gatus

Gatus is a developer-oriented health dashboard that gives you the ability to monitor your services using HTTP, ICMP, TCP, and even DNS queries as well as evaluate the result of said queries by using a list of conditions on values like the status code, the response time, the certificate expiration, the body and many others. The icing on top is that each of these health checks can be paired with alerting via Slack, Teams, PagerDuty, Discord, Twilio and many more.

I personally deploy it in my Kubernetes cluster and let it monitor the status of my core applications: https://status.twin.sh/

Looking for a managed solution? Check out Gatus.io.

docker run -p 8080:8080 --name gatus twinproduction/gatus

docker run -p 8080:8080 --name gatus ghcr.io/twin/gatus

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Table of Contents

• Table of Contents
• Why Gatus?
• Features
• Usage
• Configuration
  • Endpoints
  • External Endpoints
  • Conditions
    • Placeholders
    • Functions
  • Storage
  • Client configuration
  • Alerting
    • Configuring Discord alerts
    • Configuring Email alerts
    • Configuring GitHub alerts
    • Configuring GitLab alerts
    • Configuring Google Chat alerts
    • Configuring Gotify alerts
    • Configuring JetBrains Space alerts
    • Configuring Matrix alerts
    • Configuring Mattermost alerts
    • Configuring Messagebird alerts
    • Configuring Ntfy alerts
    • Configuring Opsgenie alerts
    • Configuring PagerDuty alerts
    • Configuring Pushover alerts
    • Configuring Slack alerts
    • Configuring Teams alerts
    • Configuring Telegram alerts
    • Configuring Twilio alerts
    • Configuring AWS SES alerts
    • Configuring custom alerts
    • Setting a default alert
  • Maintenance
  • Security
    • Basic Authentication
    • OIDC
  • TLS Encryption
  • Metrics
  • Connectivity
  • Remote instances (EXPERIMENTAL)
• Deployment
  • Docker
  • Helm Chart
  • Terraform
• Running the tests
• Using in Production
• FAQ
  • Sending a GraphQL request
  • Recommended interval
  • Default timeouts
  • Monitoring a TCP endpoint
  • Monitoring a UDP endpoint
  • Monitoring a SCTP endpoint
  • Monitoring a WebSocket endpoint
  • Monitoring an endpoint using ICMP
  • Monitoring an endpoint using DNS queries
  • Monitoring an endpoint using SSH
  • Monitoring an endpoint using STARTTLS
  • Monitoring an endpoint using TLS
  • Monitoring domain expiration
  • disable-monitoring-lock
  • Reloading configuration on the fly
  • Endpoint groups
  • Exposing Gatus on a custom path
  • Exposing Gatus on a custom port
  • Configuring a startup delay
  • Keeping your configuration small
  • Proxy client configuration
  • Badges
    • Uptime
    • Health
    • Health (Shields.io)
    • Response time
      • How to change the color thresholds of the response time badge
  • API
  • Installing as binary
  • High level design overview

Why Gatus?

Before getting into the specifics, I want to address the most common question:

Why would I use Gatus when I can just use Prometheus’ Alertmanager, Cloudwatch or even Splunk?

Neither of these can tell you that there’s a problem if there are no clients actively calling the endpoint. In other words, it's because monitoring metrics mostly rely on existing traffic, which effectively means that unless your clients are already experiencing a problem, you won't be notified.

Gatus, on the other hand, allows you to configure health checks for each of your features, which in turn allows it to monitor these features and potentially alert you before any clients are impacted.

A sign you may want to look into Gatus is by simply asking yourself whether you'd receive an alert if your load balancer was to go down right now. Will any of your existing alerts be triggered? Your metrics won’t report an increase in errors if no traffic makes it to your applications. This puts you in a situation where your clients are the ones that will notify you about the degradation of your services rather than you reassuring them that you're working on fixing the issue before they even know about it.

Features

The main features of Gatus are:

• Highly flexible health check conditions: While checking the response status may be enough for some use cases, Gatus goes much further and allows you to add conditions on the response time, the response body and even the IP address.
• Ability to use Gatus for user acceptance tests: Thanks to the point above, you can leverage this application to create automated user acceptance tests.
• Very easy to configure: Not only is the configuration designed to be as readable as possible, it's also extremely easy to add a new service or a new endpoint to monitor.
• Alerting: While having a pretty visual dashboard is useful to keep track of the state of your application(s), you probably don't want to stare at it all day. Thus, notifications via Slack, Mattermost, Messagebird, PagerDuty, Twilio, Google chat and Teams are supported out of the box with the ability to configure a custom alerting provider for any needs you might have, whether it be a different provider or a custom application that manages automated rollbacks.
• Metrics
• Low resource consumption: As with most Go applications, the resource footprint that this application requires is negligibly small.
• Badges:
• Dark mode

Usage

docker run -p 8080:8080 --name gatus twinproduction/gatus

docker run -p 8080:8080 --name gatus ghcr.io/twin/gatus

Here's a simple example:

endpoints:
  - name: website                 # Name of your endpoint, can be anything
    url: "https://twin.sh/health"
    interval: 5m                  # Duration to wait between every status check (default: 60s)
    conditions:
      - "[STATUS] == 200"         # Status must be 200
      - "[BODY].status == UP"     # The json path "$.status" must be equal to UP
      - "[RESPONSE_TIME] < 300"   # Response time must be under 300ms

  - name: make-sure-header-is-rendered
    url: "https://example.org/"
    interval: 60s
    conditions:
      - "[STATUS] == 200"                          # Status must be 200
      - "[BODY] == pat(*<h1>Example Domain</h1>*)" # Body must contain the specified header

This example would look similar to this:

By default, the configuration file is expected to be at config/config.yaml.

You can specify a custom path by setting the GATUS_CONFIG_PATH environment variable.

If GATUS_CONFIG_PATH points to a directory, all *.yaml and *.yml files inside said directory and its subdirectories are merged like so:

• All maps/objects are deep merged (i.e. you could define alerting.slack in one file and alerting.pagerduty in another file)
• All slices/arrays are appended (i.e. you can define endpoints in multiple files and each endpoint will be added to the final list of endpoints)
• Parameters with a primitive value (e.g. debug, metrics, alerting.slack.webhook-url, etc.) may only be defined once to forcefully avoid any ambiguity
  • To clarify, this also means that you could not define alerting.slack.webhook-url in two files with different values. All files are merged into one before they are processed. This is by design.

💡 You can also use environment variables in the configuration file (e.g. $DOMAIN, ${DOMAIN})

See examples/docker-compose-postgres-storage/config/config.yaml for an example.

If you want to test it locally, see Docker.

Configuration

Endpoints

Endpoints are URLs, applications, or services that you want to monitor. Each endpoint has a list of conditions that are evaluated on an interval that you define. If any condition fails, the endpoint is considered as unhealthy. You can then configure alerts to be triggered when an endpoint is unhealthy once a certain threshold is reached.