Fireline: Agentic AI incident router for DevOps
Created by: Muhammad Hashmi & Syed Rayyan Ali
Fireline is a real-time incident room for support and infrastructure teams. It aggregates heterogeneous support events (tickets, error logs, uptime pings) into incidents, uses LLM-based triage to determine severity and ownership, and generates internal and external status updates.
What It Does
Ops/support teams struggle with fragmented signals—support tickets, error logs, uptime pings—without a unified incident view. Fireline is the first Agentic AI incident router for DevOps: it streams alerts into Redpanda, auto-triages them, and fires focused Slack alerts instead of alert storms.
How It Works
Fireline acts as an incident intelligence layer that:
Ingests events from multiple sources via Redpanda (Kafka-compatible streaming)
Aggregates events into incidents grouped by service and environment
Auto-triages incidents using LLM to determine severity, owner, and summary
Generates communications for both internal teams and external status pages
Sends Slack notifications (optional) to assigned engineers and escalates SEV2+ incidents to managers
Provides real-time visibility through a web UI showing incidents and status updates
Backend: Java 21 + Akka SDK (Agents, Consumers, KeyValueEntities, Views, HTTP Endpoints)
Streaming: Redpanda for event ingestion
LLM: OpenAI API for triage and communications generation
Frontend: Next.js + TypeScript for the incident room UI
Observability: Distributed tracing with Jaeger (OpenTelemetry)
Notifications: Slack integration for real-time alerts
What we learned
Akka SDK patterns: Agents, KeyValueEntities, Views, and component communication
Distributed tracing: OpenTelemetry integration and trace visualization with Jaeger
LLM safety: Prompt injection mitigation and structured output validation
Event-driven architecture: Building resilient systems with Kafka-compatible streaming