AWS News Monitoring & LinkedIn Content Automation with Claude 3 & Feishu

AWS News Analysis and LinkedIn Automation Pipeline

Transform AWS industry news into engaging LinkedIn content with AI-powered analysis and automated approval workflows.

Who's it for

This template is perfect for: Cloud architects and DevOps engineers** who want to stay current with AWS developments Content creators** looking to automate their AWS news coverage Marketing teams** needing consistent, professional AWS content Technical leaders** who want to share industry insights on LinkedIn AWS consultants** building thought leadership through automated content

How it works

This workflow creates a comprehensive AWS news analysis and content generation pipeline with two main flows:

Flow 1: News Collection and Analysis Scheduled RSS Monitoring: Automatically fetches latest AWS news from the official AWS RSS feed daily at 8 PM AI-Powered Analysis: Uses AWS Bedrock (Claude 3 Sonnet) to analyze each news item, extracting: Professional summary Key themes and keywords Importance rating (Low/Medium/High) Business impact assessment Structured Data Storage: Saves analyzed news to Feishu Bitable with approval status tracking

Flow 2: LinkedIn Content Generation Manual Approval Trigger: Feishu automation sends approved news items to the webhook AI Content Creation: AWS Bedrock generates professional LinkedIn posts with: Attention-grabbing headlines Technical insights from a Solutions Architect perspective Business impact analysis Call-to-action engagement Automated Publishing: Posts directly to LinkedIn with relevant hashtags

How to set up

Prerequisites AWS Bedrock access** with Claude 3 Sonnet model enabled Feishu account** with Bitable access LinkedIn company account** with posting permissions n8n instance** (self-hosted or cloud)

Detailed Configuration Steps

1. AWS Bedrock Setup

Step 1: Enable Claude 3 Sonnet Model Log into your AWS Console Navigate to AWS Bedrock Go to Model access in the left sidebar Find Anthropic Claude 3 Sonnet and click Request model access Fill out the access request form (usually approved within minutes) Once approved, verify the model appears in your Model access list

Step 2: Create IAM User and Credentials Go to IAM Console Click Users → Create user Name: n8n-bedrock-user Attach policy: AmazonBedrockFullAccess (or create custom policy with minimal permissions) Go to Security credentials tab → Create access key Choose Application running outside AWS Download the credentials CSV file

Step 3: Configure in n8n In n8n, go to Credentials → Add credential Select AWS credential type Enter your Access Key ID and Secret Access Key Set Region to your preferred AWS region (e.g., us-east-1) Test the connection

Useful Links: AWS Bedrock Documentation Claude 3 Sonnet Model Access AWS Bedrock Pricing

2. Feishu Bitable Configuration

Step 1: Create Feishu Account and App Sign up at Feishu International Create a new Bitable (multi-dimensional table) Go to Developer Console → Create App Enable Bitable permissions in your app Generate App Token and App Secret

Step 2: Create Bitable Structure Create a new Bitable with these columns: title (Text) pubDate (Date) summary (Long Text) keywords (Multi-select) rating (Single Select: Low, Medium, High) link (URL) approval_status (Single Select: Pending, Approved, Rejected)

Get your App Token and Table ID: App Token: Found in app settings Table ID: Found in the Bitable URL (tbl...)

Step 3: Set Up Automation In your Bitable, go to Automation → Create automation Trigger: When field value changes → Select approval_status field Condition: approval_status equals "Approved" Action: Send HTTP request Method: POST URL: Your n8n webhook URL (from Flow 2) Headers: Content-Type: application/json Body: {{record}}

Step 4: Configure Feishu Credentials in n8n Install Feishu Lite community node (self-hosted only) Add Feishu credential with your App Token and App Secret Test the connection

Useful Links: Feishu Developer Documentation Bitable API Reference Feishu Automation Guide

3. LinkedIn Company Account Setup

Step 1: Create LinkedIn App Go to LinkedIn Developer Portal Click Create App Fill in app details: App name: AWS News Automation LinkedIn Page: Select your company page App logo: Upload your logo Legal agreement: Accept terms

Step 2: Configure OAuth2 Settings In your app, go to Auth tab Add redirect URL: https://your-n8n-instance.com/rest/oauth2-credential/callback Request these scopes: w_member_social (Post on behalf of members) r_liteprofile (Read basic profile) r_emailaddress (Read email address)

Step 3: Get Company Page Access Go to your LinkedIn Company Page Navigate to Admin tools → Manage admins Ensure you have Content admin or Super admin role Note your Company Page ID (found in page URL)

Step 4: Configure LinkedIn Credentials in n8n Add LinkedIn OAuth2 credential Enter your Client ID and Client Secret Complete OAuth2 flow by clicking Connect my account Select your company page for posting

Useful Links: LinkedIn Developer Portal LinkedIn API Documentation LinkedIn OAuth2 Guide

4. Workflow Activation

Final Setup Steps: Import the workflow JSON into n8n Configure all credential connections: AWS Bedrock credentials Feishu credentials LinkedIn OAuth2 credentials Update webhook URL in Feishu automation to match your n8n instance Activate the scheduled trigger (daily at 8 PM) Test with manual webhook trigger using sample data Verify Feishu Bitable receives data Test approval workflow and LinkedIn posting

Requirements

Service Requirements AWS Bedrock** with Claude 3 Sonnet model access AWS account with Bedrock service enabled IAM user with Bedrock permissions Model access approval for Claude 3 Sonnet Feishu Bitable** for news storage and approval workflow Feishu account (International or Lark) Developer app with Bitable permissions Automation capabilities for webhook triggers LinkedIn Company Account** for automated posting LinkedIn company page with admin access LinkedIn Developer app with posting permissions OAuth2 authentication setup n8n community nodes**: Feishu Lite node (self-hosted only)

Technical Requirements n8n instance** (self-hosted recommended for community nodes) Webhook endpoint** accessible from Feishu automation Internet connectivity** for API calls and RSS feeds Storage space** for workflow execution logs

Cost Considerations AWS Bedrock**: ~$0.01-0.05 per news analysis Feishu**: Free tier available, paid plans for advanced features LinkedIn**: Free API access with rate limits n8n**: Self-hosted (free) or cloud subscription

How to customize the workflow

Content Customization Modify AI prompts** in the AI Agent nodes to change tone, focus, or target audience Adjust hashtags** in the LinkedIn posting node for different industries Change scheduling** frequency by modifying the Schedule Trigger settings

Integration Options Replace LinkedIn** with Twitter/X, Facebook, or other social platforms Add Slack notifications** for approved content before posting Integrate with CRM** systems to track content performance Add content calendar** integration for better planning

Advanced Features Multi-language support** by modifying AI prompts for different regions Content categorization** by adding tags for different AWS services Performance tracking** by integrating analytics platforms Team collaboration** by adding approval workflows with multiple reviewers

Technical Modifications Change RSS sources** to monitor other AWS blogs or competitor news Adjust AI models** to use different Bedrock models or external APIs Add data validation** nodes for better error handling Implement retry logic** for failed API calls

Important Notes

Service Limitations This template uses community nodes (Feishu Lite) and requires self-hosted n8n Geo-restrictions** may apply to AWS Bedrock models in certain regions Rate limits** may affect high-frequency posting - adjust scheduling accordingly Content moderation** is recommended before automated posting Cost considerations**: Each AI analysis costs approximately $0.01-0.05 USD per news item

Troubleshooting Common Issues

AWS Bedrock Issues: Model not found**: Ensure Claude 3 Sonnet access is approved in your region Access denied**: Verify IAM permissions include Bedrock service access Rate limiting**: Implement retry logic or reduce analysis frequency

Feishu Integration Issues: Authentication failed**: Check App Token and App Secret are correct Table not found**: Verify Table ID matches your Bitable URL Automation not triggering**: Ensure webhook URL is accessible and returns 200 status

LinkedIn Posting Issues: OAuth2 errors**: Re-authenticate LinkedIn credentials Posting failed**: Verify company page admin permissions Rate limits**: LinkedIn has daily posting limits for company pages

Security Best Practices Never hardcode credentials** in workflow nodes Use environment variables** for sensitive configuration Regularly rotate API keys** and access tokens Monitor API usage** to prevent unexpected charges Implement error handling** for failed API calls