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algorithmia.yml
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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"