About This Architecture

Event-driven distributed ticketing system using Kafka as the central nervous system, ingesting tickets from JIRA, PagerDuty, and internal services (Fabric, Keystone) through dedicated API pollers and consumers. Ticket Normalizer standardizes incoming events onto the core Kafka Event Bus, which fans out to Ticket Enrichment Worker, Source System Sync, Notification Service, and Reporting Process for parallel processing. Enriched tickets flow to MongoDB for persistent storage with replica sets, while IMDG Update Worker maintains an in-memory data grid synchronized via SSE/WebSocket to deliver real-time updates to the Browser UI Grid. This architecture decouples ingestion, processing, and delivery, enabling independent scaling and fault isolation across layers. Fork and customize this diagram on Diagrams.so to adapt the topology for your ticketing requirements, swap Kafka for alternative event brokers, or extend with additional consumers.

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How do you design a scalable distributed ticketing system that ingests from multiple sources and delivers real-time updates?

This diagram shows a Kafka-based event-driven architecture where JIRA API Poller, PagerDuty API Poller, and internal consumers (Fabric, Keystone) feed normalized tickets into a core event bus. Parallel workers enrich tickets, sync to source systems, send notifications, and populate MongoDB for persistence, while IMDG Update Worker maintains a real-time in-memory cache delivered to the UI via WebSo