Automated Ticket Processing & File Handling System

Automates support ticket processing from Zammad with advanced file handling and logging.

⚙️ Automation & Workflows Productivity 🐍 Python FastAPI 🖥️ Backend
Automated Ticket Processing & File Handling System Cover

The Automated Ticket Processing & File Handling System for Zammad is a robust, production-ready solution that automates support ticket ingestion, enrichment, and downstream processing. Built to scale with enterprise-grade reliability, this system streamlines customer support workflows by bridging Zammad’s ticketing platform with advanced file handling, message queuing (RabbitMQ), and automation tooling (n8n, FastAPI). The result is faster ticket resolution, improved SLA compliance, and better operational visibility.

Key SEO-focused themes: automated ticket processing, Zammad integrations, support workflow automation, file handling, RabbitMQ logging, Slack notifications, n8n orchestration, FastAPI connectors.

Core capabilities include automatic ticket polling and webhook-driven ingestion from Zammad, intelligent file extraction and sanitization, metadata enrichment (attachments, sender, priority), and reliable queuing with RabbitMQ for downstream workers. The architecture separates fast acknowledgement paths from background processing, meaning ticket receipts are confirmed immediately while heavier tasks—OCR, virus scanning, large file uploads—are handled asynchronously.

Practical benefits include reduced manual triage time, consistent attachment handling, automated SLA tagging, and integrated notifications. Support agents receive contextual Slack alerts with summarized ticket content and actionable links, while exported artifacts (logs, sanitized attachments) are archived to cloud storage for compliance.

Example metrics and quick view:

Metric Typical Value Benefit
Tickets processed / day 5,000 Scales to enterprise volumes
Average processing latency < 2s (ack) / 45s (full) Fast acknowledgment + background work
Attachment types supported PDF, DOCX, PNG, ZIP Broad compatibility

Simple ASCII chart — processing stages:

Ingest -> Enrich -> Queue -> Process -> Notify

Steps to deploy and operate

  1. Configure Zammad webhooks for ticket create/update events.
  2. Deploy FastAPI connector to receive webhooks and perform light validation.
  3. Route payloads to RabbitMQ with routing keys based on priority and type.
  4. Configure n8n flows for enrichment: extract text, run OCR, classify, and store metadata.
  5. Wire Slack and logging integrations for real-time agent notifications and audit trails.

Challenges faced and solutions

  • Handling large attachments: initial designs attempted synchronous processing which caused timeouts; we solved this by switching to asynchronous queuing (RabbitMQ) and streaming uploads to object storage.
  • Ensuring idempotency: duplicate webhook deliveries required idempotent handlers with dedup keys and persistent dedupe caches in Redis.
  • Scaling OCR and ML enrichment: CPU-intensive tasks were moved to a separate worker pool with autoscaling and GPU-offload where available.
  • Maintaining data privacy: attachments are scanned and redacted before storing; access control rules are enforced at the storage layer.

Technical notes and SEO keywords

This solution combines Zammad APIs, FastAPI for lightweight HTTP handling, RabbitMQ for durable messaging, and n8n for low-code workflow orchestration. The system is containerized with Docker, making CI/CD and deployment to Kubernetes or ECS straightforward. For organizations optimizing support operations, this automated Zammad integration reduces mean time to resolution (MTTR) and increases support capacity without proportional headcount growth.

If you are evaluating support automation, consider this system for its modular architecture, clear SLAs, and extensible enrichment pipeline that can be adapted to any ticketing volume or attachment profile.

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