Oack is a monitoring, incident, and status page platform for engineering teams. It combines HTTP and browser checks, incident response, and customer-facing status pages in one place, with the stated aim of replacing separate tools with a single platform.
Its monitoring features include multi-location HTTP checks from 20+ locations, TCP telemetry, SSL and domain-expiry alerts, and scheduled Playwright test suites. The Playwright monitors can run login, checkout, and search flows. Oack also includes deep telemetry with TCP-level stats, Server-Timing parsing, CDN enrichment, HAR waterfalls, and latency percentiles, which it describes as helping diagnose issues down to the network layer.
For incident handling, the platform supports declaring, escalating, and resolving incidents. It includes on-call schedules with rotations, multi-step escalation policies, and post-mortems with AI-assisted root cause analysis. Status pages can be public or private, and they can sync with monitor failures to create incidents automatically. Those pages also support subscriber notifications, scheduled maintenance, custom domains, and branding.
Oack is delivered as a web platform and includes Terraform, API clients for Go, Python, and Node, a CLI, and an MCP server for AI agents to query monitors and manage incidents directly. The site says teams can start with a health check in two minutes and begin for free, but it does not describe license terms.
In the Uptime & status pages space, Oack takes a focused approach. It focuses on managing monitoring, incident response, and status communication without juggling multiple tools. It is built as a B2B product for engineering teams. Oack follows a freemium model, with paid plans starting at $19. It runs on the web and the command line.
Oack first shipped in 2024. Key capabilities include HTTP monitoring, browser checks, and incident management. The interface is available in 5 languages, including English, Spanish, and Japanese. It exposes integrations via a public API and an MCP server.
Summary written by a language model from the project’s public pages.
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