Bucky uses a Node server to forward the HTTP requests with your monitoring data to Statsd/Graphite, OpenTSDB, or whatever other service you'd like.
Also see the Bucky Client.
Everything you need to run Bucky on Heroku or Nodejitsu is included, just update the config file and push to the service of your choice.
heroku create
git push heroku masterjitsu deployThe jitsu application will ask you for a subdomain to run the service on, and will increment the version of the application whenever you deploy.
If you'd rather host Bucky on EC2 directly or on raw hardware, you just need something
which will run ./start.js in a reliable way.
You can use environment variables to control runtime options, or put them in your config file
in the server section.
You'll need to have nodejs installed. Anything in the 0.8.x series or above should work fine. We recommend using nvm, as it gives you an extra dimension of flexibility, but using your system's package manager should work just as well.
# In the project directory:
npm install
PORT=3333 APP_ROOT=bucky/ ./start.jsThe APP_ROOT (or config.server.appRoot) will prefix all endpoints.
Bucky will respond to all requests at /APP_ROOT/v1/health-check, if you need a health check url.
Bucky can be setup to receive data at multiple endpoints, but by default it listens
to /APP_ROOT/v1/send on whichever port you specify.
# Install nodejs
# This assumes you're on a 64 bit machine
wget http://nodejs.org/dist/v0.10.19/node-v0.10.19-linux-x64.tar.gz
tar xvf node-v0.10.19-linux-x64.tar.gz
sudo ln -s `pwd`/node-v0.10.19-linux-x64/bin/{node,npm} /usr/local/bin/
# Grab a Bucky release
# You should use the latest release available at https://github.com/HubSpot/BuckyServer/releases
wget https://github.com/HubSpot/BuckyServer/archive/v0.3.0.tar.gz -O BuckyServer.tar.gz
tar xvf BuckyServer.tar.gz
cd BuckyServer
# Install Bucky
sudo npm install -g
# Make any config changes by editing /usr/local/lib/node_modules/bucky-server/config/default.yaml
# You can start bucky by running bucky-server
# Add the upstart script so Bucky starts on startup and respawns
sudo cp init/bucky-server.conf /etc/init/
# Start Bucky with
sudo start bucky-server
# Log files will appear in /var/log/bucky.log by defaultYou can run bucky on a specific port (make sure to open that port in your security group if you're using EC2), or you can use a reverse proxy like Nginx or HAProxy to serve it on the same domain and port as your website, it's up to you.
If you're not already running a stats collection service, you should take a look at our help doc.
Most people will only need to specify the config they're interested in and start up the server.
If you need more customization, you can write a module:
There are a few of types of modules:
- Logger - Use to have Bucky log to something other than the console
- Config - Use to have Bucky pull config from somewhere other than the default file
- App - Use to do things when Bucky loads and/or on requests. Auth, monitoring initialization, etc.
- Collectors - Use to send Bucky data to new and exciting places.
We can only have one logger and one config, but you can specify as many app and collector modules as you like.
All modules follow the same basic sketch. You export a method which is called when Bucky
starts up. That method is provided with as much of {app, config, logger} as we have
loaded so far, and is expected to call a callback when it's ready for the loading to continue.
Used to log output. Defaults to a wrapper around console.log/console.error.
Should export a function which will be called when the server is started:
module.exports = ({logger}, next) ->
# logger is the previous logger (just the console)
next myNewLoggerThis function should call the callback with a logger object which implements
log and error:
module.exports = ({logger}, next) ->
myNewLogger = {
log: ->
console.log "Bucky message:", arguments...
error: ->
console.error "Bucky error:", arguments...
}
next myNewLoggerBy default config comes from the config files loaded using the node config module.
If specified, this module will replace that config. Please note that the list of
modules comes from the config module, so the list of modules must always be
specified there. All other config options can be moved to your config solution
of choice using this extension point.
At HubSpot, we're believers in config which can be changed without restarting
services. For this reason, the config api is a bit more complex than you might
expect. A wrapper is provided in lib/configWrapper.coffee for you to use
should you wish to use a simpler solution.
module.exports = ({config, logger}, next) ->
# config is the old config which was being used
# before this module was loaded
# logger.log and logger.error should be used rather than
# console
next myConfigObjectA config value will be retrieved from the config object the callback is called with like this:
config.get('some.config').get()
config.get('some.config').on 'change', ->
# The config changed!You are free to implement the on method as a dud if live reloading doesn't
make sense using your config system. Take a look at lib/configWrapper.coffee
for an example of how a basic object can be converted (and feel free to use it).
App modules get loaded once, and can optionally provide a function to be ran with each request.
Simple app modules are a good place to put any server config, initialization code, etc.
We use app modules to make little tweaks to how express works and enable monitoring.
App modules are called at initialize-time with a hash including a reference to the express app:
module.exports = ({app, logger, config}, next) ->If your app module calls the callback with a function, that function will be executed on all requests to
/v1/send, which is the default endpoint.
If the callback is called with a hash, it is expected to be a mapping between endpoints and handler functions.
module.exports = ({app, logger, config}, next) ->
next
send: (req, res, _next) ->
# Standard express request handling stuff in here
someOtherEndpoint: (req, res, _next) ->
# Will get requests which are sent to /v1/someOtherEndpointThese functions work like middleware, they are called sequentially. You can use them to implement things like auth if you need it.
It's not a standard type of module (the core of Bucky has no idea about it), but the default collectors app module looks to a fourth type of module to know where to send data.
Statsd and OpenTSDB collectors are included.
Collectors should export a function which is called on initialize, and call the callback with a hash mapping endpoints to handlers.
module.exports = ({app, logger, config}, next) ->
next
send: (data) ->
# This collector will receive any requests to /v1/send (the default endpoint)
logger.log "We got some data!"If you are interested in writing new clients, the format of metric data is the same as is used by statsd:
<metric name>:<metric value>|<unit>[@<sample rate>]
For example:
my.awesome.metric:35|ms
some.other.metric:3|[email protected]
All requests are sent with content-type text/plain.
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