apiVersion: influxdata.com/v2alpha1
kind: Bucket
metadata:
    name: unruffled-almeida-c0c001
spec:
    name: insights
---
apiVersion: influxdata.com/v2alpha1
kind: Dashboard
metadata:
    name: mystifying-booth-40c001
spec:
    charts:
      - axes:
          - base: "10"
            name: x
            scale: linear
          - base: "2"
            name: y
            scale: linear
        colors:
          - hex: '#00C9FF'
            name: laser
            type: text
          - hex: '#DC4E58'
            name: fire
            type: text
            value: 0.7
        decimalPlaces: 2
        height: 4
        kind: Single_Stat_Plus_Line
        name: Risk Score
        position: overlaid
        queries:
          - query: |-
                from(bucket: "insights")
                  |> range(start: v.timeRangeStart, stop: v.timeRangeStop)
                  |> filter(fn: (r) => r["_measurement"] == "kafka_consumer")
                  |> filter(fn: (r) => r["_field"] == "risk_score")
                  |> group()
                  |> aggregateWindow(every: v.windowPeriod, fn: mean, createEmpty: false)
                  |> yield(name: "mean")
        width: 4
        xCol: _time
        yCol: _value
      - colors:
          - hex: '#32B08C'
            name: viridian
            type: min
          - hex: '#DC4E58'
            name: fire
            type: max
            value: 1
        decimalPlaces: 2
        height: 4
        kind: Gauge
        name: Risk Score
        queries:
          - query: |-
                from(bucket: "insights")
                  |> range(start: v.timeRangeStart, stop: v.timeRangeStop)
                  |> filter(fn: (r) => r["_measurement"] == "kafka_consumer")
                  |> filter(fn: (r) => r["_field"] == "risk_score")
                  |> group()
                  |> aggregateWindow(every: v.windowPeriod, fn: mean, createEmpty: false)
                  |> yield(name: "mean")
        width: 4
        yPos: 4
      - axes:
          - base: "10"
            name: x
            scale: linear
          - base: "10"
            name: y
            scale: linear
        colors:
          - hex: '#00C9FF'
            name: laser
            type: text
          - hex: '#DC4E58'
            name: fire
            type: text
            value: 0.8
        decimalPlaces: 2
        height: 4
        kind: Single_Stat_Plus_Line
        name: Approvals
        position: overlaid
        queries:
          - query: |-
                from(bucket: "insights")
                  |> range(start: v.timeRangeStart, stop: v.timeRangeStop)
                  |> filter(fn: (r) => r["_measurement"] == "kafka_consumer")
                  |> filter(fn: (r) => r["_field"] == "approved")
                  |> group()
                  |> aggregateWindow(every: v.windowPeriod, fn: mean, createEmpty: false)
                  |> yield(name: "mean")
        width: 4
        xCol: _time
        xPos: 4
        yCol: _value
      - axes:
          - name: x
          - domain:
              - 0
              - 1
            name: y
        binSize: 20
        colors:
          - hex: '#000004'
          - hex: '#110a30'
          - hex: '#320a5e'
          - hex: '#57106e'
          - hex: '#781c6d'
          - hex: '#9a2865'
          - hex: '#bc3754'
          - hex: '#d84c3e'
          - hex: '#ed6925'
          - hex: '#f98e09'
          - hex: '#fbb61a'
          - hex: '#f4df53'
        height: 4
        kind: Heatmap
        name: Approved
        queries:
          - query: |-
                from(bucket: "insights")
                  |> range(start: v.timeRangeStart, stop: v.timeRangeStop)
                  |> filter(fn: (r) => r["_measurement"] == "kafka_consumer")
                  |> filter(fn: (r) => r["_field"] == "approved")
                  |> group()
                  |> aggregateWindow(every: v.windowPeriod, fn: mean, createEmpty: false)
                  |> yield(name: "mean")
        width: 4
        xCol: _time
        xPos: 4
        yCol: _value
        yPos: 4
      - axes:
          - base: "10"
            name: x
            scale: linear
          - base: "10"
            name: y
            scale: linear
        colors:
          - hex: '#00C9FF'
            name: laser
            type: text
        decimalPlaces: 0
        height: 4
        kind: Single_Stat_Plus_Line
        name: Algorithm Duration
        position: overlaid
        queries:
          - query: |-
                from(bucket: "insights")
                  |> range(start: v.timeRangeStart, stop: v.timeRangeStop)
                  |> filter(fn: (r) => r["_measurement"] == "kafka_consumer")
                  |> filter(fn: (r) => r["_field"] == "duration_milliseconds")
                  |> group()
                  |> aggregateWindow(every: v.windowPeriod, fn: mean, createEmpty: false)
                  |> yield(name: "mean")
        suffix: ' ms'
        width: 4
        xCol: _time
        xPos: 8
        yCol: _value
      - colors:
          - hex: '#00C9FF'
            name: laser
            type: min
          - hex: '#9394FF'
            name: comet
            type: max
            value: 100
        decimalPlaces: 0
        height: 4
        kind: Gauge
        name: Algorithm Duration
        queries:
          - query: |-
                from(bucket: "insights")
                  |> range(start: v.timeRangeStart, stop: v.timeRangeStop)
                  |> filter(fn: (r) => r["_measurement"] == "kafka_consumer")
                  |> filter(fn: (r) => r["_field"] == "duration_milliseconds")
                  |> group()
                  |> aggregateWindow(every: v.windowPeriod, fn: mean, createEmpty: false)
                  |> yield(name: "mean")
        suffix: ' ms'
        width: 4
        xPos: 8
        yPos: 4
    description: Monitor machine learning model performance metrics
    name: Algorithmia - ML Model Performance Metrics
---
apiVersion: influxdata.com/v2alpha1
kind: Telegraf
metadata:
    name: algorithmia-telegraf
spec:
    name: Algorithmia
    config: |
        [agent]
          interval = "10s"
          round_interval = true
          metric_batch_size = 1000
          metric_buffer_limit = 10000
          collection_jitter = "0s"
          flush_interval = "10s"
          flush_jitter = "0s"
          precision = ""
          hostname = ""
          omit_hostname = false

        ###############################################################################
        #                            OUTPUT PLUGINS                                   #
        ###############################################################################

        [[outputs.influxdb_v2]]
          urls = ["$INFLUX_HOST"]
          token = "$INFLUX_TOKEN"
          organization = "$INFLUX_ORG"
          bucket = "insights"

        ###############################################################################
        #                            PROCESSOR PLUGINS                                #
        ###############################################################################


        ###############################################################################
        #                            AGGREGATOR PLUGINS                               #
        ###############################################################################


        ###############################################################################
        #                            INPUT PLUGINS                                    #
        ###############################################################################

        [[inputs.kafka_consumer]]
          brokers = ["$KAFKA_BROKER"]
          topics = ["$KAFKA_TOPIC"]
          data_format = "json"
          tag_keys = [
            "algorithm_name",
            "algorithm_owner",
            "algorithm_version"
          ]
          json_string_fields = [
            "session_id",
            "request_id"
          ]
          name_override = "algorithmia"