7999d24f81
this commit updates our monkit dependency to the v3 version where it outputs in an influx style. this makes discovery much easier as many tools are built to look at it this way. graphite and rothko will suffer some due to no longer being a tree based on dots. hopefully time will exist to update rothko to index based on the new metric format. it adds an influx output for the statreceiver so that we can write to influxdb v1 or v2 directly. Change-Id: Iae9f9494a6d29cfbd1f932a5e71a891b490415ff |
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|---|---|---|
| .. | ||
| luacfg | ||
| common.go | ||
| copy.go | ||
| db.go | ||
| downgrade.go | ||
| example.lua | ||
| file.go | ||
| filter.go | ||
| graphite.go | ||
| influx.go | ||
| main.go | ||
| parser.go | ||
| print.go | ||
| README.md | ||
| sanitizer.go | ||
| schema.sql | ||
| udp.go | ||
| version.go | ||
statreceiver
This package implements a Lua-scriptable pipeline processor for zeebo/admission telemetry packets (like monkit or something).
There are a number of types of objects involved in making this work:
- Sources - A source is a source of packets. Each packet is a byte slice that, when parsed, consists of application and instance identification information (such as the application name and perhaps the MAC address or some other id of the computer running the application), and a list of named floating point values. There are currently two types of sources, a UDP source and a file source. A UDP source appends the current time as the timestamp to all packets, whereas a file source should have a prior timestamp to attach to each packet.
- Packet Destinations - A packet destination is something that can handle a packet with a timestamp. This is either a packet parser, a UDP packet destination for forwarding to another process, or a file destination that will serialize all packets and timestamps for later replay.
- Metric Destinations - Once a packet has been parsed, the contained metrics can get sent to a metric destination, such as a time series database, a relational database, stdout, a metric filterer, etc.
Please see example.lua for a good example of using this pipeline.
Setup
If you use a relational database metric destination, make sure to instantiate the schema provided in schema.sql first.