FireHydrant Alternative: Open Source AI Incident Management

Key Takeaway: FireHydrant is a solid incident management platform — but it was is an all-in-one incident management platform that helps teams plan, respond to, and learn from incidents. Their tagline: "Fight Fires Faster." They claim teams resolve incidents (NASDAQ: FRSH). The platform will become the incident management and reliability layer inside Freshservice, Freshworks' ITSM product.

Notable customers: (saving 30-90 minutes per incident), Snyk, LaunchDarkly, AuditBoard, Qlik, Avalara.

What is Aurora?

):

• AI-generated incident summaries from Slack messages


• Automated event timelines


• Real-time call transcription (Zoom, Google Meet) with key point summarization


• AI-drafted retrospectives with contributing factors and suggested action items


• Stakeholder update generation

FireHydrant's AI is documentation-focused — it summarizes what happened, transcribes calls, and drafts retrospectives. It does not autonomously investigate root causes or query infrastructure.

Aurora AI:

• Multi-agent architecture via LangGraph with dynamic tool selection (30+ tools)


• Correlates alerts across services and dependencies


• Constructs investigation timelines linking deployments, infra events, and telemetry


• Generates structured RCA with evidence citations and remediation steps


• Human-in-the-loop for write/destructive actions — read-only commands run automatically


• Executes kubectl, aws, az, gcloud commands in sandboxed Kubernetes pods


• Queries cloud APIs directly — AWS, Azure, GCP, OVH, Scaleway


• Traverses Memgraph infrastructure dependency graph for blast radius


• Searches Weaviate knowledge base (vector search over runbooks and past incidents)


• Suggests code fixes with diff preview — human approves and creates PR


• Works with any LLM provider including local models via Ollama

Incident Response & Coordination

FireHydrant is strong at incident coordination:

• Slack and Microsoft Teams chatbot


• Automated runbooks (triggered by severity, service, or custom fields)


• Incident roles and assignments


• Service catalog with dependency mapping and deployment tracking


• ):
  
  
  
  
  
  • Free trial: 2 weeks, up to 10 responders
  
  
  • Platform Pro: $9,600/year (flat, up to 20 responders)
  
  
  • Enterprise: Custom pricing (required for AI features)
  
  
  • Alerting is consumption-based (separate from platform fee)
  
  
  
  
  

  Aurora:

  
  
  
  
  
  • 
    Free — Apache 2.0, self-hosted
  
  
  • Costs: infrastructure + LLM API usage
  
  
  • $0 LLM cost with Ollama local models
  
  
  
  
  

  
  

  Note: FireHydrant AI features (summaries, transcripts, triage, retrospectives) are only available on the Enterprise tier. Pro users do not get AI capabilities.

  
  

  
  
  

  
  
  
  The Freshworks Acquisition Factor
  

  
  
  

  FireHydrant was and they'll build it with you.

Limitations of Aurora

Aurora is powerful for investigation but doesn't replace a full incident coordination platform:

• 
  No on-call scheduling — use PagerDuty, Grafana OnCall, or Opsgenie alongside Aurora


• 
  No status pages — use Atlassian Statuspage, incident.io, or Instatus


• 
  Slack only — no Microsoft Teams support currently


• 
  No mobile app — investigation results are accessed via web dashboard


• 
  SOC 2 Type II in progress — not yet certified (FireHydrant has SOC 2)


• 
  Self-hosted requires infrastructure — you maintain the Docker/K8s deployment

"We built Aurora for one job — investigating why incidents happen. We deliberately didn't build on-call or status pages because tools like PagerDuty and FireHydrant already do those well. Aurora is the investigation layer that plugs into your existing stack." — Noah Casarotto-Dinning, CEO at Arvo AI

Getting Started with Aurora

CODE Kopieren

git clone https://github.com/Arvo-AI/aurora.git

cd aurora

make init

make prod-prebuilt

Configure your monitoring webhooks, add cloud credentials, and investigations start automatically. See the . For other comparisons, see , and . Aurora data from github.com/Arvo-AI/aurora. Last verified: April 2026.