Automated developer-oriented status page with alerting and incident support for monitoring services via HTTP, ICMP, TCP, and DNS.
Gatus is an automated, developer-oriented status page that monitors the health of services using HTTP, ICMP, TCP, and DNS queries. It evaluates responses with customizable conditions on status codes, response times, and certificate expiration, providing proactive alerting via Slack, PagerDuty, Discord, and other providers. It solves the problem of reactive monitoring by simulating client requests to detect issues before users are affected.
Developers, DevOps engineers, and SREs who need a self-hosted, proactive status page to monitor internal or external services with flexible health checks and alerting.
Gatus offers highly configurable health checks with support for multiple protocols and conditions, extensive alerting integrations, and a low-resource footprint. Unlike metrics-based tools, it proactively monitors services even without traffic, ensuring early detection of outages.
Automated developer-oriented status page with alerting and incident support
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Supports HTTP, ICMP, TCP, DNS, SSH, WebSocket, gRPC, and STARTTLS with customizable conditions on status codes, response times, body content, and certificate expiration, as detailed in the conditions section.
Integrates with over 30 alerting providers including Slack, PagerDuty, Discord, and custom webhooks, with detailed configuration examples for each in the README.
Simulates client requests to monitor services even without existing traffic, alerting before users are impacted, addressing a key gap in metrics-based tools as explained in the philosophy section.
Built in Go for minimal resource consumption, suitable for containerized environments, with benchmarks and Docker deployment options highlighted.
YAML configuration files can become verbose and intricate for many endpoints, with nested conditions, alert settings, and client configurations requiring careful management.
Storage defaults cap results at 100 and events at 50 per endpoint, which may not suffice for long-term trend analysis or large-scale monitoring without custom adjustments.
Key functionalities like suites for multi-step workflows are marked as ALPHA, and remote instances as EXPERIMENTAL, indicating potential instability or breaking changes.
Requires setup and ongoing maintenance for deployment, storage, and security, unlike managed alternatives, with dependencies on Docker or Kubernetes for optimal use.