Automated Edge Device Log Compression and Analysis via Webhook
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This n8n workflow automatically compresses and analyzes edge device logs received via a webhook. It utilizes Langchain nodes for text splitting, embedding, and querying a Redis vector store, ultimately archiving the processed logs in Google Sheets.
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About This Workflow
Overview
This workflow is designed to efficiently manage and analyze log data generated by edge devices. When a webhook receives new log entries, the workflow automatically processes them by splitting large logs into manageable chunks, generating embeddings, and storing them in a Redis vector database for quick retrieval and analysis. This enables intelligent querying of log data and ensures that valuable insights are captured and stored, preventing data loss and facilitating troubleshooting. The final processed logs are then appended to a Google Sheet for long-term archiving and reporting.
Key Features
- Real-time log ingestion via Webhook.
- Intelligent log chunking and processing using Langchain's Text Splitter.
- Semantic searching capabilities powered by Cohere Embeddings and a Redis Vector Store.
- Automated archival of processed logs to Google Sheets.
- Flexible agent-based processing for advanced analysis.
How To Use
- Configure the
Webhooknode to receive incoming log data from your edge devices. - Set up the
Splitternode with appropriatechunkSizeandchunkOverlapparameters. - Connect your Cohere API credentials to the
Embeddingsnode. - Configure the
InsertandQuerynodes with your Redis instance details and a desiredindexName. - Connect your Google Sheets credentials and specify the
sheetNamein theSheetnode. - Trigger the webhook with edge device logs to initiate the workflow.
Apps Used
Workflow JSON
{
"id": "617357a7-d03b-49aa-a5a8-3a7f0796598c",
"name": "Automated Edge Device Log Compression and Analysis via Webhook",
"nodes": 0,
"category": "IoT Automation",
"status": "active",
"version": "1.0.0"
}Note: This is a sample preview. The full workflow JSON contains node configurations, credentials placeholders, and execution logic.
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ID: 617357a7-d03b...
About the Author
Crypto_Watcher
Web3 Developer
Automated trading bots and blockchain monitoring workflows.
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