RandOME

A CLI tool to generate a (pseudo)random stream of open metrics data for debugging prometheus based TSDBs and tools that depend on it. This is very similar to Avalanche. While avalanche focuses more on the "load testing" aspect of things, randOME focuses more on the actual data generated.

By controlling the shape of the data, you can test/debug/benchmark specific scenarios related to alerting, visualization, storage, and performance. With randOME, you can create more targeted and meaningful tests that enable you to optimize your systems more effectively.

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Configuration

This tool can be configured with a simple YAML file. Here's a sample config:

metrics:
  - name: metric_1
    value_min: 0
    value_max: 100
    labels:
      instance: [localhost:8080]
      cluster: [dev, prod, staging, test, qa]

  - name: metric_2
    max_cardinality: 10
    labels:
      method: [GET, POST, PUT, DELETE]
      status: [200, 400, 404, 500]

Attributes

Field	Type	Description
Name	string	The name of the metric.
ValueMin	number	The minimum value that the metric can have.
ValueMax	number	The maximum value that the metric can have.
Value	number	The static value of the metric. This field is optional.
Labels	map[string][]string	The labels associated with the metric, as a map of string to string slices (refer to the above examples for the exact format).
MaxCardinality	number	The maximum number of unique label value combinations that can be associated with the metric. This field is optional.

Easiest way to run

Emit default metrics

$ docker run -d -p 9090:9090 arjunmahishi/randome

Emit custom metrics

$ cat > sample.yaml <<EOF
metrics:
  - name: metric_1
    value_min: 0
    value_max: 100
    labels:
      instance: [localhost:8080]
      cluster: [dev, prod, staging, test, qa]

  - name: metric_2
    max_cardinality: 10
    labels:
      method: [GET, POST, PUT, DELETE]
      status: [200, 400, 404, 500]
EOF

$ docker run -d -p 9090:9090 -v $(pwd)/sample.yaml:/app/sample.yaml  arjunmahishi/randome

Remote write default metrics

$ docker run -d -e REMOTE_WRITE_ADDR='http://<prometheus-compatible-host>/api/v1/write' arjunmahishi/randome

Remote write custom metrics

$ cat > sample.yaml <<EOF
metrics:
  - name: metric_1
    value_min: 0
    value_max: 100
    labels:
      instance: [localhost:8080]
      cluster: [dev, prod, staging, test, qa]

  - name: metric_2
    max_cardinality: 10
    labels:
      method: [GET, POST, PUT, DELETE]
      status: [200, 400, 404, 500]
EOF

$ docker run -d -e REMOTE_WRITE_ADDR='http://<prometheus-compatible-host>/api/v1/write' -v $(pwd)/sample.yaml:/app/sample.yaml arjunmahishi/randome

Building locally

# for your OS
make build

# for a specific OS (check the makefile to see if the command is available for the OS you're looking for)
make build_<platform>

# both commands will create an executable binary in ./bin

Running the binary directly

$ randOME --help
usage: randOME [<flags>] <command> [<args> ...]

Flags:
      --help           Show context-sensitive help (also try --help-long and --help-man).
  -f, --frequency=4s   Frequency of data points
  -c, --config=CONFIG  path to the config file
      --version        Show application version.

Commands:
  help [<command>...]
    Show help.

  print
    print the data to stdout

  remote-write --addr=ADDR
    Remote write to a Prometheus-compatible TSDB

  emit [<flags>]
    Emit metrics over HTTP on a given port (localhost:<port>/metrics)

Print metrics to STDOUT

randOME print -f 5s

Emit metrics over HTTP

randOME emit -f 5s

Remote write to a prometheus compatible storage

randOME remote-write -f 5s --addr http://localhost:8428/api/v1/write

Defining custom metrics

$ cat sample.yaml
metrics:
  - name: cpu_usage
    value_min: 0
    value_max: 100
    labels:
      instance: [localhost:8080]
      cluster: [dev, prod, staging, test, qa]

  - name: requests_total
    max_cardinality: 10
    labels:
      method: [GET, POST, PUT, DELETE]
      status: [200, 400, 404, 500]

$ randOME print -c sample.yaml -f 5s
requests_total{status='200',method='GET'} 2
requests_total{status='400',method='GET'} 7
requests_total{status='404',method='GET'} 6
requests_total{status='500',method='GET'} 0
requests_total{status='200',method='POST'} 5
requests_total{status='400',method='POST'} 3
requests_total{method='POST',status='404'} 4
requests_total{method='POST',status='500'} 3
requests_total{status='200',method='PUT'} 9
requests_total{status='400',method='PUT'} 6
cpu_usage{instance='localhost:8080',cluster='dev'} 21
cpu_usage{instance='localhost:8080',cluster='prod'} 52
cpu_usage{instance='localhost:8080',cluster='staging'} 36
cpu_usage{instance='localhost:8080',cluster='test'} 5
cpu_usage{instance='localhost:8080',cluster='qa'} 62
cpu_usage{cluster='dev',instance='localhost:8080'} 94
cpu_usage{instance='localhost:8080',cluster='prod'} 93
cpu_usage{cluster='staging',instance='localhost:8080'} 80
cpu_usage{instance='localhost:8080',cluster='test'} 67
cpu_usage{cluster='qa',instance='localhost:8080'} 59