Automation2025
in progress
Cognitive Workflow Pipeline
Self-healing enterprise webhook infrastructure.
n8nPythonDockerPostgreSQL
▸▸ 01 — Overview
The Challenge
Manual intervention in failed asynchronous webhooks was creating significant operational delays. Support engineers spent 20+ hours weekly diagnosing raw API payloads.
Key Outcomes
- Automated 80% of Level 1 payload triages
- Reduced error identification time from 15 minutes to <2 seconds
- Established a scalable Dockerized instance topology
▸▸ 02 — Visuals
IMAGE PENDING
n8n Sub-workflow execution map
▸▸ 03 — Process
Infrastructure Scaling
Set up highly available n8n Docker containers connected to a central PostgreSQL database to handle up to 5,000 tasks per hour.
Docker Composen8n
Python Log Parser
Wrote a bespoke Python queue consumer to ingest incoming failed trace chunks and format them cleanly for alert broadcasting.
PythonFastAPI
▸▸ 04 — Engineering
Impact
Completely eliminated dead-letter queues by introducing automatic retry mechanics managed intelligently by the system.
▸▸ 05 — Network Logs