields if required. Customize Slack channel IDs. Enable the schedule trigger (weekly summary). Activate the workflow. How To Customize Nodes Customize Sentiment Rules Modify the IF node that checks OpenAI output: Add new sentiment labels (e.g., “bug”, “urgent”) Adjust rules for what should create a Jira issue Customize Jira Task Fields In the Create Jira Task node, you can change: Project ID Issue type Summary and description templates Labels or assignees Customize Slack Messages Update Slack node text blocks to: Format alerts Add more details Send messages to different channels Add-Ons (Optional Enhancements) You can extend this workflow with: Email notifications for high-priority feedback Auto-reply emails to customers acknowledging their feedback Google Sheets logging for historical data Dashboard creation using Airtable or Notion Multi-language sentiment detection Auto-tagging Jira issues with sentiment categories Use Case Examples Customer Complaint Handling – Automatically detect negative feedback and create a Jira issue. Feature Request Collection – Route suggestions to the product backlog. Weekly Sentiment Reporting – Keep managers updated on trends. Slack Alerts for Bad Payloads – Notify the team when someone sends incomplete or incorrect feedback. Automated Feedback Triage – Assign tasks to specific Jira users based on sentiment or keywords. You can extend to many more such similar use cases. Troubleshooting Guide | Issue | Possible Cause | Solution | |-----------------------------|-----------------------------------------------|---------------------------------------------------| | Slack alert not sent | Wrong API credentials or channel ID | Check Slack credentials and update channel ID | | Jira issue not created | Incorrect project ID or issue type | Verify Jira configuration in n8n | | OpenAI sentiment not reading| Wrong JSON path in IF node | Re-check $json.output[0].content[0].text | | Weekly summary not generated| Schedule trigger disabled | Enable the Schedule Trigger node | | Webhook not receiving data | Application not pointing to correct URL | Verify webhook URL in your app | Need Any Help? If you need any help setting up this workflow, troubleshooting or adding custom features, our n8n experts at WeblineIndia is always here to support. We can help you automate more processes, integrate external systems or build complete workflow solutions tailored to your business.

Description: Bridge the gap between Monday.com and Jira with this intelligent n8n automation template. The workflow listens for new or updated Monday.com items, normalizes data fields, and syncs them with your Jira backlog—automatically detecting duplicates using fuzzy matching logic. It then creates or updates Jira issues accordingly and logs the results back into Monday.com, ensuring your product and engineering teams stay aligned in real time. Ideal for project managers, product ops, and agile teams who manage intake in Monday.com but execute tasks in Jira. ✅ What This Template Does (Step-by-Step) 🌐 Webhook Trigger from Monday.com: Starts automatically whenever a new task or update occurs in Monday.com. 🔄 Normalize Monday.com Data: Extracts and cleans key data fields such as summary, component, severity, and description for consistent formatting before sending to Jira. 📊 Query Jira Backlog: Fetches all existing issues from Jira to establish a baseline for duplicate detection. 🔍 Detect Duplicates with Fuzzy Matching: Compares Monday item titles with Jira summaries using character-level similarity (>80% threshold) to detect potential duplicates even with minor variations. ⚖️ Decision Gate: Duplicate or New: If duplicate found: updates the existing Jira issue with new data. If no match: creates a new Jira task in the appropriate project and issue type. 🔧 Update Existing Jira Issues: Automatically enhances Jira tickets with latest information from Monday.com including updated priority, description, and reference links. ✨ Create New Jira Issues: For new requests, generates a Jira task with details mapped from Monday—complete with severity, component, and description. 📝 Log Actions Back to Monday.com: Posts an update back to the originating Monday item confirming whether the action created or updated a Jira issue, including timestamp and Jira key link. 📋 (Optional) Create New Monday Board: Can also auto-create a private board in Monday.com for project-specific task organization. 🧠 Key Features 🔍 Smart fuzzy duplicate detection (>80% match threshold) ⚙️ Full bidirectional visibility between Monday.com and Jira 📢 Automatic task creation and update logic 🧾 Real-time status logging and audit trail in Monday.com 🔐 Secure API-based connections for both platforms 💼 Use Cases 💡 Sync product feedback and feature requests from Monday to Jira 🎯 Centralize intake forms and align engineering backlogs 🤝 Eliminate duplicate Jira issues from multiple product submissions 📈 Maintain transparent traceability across tools 📦 Required Integrations Monday.com API – for item intake and updates Jira Software Cloud API – for issue creation and modification 🎯 Why Use This Template? ✅ Eliminates duplicate Jira issues automatically ✅ Keeps Monday.Com and Jira perfectly aligned ✅ Saves hours of manual task reconciliation ✅ Ideal for agile and cross-functional collaboration

Automate Bug Reports: GitHub Issues → AI Analysis → Jira Tickets with Slack & Discord Alerts Automatically convert GitHub issues into analyzed Jira tickets with AI-powered severity detection, developer assignment, and instant team alerts. Overview This workflow captures GitHub issues in real-time, analyzes them with GPT-4o for severity and categorization, creates enriched Jira tickets, assigns the right developers, and notifies your team across Slack and Discord—all automatically. Features AI-Powered Triage**: GPT-4o analyzes bug severity, category, root cause, and generates reproduction steps Smart Assignment**: Automatically assigns developers based on mentioned files and issue context Two-Way Sync**: Posts Jira ticket links back to GitHub issues Multi-Channel Alerts**: Rich notifications in Slack and Discord with action buttons Time Savings**: Eliminates 15-30 minutes of manual triage per bug Customizable Routing**: Easy developer mapping and priority rules What Gets Created Jira Ticket: Original GitHub issue details with reporter info AI severity assessment and categorization Reproduction steps and root cause analysis Estimated completion time Automatic labeling and priority assignment GitHub Comment: Jira ticket link AI analysis summary Assigned developer and estimated time Team Notifications: Severity badges and quick-access buttons Developer assignment and root cause summary Color-coded priority indicators Use Cases Development teams managing 10+ bugs per week Open source projects handling community reports DevOps teams tracking infrastructure issues QA teams coordinating with developers Product teams monitoring user-reported bugs Setup Requirements Required: GitHub repository with admin access Jira Software workspace OpenAI API key (GPT-4o access) Slack workspace OR Discord server Customization Needed: Update developer email mappings in "Parse GPT Response & Map Data" node Replace YOUR_JIRA_PROJECT_KEY with your project key Update Slack channel name (default: dev-alerts) Replace YOUR_DISCORD_WEBHOOK_URL with your webhook Change your-company.atlassian.net to your Jira URL Setup Time: 15-20 minutes Configuration Steps Import workflow JSON into n8n Add credentials: GitHub OAuth2, Jira API, OpenAI API, Slack, Discord Configure GitHub webhook in repository settings Customize developer mappings and project settings Test with sample GitHub issue Activate workflow Expected Results 90% faster bug triage (20 min → 2 min per issue) 100% consistency in bug analysis Zero missed notifications Better developer allocation Improved bug documentation Tags GitHub, Jira, AI, GPT-4, Bug Tracking, DevOps, Automation, Slack, Discord, Issue Management, Development, Project Management, OpenAI, Webhook, Team Collaboration

What it does Automates code review by listening for a comment trigger on GitLab merge requests, summarising the diff, and using an LLM to post constructive, line‑specific feedback. If a JIRA ticket ID is found in the MR description, the ticket’s summary is used to inform the AI review. Use cases Quickly obtain high‑quality feedback on MRs without waiting for peers. Highlight logic, security or performance issues that might slip through cursory reviews. Incorporate project context by pulling in related JIRA ticket summaries. Good to know Triggered by commenting ai-review on a merge request. The LLM returns only high‑value findings; if nothing critical is detected, the workflow posts an “all clear” message. You can swap out the LLM (Gemini, OpenAI, etc.) or adjust the prompt to fit your team’s guidelines. AI usage may incur costs or be geo‑restricted depending on your provider n8n.io. How it works Webhook listener:** A Webhook node captures GitLab note events and filters for the trigger phrase. Fetch & parse:** The workflow retrieves MR details and diffs, splitting each change into “original” and “new” code blocks. Optional JIRA context:** If your MR description includes a JIRA key (e.g., PROJ-123), the workflow fetches the ticket (and parent ticket for subtasks) and composes a brief context summary. LLM review:** The parsed diff and optional context are sent to an LLM with instructions to identify logic, security or performance issues and suggest improvements. Post results:** Inline comments are posted back to the MR at the appropriate file/line positions; if no issues are found, a single “all clear” note is posted. How to use Import the template JSON and open the Webhook node. Replace the REPLACE_WITH_UNIQUE_PATH placeholder with your desired path and configure a GitLab project webhook to send MR comments to that URL. Select your LLM credentials in the Gemini (or other LLM) node, and optionally add JIRA credentials in the JIRA nodes. Activate the workflow and comment ai-review on any merge request to test it. For each review, the workflow posts status updates (“AI review initiated…”) and final comments. Requirements A GitLab project with a generate Personal Access Token (PAT) stored as an environment variable (GITLAB_TOKEN). LLM credentials (e.g., Google Gemini) and optional JIRA credentials. Customising this workflow Change the trigger phrase in the Trigger Phrase Filter node. Modify the LLM prompt to focus on different aspects (e.g., style, documentation). Filter out certain file types or directories before sending diffs to the LLM. Integrate other services (Slack, email) to notify teams when reviews are complete.

This n8n template from Intuz provides a complete and automated solution for scaling your DevOps practices across multiple repositories. Are you tired of the repetitive dance between git push, creating a pull request in GitHub, updating the corresponding task in JIRA, and then manually notifying your team in Slack, or Notion? This template puts your entire post-commit workflow on autopilot, creating a seamless and intelligent bridge between your code and your project management. By embedding specific keywords and a JIRA issue ID into your git commit commands, this workflow automatically creates a Pull Request in the correct GitHub repository and updates the corresponding JIRA ticket. This creates a complete, centralized system that keeps all your projects synchronized, providing a massive efficiency boost for teams managing a diverse portfolio of codebases. Who This Template Is For? This template is a must-have for any organization looking to streamline its software development lifecycle (SDLC). It’s perfect for: Development Teams: Eliminate tedious, manual tasks and enforce a consistent workflow, allowing developers to stay focused on coding. DevOps Engineers: A ready-to-deploy solution that integrates key developer tools without weeks of custom scripting. Engineering Managers & Team Leads: Gain real-time visibility into development progress and ensure processes are followed without constant check-ins. Project Managers: Get accurate, automatic updates in JIRA the moment development work is completed, improving project tracking and forecasting. Step-by-Step Setup Instructions Follow these steps carefully to configure the workflow for your environment. Connect Your Tools (Credentials) GitHub: Create credentials with repo scope to allow PR creation. JIRA: Create an API token and connect your JIRA Cloud or Server instance. Slack: Connect your Slack workspace using OAuth2. Notion: Connect your Notion integration token. Configure the GitHub Webhook (For Each Repository) This workflow is triggered by a GitHub webhook. You must add it to every repository you want to automate. First, Save and Activate the n8n workflow to ensure the webhook URL is live. In the n8n workflow, copy the Production URL from the Webhook node. Go to your GitHub repository and navigate to Settings > Webhooks > Add webhook. In the Payload URL field, paste the n8n webhook URL. Change the Content type to application/json. Under "Which events would you like to trigger this webhook?", select "Just the push event." Click "Add webhook." Repeat this for all relevant repositories. Configure the JIRA Nodes (Crucial Step) Your JIRA project has unique IDs for its statuses. You must update the workflow to match yours. Find the two JIRA nodes named "Update task status after PR" and "Update the task status without PR." In each node, go to the Status ID field. Click the dropdown and select the status that corresponds to "Done" or "Development Done" in your specific JIRA project workflow. The list is fetched directly from your connected JIRA instance. Configure Notification Nodes Tell the workflow where to send updates. For Slack: Open the two nodes named "Send message in slack..." and select your desired channel from the Channel ID dropdown. For Notion: Open the two nodes named "Append a block in notion..." and paste the URL of the target Notion page or database into the Block ID field. Final Activation Once all configurations are complete, ensure the workflow is Saved and the toggle switch is set to Active. You are now ready to automate! Customization Guidance This template is a powerful foundation. Here’s how you can adapt it to your team's specific needs. Changing the PR Title or Body: Go to the "Request to create PR" (HTTP Request) node. In the JSON Body field, you can edit the title and body expressions. For example, you could add the committer's name ({{$('Webhook').item.json.body.pusher.name }}) or a link back to the JIRA task. Adapting to a Fixed Branching Strategy: If your team always creates pull requests against a single branch (e.g., develop), you can simplify the workflow. In the "Request to create PR" node, change the base value in the JSON body from {{...}} to your static branch name: "base": "develop". You can then remove the base branch logic from the "Commit Message Breakdown" (Code) node. Modifying Notification Messages: The text sent to Slack and Notion is fully customizable. Open any of the Slack or Notion nodes and edit the text fields. You can include any data from previous nodes, such as the PR URL ({{ $('Request to create PR').item.json.body.html_url }}) or the repository name. Adjusting the Commit Regex for Different Conventions: This is an advanced customization. If your team uses a different commit format (e.g., (DEV-123) instead of DEV-123), you can edit the regular expression in the "Commit Message Breakdown" (Code) node. Be sure to test your changes carefully. Adding/Removing Notification Channels: Don't use Notion? Simply delete the two Notion nodes. Want to send an email instead? Add a Gmail or SMTP node in parallel with a Slack node and configure it with the same data. Connect with us Website: https://www.intuz.com/n8n-workflow-automation-templates Email: [email protected] LinkedIn: https://www.linkedin.com/company/intuz Get Started: https://n8n.partnerlinks.io/intuz For Custom Worflow Automation Click here- Get Started

This workflow automatically processes customer support requests from emails and web forms, uses AI to classify and either auto-resolve simple issues or intelligently route complex ones to the right team members with proper JIRA tickets and SLA tracking. Key Benefits Multi-channel support (email + web forms) Smart routing to qualified agents based on expertise Consistent ticket creation with full context in JIRA Perfect For Support teams handling 50+ requests/day SaaS companies with tiered customer support Organizations wanting to scale support without hiring Teams needing consistent ticket classification Requirements Microsoft Outlook (email monitoring) OpenAI API (AI classification) JIRA Cloud (ticket management) n8n instance with AI nodes

Description Automates error detection and notification to prevent production downtime. Monitors incoming webhooks, filters critical errors, and triggers alerts or bug reports. Ensures rapid response to critical issues in real-time. Essential Information Processes webhook triggers to detect errors instantly. Filters and categorizes errors as critical or non-critical. Sends Slack alerts for critical errors and creates Jira bugs as needed. System Architecture Error Detection Pipeline**: Webhook Trigger: Captures incoming error data via POST requests. Filter Critical Errors: Identifies and separates critical errors. Alert Generation Flow**: Send Slack Alert: Notifies the team via Slack for critical errors. Create Jira Bug: Logs critical errors as Jira issues. Non-Critical Handling**: No Action for Non-Critical: Skips non-critical errors with no further action. Implementation Guide Import the workflow JSON into n8n. Configure webhook URL and test with sample error data. Set up Slack and Jira credentials for alerts and bug creation. Test error filtering and notification flows. Monitor alert accuracy and adjust filter rules as needed. Technical Dependencies Webhook service for error data ingestion. Slack API for real-time notifications. Jira API for bug tracking and issue creation. n8n for workflow automation. Customization Possibilities Adjust Filter Critical Errors node to refine error severity rules. Customize Slack alert messages in Send Slack Alert node. Modify Jira issue templates in Create Jira Bug node. Add logging node to track all errors for analysis. Integrate with additional notification tools (e.g., email).

This n8n workflow serves as an incident response and notification system for handling potentially malicious emails flagged by Sublime Security. It begins with a Webhook trigger that Sublime Security uses to initiate the workflow by POSTing an alert. The workflow then extracts message details from Sublime Security using an HTTP Request node, based on the provided messageId, and subsequently splits into two parallel paths. In the first path, the workflow looks up a Slack user by email, aiming to find the recipient of the email that triggered the alert. If a user is found in Slack, a notification is sent to them, explaining that they have received a potentially malicious email that has been quarantined and is under investigation. This notification includes details such as the email's subject and sender. The second path checks whether the flagged email has been opened by inspecting the read_at value from Sublime Security. If the email was opened, the workflow prepares a table summarizing the flagged rules and creates a corresponding issue in Jira Software. The Jira issue contains information about the email, including its subject, sender, and recipient, along with the flagged rules. Issues that someone might encounter when setting up this workflow for the first time include potential problems with the Slack user lookup if the user information is not available or if Slack API integration is not configured correctly. Additionally, the issue creation in Jira Software may not work as expected, as indicated by the note that mentions a need for possible node replacement. Thorough testing and validation with sample data from Sublime Security alerts can help identify and resolve any potential issues during setup.

The workflow is an automated process designed for incident management and tracking, specifically by integrating Splunk alerts with a Jira ticketing system using n8n. The initial step in the workflow is a Webhook Trigger, which is set up to receive POST requests with data from Splunk to initiate the workflow. Once the workflow is triggered, the "Set Host Name" node cleans up the hostname received from Splunk, ensuring that it is alphanumeric for consistency and security purposes. Subsequently, the "Search Ticket" node interacts with Jira through a Jira Query Language (JQL) request to locate any existing issues that match the sanitized hostname. The workflow splits at the "IF Ticket Not Exists" node, which checks for the presence of a key indicating a matching issue. If an issue exists, the workflow proceeds to add a comment to the identified issue, and if not, it creates a new Jira issue. At the false path, the "Add Ticket Comment" node appends a new comment to the existing Jira issue, encapsulating details from the Splunk alert, such as the timestamp and the alert description.

This workflow creates a Jira issue when a new ticket is created in Zendesk. Subsequent comments on the ticket in Zendesk are added as comments to the issue in Jira. Prerequisites Zendesk account and Zendesk credentials. Jira account and Jira credentials. Jira project to create issues in. How it works The workflow listens for new tickets in Zendesk. When a new ticket is created, the workflow creates a new issue in Jira. The Jira issue key is then saved in one of the ticket's fields (in setup we call this "Jira Issue Key"). The next time a comment is added to the ticket, the workflow retrieves the Jira issue key from the ticket's field and adds the comment to the issue in Jira. Setup This workflow requires that you set up a webhook in Zendesk. To do so, follow the steps below: In the workflow, open the On new Zendesk ticket node and copy the webhook URL. In Zendesk, navigate to Admin Center > Apps and integrations > Webhooks > Actions > Create Webhook. Add all the required details which can be retrieved from the On new Zendesk ticket node. The webhook URL gets added to the “Endpoint URL” field, and the “Request method” should match what is shown in n8n. Save the webhook. In Zendesk, navigate to Admin Center > Objects and rules > Business rules > Triggers > Add trigger. Give the trigger a name such as “New tickets”. Under “Conditions” in “Meet ALL of the following conditions”, add “Status is New”. Under “Actions”, select “Notify active webhook” and select the webhook you created previously. In the JSON body, add the following: { "id": "{{ticket.id}}", "comment": "{{ticket.latest_comment_html}}" } Save the Zendesk trigger. You will also need to set up a field in Zendesk to store the Jira issue key. To do so, follow the steps below: In Zendesk, navigate to Admin Center > Objects and rules > Tickets > Fields > Add field. Use the text field option and give the field a name such as “Jira Issue Key". Save the field. In n8n, open the Update ticket node and select the field you created in Zendesk.

This workflow is the third of three. You can find the other workflkows here: Incident Response Workflow - Part 1 Incident Response Workflow - Part 2 Incident Response Workflow - Part 3 We have the following nodes in the workflow: Webhook node: This trigger node listens to the event when the Resolve button is clicked. PagerDuty node: This node changes the status of the incident report from Acknowledged to Resolved in PagerDuty. Jira Software node: This node moves the incident issue to Done. Mattermost node: This node publishes a message in the auxiliary channel mentioning that the incident has been marked as resolved in PagerDuty and Jira. Mattermost node: This node publishes a message in the specified Incidents channel that the incident has been resolved by the on-call team.

This workflow automatically follows the steps in a custom incident response playbook and manages incidents in PagerDuty, Jira tickets, and notifies the on-call team in Mattermost. This workflow consists of three sub-workflows, each automating specific steps in the playbook. Read more about this use case and learn how to set up the workflows step-by-step in the blog tutorial How to automate every step of an incident response workflow. Prerequisites A PagerDuty account and credentials A Mattermost account and credentials A Jira account and credentials Nodes Webhook nodes trigger the workflows when an incident is created in PagerDuty, and when the incidedent is acknowledged and resolved. Mattermost nodes create an auxiliary channel for the on-call team to discuss the incident with buttons to acknowledge the incident and mark it as resolved. PagerDuty nodes update the status of the incident. Jira nodes create an issue about the incident and update its status when it's resolved.