Gatus — Automated Status Page with Health Checks & Alerts

What it is

Gatus is a developer-oriented health monitoring tool that checks service availability and displays results on a status page. Endpoints are defined in YAML configuration files with conditions that must be met for a service to be considered healthy. Gatus checks HTTP responses, DNS records, TCP connections, and more on configurable intervals.

It targets DevOps engineers and development teams who want a lightweight status page and health monitoring system without the overhead of full monitoring platforms like Prometheus or Datadog.

How it saves time or tokens

Gatus replaces the need to build a custom status page. Define your endpoints and health conditions in YAML, deploy Gatus, and you have a production-ready status page with uptime history, response time charts, and embeddable badges.

The condition-based health checking is more flexible than simple up/down pings. You can check HTTP status codes, response body content, response time thresholds, certificate expiration, and DNS resolution results in a single endpoint definition.

How to use

1. Create a config.yaml defining your endpoints with health conditions. Each endpoint specifies a URL, check interval, and conditions to evaluate.
2. Deploy Gatus with Docker: docker run -p 8080:8080 -v ./config.yaml:/config/config.yaml twinproduction/gatus. The status page is available at port 8080.
3. Configure alerting to receive notifications via Slack, Discord, PagerDuty, email, or webhooks when endpoints fail their health conditions.

Example

# config.yaml
endpoints:
  - name: API
    url: 'https://api.example.com/health'
    interval: 60s
    conditions:
      - '[STATUS] == 200'
      - '[RESPONSE_TIME] < 500'
      - '[BODY].status == up'
    alerts:
      - type: slack
        send-on-resolved: true

  - name: Website
    url: 'https://example.com'
    interval: 120s
    conditions:
      - '[STATUS] == 200'
      - '[CERTIFICATE_EXPIRATION] > 720h'

  - name: Database
    url: 'tcp://db.example.com:5432'
    interval: 30s
    conditions:
      - '[CONNECTED] == true'

alerting:
  slack:
    webhook-url: 'https://hooks.slack.com/services/xxx/yyy/zzz'

Related on TokRepo

• AI tools for monitoring — Monitoring and observability tools
• AI tools for DevOps — Infrastructure management and automation

Common pitfalls

• Defining too many conditions without understanding precedence. If any condition fails, the endpoint is marked unhealthy. Start with basic status code checks and add response time and body checks incrementally.
• Not configuring persistent storage for uptime history. Without a database (SQLite or PostgreSQL), Gatus loses all historical data on restart. Mount a volume for the SQLite database to persist uptime records.
• Checking endpoints too frequently from a single instance. Very short intervals (under 10 seconds) can trigger rate limiting or appear as attack traffic to the monitored service. Use reasonable intervals for external endpoints.