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Description

This gem captures and aggregates Rails application metrics such as: duration, views, db, queries, status and stores them for a variable timeframe.

The implementation is based on Redis commands such as: get, mget, setex which are extremely fast.

It may be useful if you want a simple but effective metrics aggregation tool for your Rails app.

Monthly Downloads: 746
Programming language: Ruby
License: MIT License
Latest version: v3.0.2

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README

ezmetrics

Gem Version

Simple, lightweight and fast metrics aggregation for Rails.

Installation

gem 'ezmetrics'

Available metrics

Type Aggregate functions
duration avg, max, percentile
views avg, max, percentile
db avg, max, percentile
queries avg, max, percentile
requests all, 2xx, 3xx, 4xx, 5xx

Usage

Capture metrics

rails generate ezmetrics:initializer

Display metrics

1. Dashboard

# add the following line to 'config/routes.rb'

mount Dashboard::Ezmetrics, at: "/dashboard", as: "dashboard"

Dashboard

2. Directly

As simple as:

Ezmetrics::Storage.new.show

This will return a hash with the following structure:

{
  duration: {
    avg: 5569,
    max: 9675
  },
  views: {
    avg: 12,
    max: 240
  },
  db: {
    avg: 155,
    max: 4382
  },
  queries: {
    avg: 26,
    max: 76
  },
  requests: {
    all: 2000,
    grouped: {
      "2xx" => 1900,
      "3xx" => 15,
      "4xx" => 80,
      "5xx" => 5
    }
  }
}

If you prefer a single level object - you can change the default output structure by calling .flatten before .show

Ezmetrics::Storage.new(1.hour).flatten.show(db: :avg, duration: [:avg, :max])
{
  db_avg:       182,
  duration_avg: 205,
  duration_max: 5171
}

Same for partitioned aggregation

Ezmetrics::Storage.new(1.hour).partition_by(:minute).flatten.show(db: :avg, duration: [:avg, :max])
[
  {
    timestamp:    1575242880,
    db_avg:       387,
    duration_avg: 477,
    duration_max: 8566
  },
  {
    timestamp:    1575242940,
    db_avg:       123,
    duration_avg: 234,
    duration_max: 3675
  }
]

Aggregation

The aggregation can be easily configured by specifying aggregation options as in the following examples:

1. Single

Ezmetrics::Storage.new.show(duration: :max)
{
  duration: {
    max: 9675
  }
}

2. Multiple

Ezmetrics::Storage.new.show(queries: [:max, :avg])
{
  queries: {
    max: 76,
    avg: 26
  }
}

3. Requests

Ezmetrics::Storage.new.show(requests: true)
{
  requests: {
    all: 2000,
    grouped: {
      "2xx" => 1900,
      "3xx" => 15,
      "4xx" => 80,
      "5xx" => 5
    }
  }
}

4. Combined

Ezmetrics::Storage.new.show(views: :avg, :db: [:avg, :max], requests: true)
{
  views: {
    avg: 12
  },
  db: {
    avg: 155,
    max: 4382
  },
  requests: {
    all: 2000,
    grouped: {
      "2xx" => 1900,
      "3xx" => 15,
      "4xx" => 80,
      "5xx" => 5
    }
  }
}

5. Percentile

This feature is available since version 2.0.0.

By default percentile aggregation is turned off because it requires to store each value of all metrics.

To enable this feature - you need to set store_each_value: true when saving the metrics:

Ezmetrics::Storage.new.log(
  duration:         100.5,
  views:            40.7,
  db:               59.8,
  queries:          4,
  status:           200,
  store_each_value: true
)

The aggregation syntax has the following format metrics_type: :percentile_{number} where number is any integer in the 1..99 range.

Ezmetrics::Storage.new.show(db: [:avg, :percentile_90, :percentile_95], duration: :percentile_99)
{
  db: {
    avg: 155,
    percentile_90: 205,
    percentile_95: 215
  },
  duration: {
    percentile_99: 236
  }
}

6. Percentile distribution

If you want to visualize percentile distribution (from 1% to 99%):

Ezmetrics::Storage.new.show(duration: :percentile_distribution)
{
  duration: {
    percentile_distribution: {
      1: 12,
      2: 15,
      3: 19,
      #...
      97: 6540,
      98: 6682,
      99: 6730
    }
  }
}

Partitioning

If you want to visualize your metrics by using a line chart, you will need to use partitioning.

To aggregate metrics, partitioned by a unit of time you need to call .partition_by({time_unit}) before calling .show

# Aggregate metrics for last hour, partition by minute
Ezmetrics::Storage.new(1.hour).partition_by(:minute).show(duration: [:avg, :max], db: :avg)

This will return an array of objects with the following structure:

[
  {
    timestamp: # UNIX timestamp
    data:      # a hash with aggregated metrics
  }
]

like in the example below:

[
  {
    timestamp: 1575242880,
    data: {
      duration: {
        avg: 477,
        max: 8566
      },
      db: {
        avg: 387
      }
    }
  },
  {
    timestamp: 1575242940,
    data: {
      duration: {
        avg: 234,
        max: 3675
      },
      db: {
        avg: 123
      }
    }
  }
]

Available time units for partitioning: second, minute, hour, day. Default: minute.

Performance

The aggregation speed relies on the performance of Redis (data storage) and Oj (json serialization/parsing).

You can check the aggregation time (in seconds) by running:

# 1. Simple
Ezmetrics::Benchmark.new.measure_aggregation

# 2. Partitioned
Ezmetrics::Benchmark.new.measure_aggregation(:minute)

# 3. Percentile
Ezmetrics::Benchmark.new(true).measure_aggregation

# 4. Percentile (partitioned)
Ezmetrics::Benchmark.new(true).measure_aggregation(:minute)
Interval Simple aggregation Partitioned Percentile Percentile (partitioned)
1 minute 0.0 0.0 0.0 0.0
1 hour 0.02 0.02 0.14 0.16
12 hours 0.22 0.25 2.11 1.97
24 hours 0.61 0.78 5.85 5.85
48 hours 1.42 1.75 14.1 13.9

The benchmarks above were run on a 2017 Macbook Pro 2.9 GHz Intel Core i7 with 16 GB of RAM

[Changelog](CHANGELOG.md)

License

ezmetrics is released under the MIT License.


*Note that all licence references and agreements mentioned in the ezmetrics README section above are relevant to that project's source code only.