0.2.4
Bucky is a client and server for sending performance data from the client into statsd+graphite, OpenTSDB, or any other stats aggregator of your choice.
It can automatically measure how long your pages take to load, how long AJAX requests take and how long various functions take to run. Most importantly, it's taking the measurements on actual page loads, so the data has the potential to be much more valuable than in vitro measurements.
If you already use statsd or OpenTSDB, you can get started in just a few minutes. If you're not collecting stats, you should start! What gets measured gets managed.
You can play with Bucky just using the client, but if you'd like to start collecting data, see the Server Instructions.
Include bucky.js on your page, the only required config can be done right in the script tag:
<script src="bucky.js" data-bucky-host="/bucky" data-bucky-page data-bucky-requests></script>
That config will automatically log the performance of your page and all the requests you make to a server running at /bucky. It will automatically decide the right key name based on the url of the page. If you'd like, you can also specify it manually:
<script src="bucky.js" data-bucky-host="/bucky" data-bucky-page="index" data-bucky-requests="index"></script>
The Bucky
object will be available globally, but there is nothing you need to call for basic usage.
Bucky can also be loaded with AMD or Browserify (see the methods below).
npm install bucky
bucky = require('bucky')
Before sending any data, call setOptions
if you're not using the data- attribute based configuration:
Bucky.setOptions({
host: 'http://myweb.site:9999/bucky'
});
Some options you might be interested in:
host
: Where we can reach your Bucky server, including the
APP_ROOT.
The Bucky server has a very liberal CORS config, so we should be able to connect to it even if it's on a different domain, but hosting it on the same domain and port will save you some preflight requests.
active
: Should Bucky actually send data? Use this to disable Bucky during local dev for example.
sample
: What fraction of clients should actually send data? Use to subsample your clients if you have
too much data coming in.Take a look at the source for a full list of options.
Modern browsers log a bunch of page performance data, bucky includes a method for writing all of this in one go. It won't do anything on browsers which don't support the performance.timing api. Call it whenever, it will bind an event if the data isn't ready yet.
Bucky.sendPagePerformance('where.the.data.should.go')
Setting data-bucky-page
triggers this automatically.
The two most relevant stats provided are responseEnd
which is the amount of time it took for the
original page to be loaded and domInteractive
which is the amount of time before the page has
finished loaded and can be interacted with by the user.
As a reminder: this data is browser specific, so it will likely skew lower than what users on old browsers see.
If you're using Backbone, it might be a good idea to send your data based on route:
Backbone.history.on 'route', (router, route) ->
# Will only send on the initial page load:
Bucky.sendPagePerformance("some.location.page.#{ route }")
The data collected will look something like this:
pages.contactDetail.timing.connectEnd: "172.000|ms"
pages.contactDetail.timing.connectStart: "106.000|ms"
pages.contactDetail.timing.domComplete: "1029.000|ms"
pages.contactDetail.timing.domContentLoadedEventEnd: "1019.000|ms"
pages.contactDetail.timing.domContentLoadedEventStart: "980.000|ms"
pages.contactDetail.timing.domInteractive: "980.000|ms"
pages.contactDetail.timing.domLoading: "254.000|ms"
pages.contactDetail.timing.domainLookupEnd: "106.000|ms"
pages.contactDetail.timing.domainLookupStart: "106.000|ms"
pages.contactDetail.timing.fetchStart: "103.000|ms"
pages.contactDetail.timing.loadEventEnd: "1030.000|ms"
pages.contactDetail.timing.loadEventStart: "1029.000|ms"
pages.contactDetail.timing.navigationStart: "0.000|ms"
pages.contactDetail.timing.requestStart: "173.000|ms"
pages.contactDetail.timing.responseEnd: "243.000|ms"
pages.contactDetail.timing.responseStart: "235.000|ms"
pages.contactDetail.timing.secureConnectionStart: "106.000|ms"
A description of what each datapoint represents is included in the spec.
Bucky can automatically log all ajax requests made by hooking into XMLHttpRequest and doing some transformations on the url to try and create a graphite key from it. Enable it as early in your app's load as is possible:
Bucky.requests.monitor('my.project.requests')
Setting data-bucky-requests
calls this automatically.
The data collected will look something like this for a GET request to
api.hubapi.com/automation/v2/workflows
:
contacts.web.prod.requests.api.hubapi.automation.v2.workflows.get: "656.794|ms"
contacts.web.prod.requests.api.hubapi.automation.v2.workflows.get.2xx: "1|c"
contacts.web.prod.requests.api.hubapi.automation.v2.workflows.get.200: "1|c"
contacts.web.prod.requests.api.hubapi.automation.v2.workflows.get.headers: "436.737|ms"
contacts.web.prod.requests.api.hubapi.automation.v2.workflows.get.receiving: "0.182|ms"
contacts.web.prod.requests.api.hubapi.automation.v2.workflows.get.sending: "0.059|ms"
contacts.web.prod.requests.api.hubapi.automation.v2.workflows.get.waiting: "206.035|ms"
You can build a client which will prefix all of your datapoints by calling bucky as a function:
myBucky = Bucky('awesome.app.view')
# You can then use all of the normal methods:
myBucky.send('data.point', 5)
You can repeatedly call clients to add more prefixes:
contactsBucky = bucky('contacts')
cwBucky = contactsBucky('web')
cwBucky.send('x', 1) # Data goes in contacts.web.x
By default send
sends absolute values, this is rarely what you want when working from the client, incrementing
a counter is usually more helpful:
bucky.count('my.awesome.thing')
bucky.count('number.of.chips.eaten', 5)
You can manually send ms durations using timer.send
:
bucky.timer.send('timed.thing', 55)
Bucky includes a method to time async functions:
bucky.timer.time 'my.awesome.function', (done) ->
asyncThingy ->
done()
You can also manually start and stop your timer:
bucky.timer.start 'my.awesome.function'
asyncThingy ->
bucky.timer.stop 'my.awesome.function'
You can time synchronous functions as well:
bucky.timer.timeSync 'my.awesome.function', ->
Math.sqrt(100)
The time
and timeSync
functions also accept a context and arguments to pass to the
called function:
bucky.timer.timeSync 'my.render.function', @render, @, arg1, arg2
You can wrap existing functions using wrap
:
func = bucky.timer.wrap('func.time', func)
It also supports a special syntax for methods:
class SomeClass
render: bucky.timer.wrap('render') ->
# Normal render stuff
Note that this wrapping does not play nice with CoffeeScript super
calls.
Bucky also includes a function for measuring the time since the navigationStart event was fired (the beginning of the request):
bucky.timer.mark('my.thing.happened')
It acts like a timer where the start is always navigation start.
The stopwatch method allows you to begin a timer which can be stopped multiple times:
watch = bucky.stopwatch('some.prefix.if.you.want')
You can then call watch.mark('key')
to send the time since the stopwatch started, or
watch.split('key')
to send the time since the last split.
If you want to send absolute values (rare from the client), you can use send directly.
The one use we've had for this is sending +new Date
from every client to get an idea
of how skewed their clocks are.
Bucky.send 'my.awesome.datapoint', 2432.43434
You can find your stats in the stats
and stats.timing
folders in graphite, or as written in OpenTSDB.
Bucky will send your data in bulk from the client either five seconds after the last datapoint is added, or thirty seconds after the last send, whichever comes first. If you log multiple datapoints within this send frequency, the points will be averaged (and the appropriate frequency information will be sent to statsd) (with the exception of counters, they are incremented). This means that the max and min numbers you get from statsd actually represent the max and min 5-30 second bucket. Note that this is per-client, not for the entire bucky process (it's generally only important on the server where you might be pushing out many points with the same key).
The Bucky object provides a couple extra properties you can access:
Bucky.history
: The history of all datapoints ever sent.Bucky.active
: Is Bucky sending data? This can change if you change the active
or sample
settings.Bucky.flush()
: Send the Bucky queue immediatelyBucky.timer.now()
: A clock based on the most precise time available (not guarenteed to be from the epoch)request.monitor
attempts to automatically transform your urls into keys. It does a bunch of transformations
with the goal of removing anything which will vary per-request, so you end up with stats per-endpoint. These
tranformations include:
If you find these tranformations too invasive, or not invasive enough, you can modify them.
// You can diable tranforms with `.disable`
Bucky.requests.transforms.disable('guid');
// You can enable transforms with `.enable`
Bucky.requests.tranforms.enable('guid');
// `.enable` can also be used to add a new tranform:
Bucky.requests.transforms.enable('my-ids', /[0-9]{4}-[0-9]{12}/g)
// The third argument defines what the match is replaced with (rather than just eliminating it):
Bucky.requests.transforms.enable('campaign', /campaigns\/\w{15}/ig, '/campaigns')
// You can also just provide a function which takes in the url, and returns it modified:
Bucky.request.transforms.enable('soup', function(url){ return url.split('').reverse().join(''); })
Enabled tests will be added to the beginning of the enabled
list, meaning they will be executed before
any other tranform. Edit the Bucky.requests.tranforms.enabled
array if you need more specific control.
The order of the transforms is very important. If you, for example, were to run the id
transform before
the guid
one, the guid
transform wouldn't match any guid which began with a number (as the number would
have already been stripped out, making the guid the wrong length).
When you first enable request monitoring, it's a good idea to keep an eye on the Bucky logs to get an idea of what sort of data points are being created.
This project pushes data to the Bucky Server.