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OpsOrch

Unified API for Incidents, Logs, Metrics, and Tickets

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I built OpsOrch, an open-source orchestration layer that gives you one unified API for incidents, logs, metrics, tickets, messaging, and service metadata. It sits on top of the tools you already use (PagerDuty, Jira, Elasticsearch, Prometheus, Slack, etc.) and normalizes everything into a single schema.OpsOrch doesn’t store your operational data. It just brokers requests through pluggable adapters (Go or JSON-RPC) and returns unified structures. On top of this, there’s an optional MCP server that exposes all capabilities as typed tools for LLM agents.Why? Most incident workflows today require jumping across 5+ vendor UIs and APIs, each with its own query language and auth model. OpsOrch aims to be the small, transparent “glue layer” that removes that complexity without forcing a migration.What’s available now:Core orchestration service (Go, Apache-2.0)Adapters: PagerDuty, Jira, Prometheus, Elasticsearch, Slack, plus mock providersMCP server exposing incidents/logs/metrics/tickets/services as agent toolsNo vendor lock-in, no data gravityRepos: https://github.com/OpsOrch/opsorch-corehttps://github.com/OpsOrch/opsorch-mcp(+ adapters in the OpsOrch org)Would love feedback on architecture, adapter model, security concerns, and which integrations you’d want next.

HN · launched Dec 8, 2025 · 6 upvotes (top 73%) · 0 views

Niche: incident response software · 72 launches, 2 in the last 7 days ▼ -71% · Explore this niche →

Category and tags

  • Horizontal
  • Observability & eval
  • Developer
  • Not AI
  • Commercial product

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Could you build this?

Partial The front-end dashboard and workflow triggers are vibe-codeable, but creating a unified schema and resilient connector architecture across dozens of third-party monitoring, incident, and ticketing systems is complex engineering.

What it would actually take: The platform requires a Go or Node.js backend with an extensible adapter pattern normalizing data models across PagerDuty, Jira, Prometheus, Slack, and Elasticsearch. The hard parts are maintaining bi-directional syncing, rate limits, webhooks, and state consistency across heterogeneous third-party APIs while handling enterprise auth and RBAC.

Discussion

No comments on this launch.

Competitors

Other products that read as similar to this one : 112 launches clear the similarity bar, closest 8 shown.

Attention rank: #94 of 113 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).

Launched 37 days after the earliest competitor.

The niche, labels, vibe code rating and competitor comparison on this page are analysis by Nicheloom. If you use them, please credit nicheloom.com. How you may use our data.