Tool overview
Overview
OpenAI Downtime Monitor is a free, developer-focused status dashboard that continuously tracks uptime, latency, and incident history for OpenAI APIs and other major LLM providers. Instead of manually refreshing provider status pages or guessing whether an error is in your code or on the platform side, you get a clear, real-time view of API health in one place. The tool collects and visualizes performance metrics for different OpenAI models and endpoints, helping you quickly spot regional issues, model-specific slowdowns, and partial outages. Historical charts make it easy to correlate traffic spikes, deployment changes, or error rate increases with provider incidents, so you can debug faster and communicate more transparently with your team and stakeholders. OpenAI Downtime Monitor is ideal for teams running production workloads on GPT models, RAG pipelines, or multi-provider LLM routing. It lets you make data-driven decisions, such as automatically failing over to a backup provider or temporarily disabling certain
features
when latency crosses a threshold. Because the monitor is free and accessible via the web, every engineer, SRE, or product manager can use it without extra setup. Whether you’re building a high-traffic AI product or a small internal tool, OpenAI Downtime Monitor gives you the operational visibility you need to ship reliable, stable AI experiences.
Screenshots
Features
- Real-time OpenAI API status
- Cross-provider uptime comparison
- Per-model latency monitoring
- Historical incident timelines
- Region and endpoint breakdowns
- Production-ready reliability insights
- Free web-based status dashboard
- Developer-friendly performance metrics
Tags
Use Cases
Monitor production GPT workloads to quickly detect provider outages or latency spikes before they impact end users.
Debug API errors by correlating your application failures with real-time and historical OpenAI incident data.
Operate multi-LLM routing by tracking the health of different providers and deciding when to fail over.
Share a single source of truth on OpenAI performance with engineering, SRE, and product teams during incidents.
Plan capacity and SLAs using historical uptime and latency trends across models and regions.
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