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Checkup

GoDoc Sourcegraph

Checkup is distributed, lock-free, self-hosted health checks and status pages, written in Go.

It features an elegant, minimalistic CLI and an idiomatic Go library. They are completely interoperable and their configuration is beautifully symmetric.

Checkup was created by Matt Holt, author of the Caddy web server. It is maintained and sponsored by Sourcegraph. If you'd like to dive into the source, you can start here.

This tool is a work-in-progress. Please use liberally (with discretion) and report any bugs!

Recent changes

Due to recent development, some breaking changes have been introduced:

  • providers: the json config field provider was renamed to type for consistency,
  • notifiers: the json config field name was renamed to type for consistency,
  • sql: by default the sqlite storage engine is disabled (needs build with -tags sql to enable),
  • sql: storage engine is deprecated in favor of new storage engines postgres, mysql, sqlite3
  • mailgun: the to parameter now takes a list of e-mail addresses (was a single recipient)
  • LOGGING IS NOT SWALLOWED ANYMORE, DON'T PARSE checkup OUTPUT IN SCRIPTS
  • default for status page config has been set to local source (use with checkup serve)

If you want to build the latest version, it's best to run:

  • make build - builds checkup with mysql and postgresql support,
  • make build-sqlite3 - builds checkup with additional sqlite3 support

The resulting binary will be placed into builds/checkup.

Intro

Checkup can be customized to check up on any of your sites or services at any time, from any infrastructure, using any storage provider of your choice (assuming an integration exists for your storage provider). The status page can be customized to your liking since you can do your checks however you want. The status page is also mobile-responsive.

Checkup currently supports these checkers:

  • HTTP
  • TCP (+TLS)
  • DNS
  • TLS

Checkup implements these storage providers:

  • Amazon S3
  • Local file system
  • GitHub
  • MySQL
  • PostgreSQL
  • SQLite3
  • Azure Application Insights

Currently the status page does not support SQL or Azure Application Insights storage back-ends.

Checkup can even send notifications through your service of choice (if an integration exists).

How it Works

There are 3 components:

  1. Storage. You set up storage space for the results of the checks.
  2. Checks. You run checks on whatever endpoints you have as often as you want.
  3. Status Page. You (or GitHub) host the status page.

Quick Start

Download Checkup for your platform and put it in your PATH, or install from source:

$ go get -u github.com/sourcegraph/checkup/cmd/checkup

You'll need Go 1.8 or newer. Verify it's installed properly:

$ checkup --help

Then follow these instructions to get started quickly with Checkup.

Create your Checkup config

You can configure Checkup entirely with a simple JSON document. You should configure storage and at least one checker. Here's the basic outline:

{
    "checkers": [
        // checker configurations go here
    ],

    "storage": {
        // storage configuration goes here
    },

    "notifiers": [
        // notifier configuration goes here
    ]
}

Save the checkup configuration file as checkup.json in your working directory.

We will show JSON samples below, to get you started. But please refer to the godoc for a comprehensive description of each type of checker, storage, and notifier you can configure!

Here are the configuration structures you can use, which are explained fully in the godoc. Only the required fields are shown, so consult the godoc for more.

HTTP Checker

godoc: check/http

{
    "type": "http",
    "endpoint_name": "Example HTTP",
    "endpoint_url": "http://www.example.com"
    // for more fields, see the godoc
}

TCP Checker

godoc: check/tcp

{
    "type": "tcp",
    "endpoint_name": "Example TCP",
    "endpoint_url": "example.com:80"
}

DNS Checkers

godoc: check/dns

{
    "type": "dns",
    "endpoint_name": "Example of endpoint_url looking up host.example.com",
    "endpoint_url": "ns.example.com:53",
    "hostname_fqdn": "host.example.com"
}

TLS Checkers

godoc: check/tls

{
    "type": "tls",
    "endpoint_name": "Example TLS Protocol Check",
    "endpoint_url": "www.example.com:443"
}

Exec Checkers

godoc: check/exec

The exec checker can run any command, and expects an zero-value exit code on success. Non-zero exit codes are considered errors. You can configure the check with "raise":"warning" if you want to consider a failing service as DEGRADED. Additional options available on godoc link above.

{
    "type": "exec",
    "name": "Example Exec Check",
    "command": "testdata/exec.sh"
}

Amazon S3 Storage

godoc: S3

{
    "type": "s3",
    "access_key_id": "<yours>",
    "secret_access_key": "<yours>",
    "bucket": "<yours>",
    "region": "us-east-1"
}

To serve files for your status page from S3, copy statuspage/config_s3.js over statuspage/config.js, and fill out the required public, read-only credentials.

File System Storage

godoc: FS

{
    "type": "fs",
    "dir": "/path/to/your/check_files"
}

GitHub Storage

godoc: GitHub

{
    "type": "github",
    "access_token": "some_api_access_token_with_repo_scope",
    "repository_owner": "owner",
    "repository_name": "repo",
    "committer_name": "Commiter Name",
    "committer_email": "[email protected]",
    "branch": "gh-pages",
    "dir": "updates",
    "commit_message_suffix": "[ci skip]"
}
  • "dir" is a subdirectory within the repo to push all the check files
  • "commit_message_suffix" is appended to each commit message (default: "[ci skip]", to remove set to " " (single space))

Setup instructions:

  1. Create a repository,
  2. Copy the contents of statuspage/ from this repo to the root of your new repo,
  3. Update the URL in config.js to https://your-username.github.com/dir/,
  4. Create updates/.gitkeep,
  5. Enable GitHub Pages in your settings for your desired branch.

MySQL Storage

godoc: storage/mysql

A MySQL database can be configured as a storage backend.

Example configuration:

{
    "type": "mysql",
    "create": true,
    "dsn": "checkup:checkup@tcp(mysql-checkup-db:3306)/checkup"
}

When create is set to true, checkup will issue CREATE TABLE statements required for storage.

SQLite3 Storage (requires CGO to build, not available as a default)

godoc: storage/sqlite3

A SQLite3 database can be configured as a storage backend.

Example configuration:

{
    "type": "sqlite3",
    "create": true,
    "dsn": "/path/to/your/sqlite.db"
}

When create is set to true, checkup will issue CREATE TABLE statements required for storage.

PostgreSQL Storage

godoc: storage/postgres

A PostgreSQL database can be configured as a storage backend.

Example configuration:

{
    "type": "postgres",
    "dsn": "host=postgres-checkup-db user=checkup password=checkup dbname=checkup sslmode=disable"
}

When create is set to true, checkup will issue CREATE TABLE statements required for storage.

Azure Application Insights Storage

godoc: appinsights

Azure Application Insights can be used as a storage backend, enabling Checkup to be used as a source of custom availability tests and metrics. An example use case is documented here.

A sample storage configuration with retries enabled:

{
  "type": "appinsights",
  "test_location": "data center 1",
  "instrumentation_key": "11111111-1111-1111-1111-111111111111",
  "retry_interval": 1,
  "max_retries": 3,
  "tags": {
    "service": "front end",
    "product": "main web app"
  }
} 

The following keys are optional:

  • test_location (default is Checkup Monitor)
  • retry_interval (default is 0)
  • max_retries (default is 0)
  • timeout (defaults to 2 seconds if omitted or set to 0)
  • tags

If retries are disabled, the plugin will wait up to timeout seconds to submit telemetry before closing.

When check results are sent to Application Insights, the following values are included in the logged telemetry:

  • success is set to 1 if the check passes, 0 otherwise
  • message is set to Up, Down, or Degraded
  • duration is set to the average of all check result round-trip times and is displayed as a string in milliseconds
  • customMeasurements is set to a JSON object including the number of the check as a string and the round-trip time of the check in nanoseconds
  • If the check included a threshold_rtt setting, it will be added to the customDimensions JSON object as key ThresholdRTT with a time duration string value (ie: 200ms)
  • If any tags were included in the storage configuation, they will be added to the customDimensions JSON object

Currently the status page does not support Application Insights storage.

Slack notifier

Enable notifications in Slack with this Notifier configuration:

{
    "type": "slack",
    "username": "username",
    "channel": "#channel-name",
    "webhook": "webhook-url"
}

Follow these instructions to create a webhook.

Mail notifier

Enable E-mail notifications with this Notifier configuration:

{
    "type": "mail",
    "from": "[email protected]",
    "to": [ "[email protected]", "[email protected]" ],
    "subject": "Custom subject line",
    "smtp": {
        "server": "smtp.example.com",
        "port": 25,
        "username": "username",
        "password": "password"
    }
}

The settings for subject, smtp.port (default to 25), smtp.username and smtp.password are optional.

Mailgun notifier

Enable notifications using Mailgun with this Notifier configuration:

{
    "type": "mailgun",
    "from": "[email protected]",
    "to": [ "[email protected]", "[email protected]" ],
    "subject": "Custom subject line"
    "apikey": "mailgun-api-key",
    "domain": "mailgun-domain",
}

Pushover notifier

Enable notifications using Pushover with this Notifier configuration:

{
    "type": "pushover",
    "token": "API_TOKEN",
    "recipient": "USER_KEY"
    "subject": "Custom subject line"
}

Setting up storage on S3

The easiest way to do this is to give an IAM user these two privileges (keep the credentials secret):

  • arn:aws:iam::aws:policy/IAMFullAccess
  • arn:aws:iam::aws:policy/AmazonS3FullAccess

Implicit Provisioning

If you give these permissions to the same user as with the credentials in your JSON config above, then you can simply run:

$ checkup provision

and checkup will read the config file and provision S3 for you. If the user is different, you may want to use explicit provisioning instead.

This command creates a new IAM user with read-only permission to S3 and also creates a new bucket just for your check files. The credentials of the new user are printed to your screen. Make note of the Public Access Key ID and Public Access Key! You won't be able to see them again.

IMPORTANT SECURITY NOTE: This new IAM user will have read-only permission to all S3 buckets in your AWS account, and its credentials will be visible to any visitor to your status page. If you do not want to grant visitors to your status page read access to all your S3 buckets, you need to modify this IAM user's permissions to scope its access to the Checkup bucket. If in doubt, restrict access to your status page to trusted visitors. It is recommended that you do NOT include ANY sensitive credentials on the machine running Checkup.

Explicit Provisioning

If you do not prefer implicit provisioning using your checkup.json file, do this instead. Export the information to environment variables and run the provisioning command:

$ export AWS_ACCESS_KEY_ID=...
$ export AWS_SECRET_ACCESS_KEY=...
$ export AWS_BUCKET_NAME=...
$ checkup provision s3

Manual Provisioning

If you'd rather do this manually, see the instructions on the wiki but keeping in mind the region must be US Standard.

Checkup status page

Checkup now has a local HTTP server that supports serving checks stored in:

  • FS (local filesystem storage),
  • MySQL
  • PostgreSQL
  • SQLite3 (not enabled by default)

You can run checkup serve from the folder which contains checkup.json and the statuspage/ folder.

Setting up the status page for GitHub

You will need to edit `

Setting up the status page for S3

In statuspage/js, use the contents of config_s3.js to fill out config.js, which is used by the status page. This is where you specify how to access the S3 storage bucket you just provisioned for check files.

As you perform checks, the status page will update every so often with the latest results. Only checks that are stored will appear on the status page.

Performing checks

You can run checks many different ways: cron, AWS Lambda, or a time.Ticker in your own Go program, to name a few. Checks should be run on a regular basis. How often you run checks depends on your requirements and how much time you render on the status page.

For example, if you run checks every 10 minutes, showing the last 24 hours on the status page will require 144 check files to be downloaded on each page load. You can distribute your checks to help avoid localized network problems, but this multiplies the number of files by the number of nodes you run checks on, so keep that in mind.

Performing checks with the checkup command is very easy.

Just cd to the folder with your checkup.json from earlier, and checkup will automatically use it:

$ checkup

The vanilla checkup command runs a single check and prints the results to your screen, but does not save them to storage for your status page.

To store the results instead, use --store:

$ checkup --store

If you want Checkup to loop forever and perform checks and store them on a regular interval, use this:

$ checkup every 10m

And replace the duration with your own preference. In addition to the regular time.ParseDuration() formats, you can use shortcuts like second, minute, hour, day, or week.

You can also get some help using the -h option for any command or subcommand.

Posting status messages

Site reliability engineers should post messages when there are incidents or other news relevant for a status page. This is also very easy:

$ checkup message --about=Example "Oops. We're trying to fix the problem. Stay tuned."

This stores a check file with your message attached to the result for a check named "Example" which you configured in checkup.json earlier.

Doing all that, but with Go

Checkup is as easy to use in a Go program as it is on the command line.

Using Go to set up storage on S3

First, create an IAM user with credentials as described in the section above.

Then go get github.com/sourcegraph/checkup and import it.

Then replace ACCESS_KEY_ID and SECRET_ACCESS_KEY below with the actual values for that user. Keep those secret. You'll also replace BUCKET_NAME with the unique bucket name to store your check files:

storage := checkup.S3{
	AccessKeyID:     "ACCESS_KEY_ID",
	SecretAccessKey: "SECRET_ACCESS_KEY",
	Bucket:          "BUCKET_NAME",
}
info, err := storage.Provision()
if err != nil {
	log.Fatal(err)
}
fmt.Println(info) // don't lose this output!

This method creates a new IAM user with read-only permission to S3 and also creates a new bucket just for your check files. The credentials of the new user are printed to your screen. Make note of the PublicAccessKeyID and PublicAccessKey! You won't be able to see them again.

Using Go to perform checks

First, go get github.com/sourcegraph/checkup and import it. Then configure it:

c := checkup.Checkup{
	Checkers: []checkup.Checker{
		checkup.HTTPChecker{Name: "Example (HTTP)", URL: "http://www.example.com", Attempts: 5},
		checkup.HTTPChecker{Name: "Example (HTTPS)", URL: "https://www.example.com", Attempts: 5},
		checkup.TCPChecker{Name:  "Example (TCP)", URL:  "www.example.com:80", Attempts: 5},
		checkup.TCPChecker{Name:  "Example (TCP SSL)", URL:  "www.example.com:443", Attempts: 5, TLSEnabled: true},
		checkup.TCPChecker{Name:  "Example (TCP SSL, self-signed certificate)", URL:  "www.example.com:443", Attempts: 5, TLSEnabled: true, TLSCAFile: "testdata/ca.pem"},
		checkup.TCPChecker{Name:  "Example (TCP SSL, validation disabled)", URL:  "www.example.com:8443", Attempts: 5, TLSEnabled: true, TLSSkipVerify: true},
		checkup.DNSChecker{Name:  "Example DNS test of ns.example.com:53 looking up host.example.com", URL:  "ns.example.com:53", Host: "host.example.com", Attempts: 5},
	},
	Storage: checkup.S3{
		AccessKeyID:     "<yours>",
		SecretAccessKey: "<yours>",
		Bucket:          "<yours>",
		Region:          "us-east-1",
		CheckExpiry:     24 * time.Hour * 7,
	},
}

This sample checks 2 endpoints (HTTP and HTTPS). Each check consists of 5 attempts so as to smooth out the final results a bit. We will store results on S3. Notice the CheckExpiry value. The checkup.S3 type is also checkup.Maintainer type, which means it can maintain itself and purge any status checks older than CheckExpiry. We chose 7 days.

Then, to run checks every 10 minutes:

c.CheckAndStoreEvery(10 * time.Minute)
select {}

CheckAndStoreEvery() returns a time.Ticker that you can stop, but in this case we just want it to run forever, so we block forever using an empty select.

Using Go to post status messages

Simply perform a check, add the message to the corresponding result, and then store it:

results, err := c.Check()
if err != nil {
	// handle err
}

results[0].Message = "We're investigating connectivity issues."

err = c.Storage.Store(results)
if err != nil {
	// handle err
}

Of course, real status messages should be as descriptive as possible. You can use HTML in them.

Other topics

Getting notified when there are problems

Uh oh, having some fires? 🔥 You can create a type that implements checkup.Notifier. Checkup will invoke Notify() after every check, where you can evaluate the results and decide if and how you want to send a notification or trigger some event.

Other kinds of checks or storage providers

You can implement your own Checker and Storage types. If it's general enough, feel free to submit a pull request so others can use it too!

Building Locally

Requires Go v1.14 or newer. Building with the latest Go version is encouraged.

git clone [email protected]:sourcegraph/checkup.git
cd checkup
make

Building the SQLite3 enabled version is done with make build-sqlite3. PostgreSQL and MySQL are enabled by default.

Building a Docker image

If you would like to run checkup in a docker container, building it is done by running make docker. It will build the version without sql support. An SQL supported docker image is currently not provided, but there's a plan to do that in the future.