05891fd731
According to the documentation:
// WriteHeader sends an HTTP response header with status code.
// If WriteHeader is not called explicitly, the first call to Write
// will trigger an implicit WriteHeader(http.StatusOK).
// Thus explicit calls to WriteHeader are mainly used to
// send error codes.
and
// Header returns the header map that will be sent by WriteHeader.
// Changing the header after a call to WriteHeader (or Write) has
// no effect.
so calling `w.Header().Set(contentType, jsonContentType)` after calling
`w.WriteHeader` does not set the content type -- the call can be removed
though as it always set `http.StatusOK` which will be done anyways
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|---|---|---|
| examples | ||
| maths | ||
| metrics | ||
| utility | ||
| .gitignore | ||
| .travis.yml | ||
| LICENSE | ||
| README.md | ||
| TODO | ||
| documentation.go | ||
| registry.go | ||
README.md
Overview
This Go package is an extraction of a piece of instrumentation code I whipped-up for a personal project that a friend of mine and I are working on. We were in need for some rudimentary statistics to observe behaviors of the server's various components, so this was written.
The code here is not a verbatim copy thereof but rather a thoughtful re-implementation should other folks need to consume and analyze such telemetry.
N.B. --- I have spent a bit of time working through the model in my head and probably haven't elucidated my ideas as clearly as I need to. If you examine examples/{simple,uniform_random}/main.go and registry.go, you'll find several examples of what types of potential instrumentation use cases this package addresses. There are probably numerous Go language idiomatic changes that need to be made, but this task has been deferred for now.
Continuous Integration
Documentation
Please read the generated documentation for the project's documentation from source code.
Basic Overview
Metrics
A metric is a measurement mechanism.
Gauge
A Gauge is a metric that exposes merely an instantaneous value or some snapshot thereof.
Histogram
A Histogram is a metric that captures events or samples into buckets. It exposes its values via percentile estimations.
Buckets
A Bucket is a generic container that collects samples and their values. It prescribes no behavior on its own aside from merely accepting a value, leaving it up to the concrete implementation to what to do with the injected values.
Accumulating Bucket
An Accumulating Bucket is a bucket that appends the new sample to a timestamped priority queue such that the eldest values are evicted according to a given policy.
Eviction Policies
Once an Accumulating Bucket reaches capacity, its eviction policy is invoked. This reaps the oldest N objects subject to certain behavior.
Remove Oldest
This merely removes the oldest N items without performing some aggregation replacement operation on them.
Aggregate Oldest
This removes the oldest N items while performing some summary aggregation operation thereupon, which is then appended to the list in the former values' place.
Tallying Bucket
A Tallying Bucket differs from an Accumulating Bucket in that it never stores any of the values emitted into it but rather exposes a simplied summary representation thereof. For instance, if a values therein is requested, it may situationally emit a minimum, maximum, an average, or any other reduction mechanism requested.
Testing
This package employs gocheck for testing. Please ensure that all tests pass by running the following from the project root:
$ go test ./...