apiVersion: influxdata.com/v2alpha1
kind: Label
metadata:
name: fervent-dijkstra-184001
spec:
color: '#0b3a8d'
name: ADS-B
---
apiVersion: influxdata.com/v2alpha1
kind: Bucket
metadata:
name: endangered-haslett-184005
spec:
associations:
- kind: Label
name: fervent-dijkstra-184001
name: ads-b
---
apiVersion: influxdata.com/v2alpha1
kind: Dashboard
metadata:
name: loving-proskuriakova-984001
spec:
associations:
- kind: Label
name: fervent-dijkstra-184001
charts:
- colors:
- hex: '#00C9FF'
id: base
name: laser
type: text
decimalPlaces: 0
height: 2
kind: Single_Stat
name: Recent Aircraft Total
queries:
- query: |-
from(bucket: v.bucket)
|> range(start: v.timeRangeStart, stop: v.timeRangeStop)
|> filter(fn: (r) => r["_measurement"] == "dump1090_recent_aircraft_observed")
|> aggregateWindow(every: v.windowPeriod, fn: last, createEmpty: false)
|> yield(name: "last")
staticLegend: {}
width: 2
- axes:
- base: "10"
name: x
scale: linear
- base: "10"
label: '# of Aircraft'
name: y
scale: linear
colors:
- hex: '#31C0F6'
id: 5ce5deb4-b018-4aba-b270-b2cf3f3648fd
name: Nineteen Eighty Four
type: scale
- hex: '#A500A5'
id: 9bf389b2-87cd-4489-9580-d8d9d1bf64ff
name: Nineteen Eighty Four
type: scale
- hex: '#FF7E27'
id: 402d2f6f-6d2c-4cec-ab68-6255f3aba755
name: Nineteen Eighty Four
type: scale
geom: line
height: 6
hoverDimension: auto
kind: Xy
name: Aircraft
position: overlaid
queries:
- query: |-
from(bucket: v.bucket)
|> range(start: v.timeRangeStart, stop: v.timeRangeStop)
|> filter(fn: (r) => r["_measurement"] == "dump1090_recent_aircraft_observed" or r["_measurement"] == "dump1090_recent_aircraft_with_multilateration" or r["_measurement"] == "dump1090_recent_aircraft_with_position")
|> aggregateWindow(every: v.windowPeriod, fn: last, createEmpty: false)
|> yield(name: "last")
staticLegend: {}
width: 10
xCol: _time
yCol: _value
yPos: 2
- axes:
- base: "10"
name: x
scale: linear
- label: Distance
name: y
scale: linear
suffix: m
colors:
- hex: '#31C0F6'
id: 5ce5deb4-b018-4aba-b270-b2cf3f3648fd
name: Nineteen Eighty Four
type: scale
- hex: '#A500A5'
id: 9bf389b2-87cd-4489-9580-d8d9d1bf64ff
name: Nineteen Eighty Four
type: scale
- hex: '#FF7E27'
id: 402d2f6f-6d2c-4cec-ab68-6255f3aba755
name: Nineteen Eighty Four
type: scale
geom: line
height: 5
kind: Xy
name: Distance from receiver
position: overlaid
queries:
- query: |-
from(bucket: v.bucket)
|> range(start: v.timeRangeStart, stop: v.timeRangeStop)
|> filter(fn: (r) => r["_measurement"] == "dump1090_recent_aircraft_max_range")
|> aggregateWindow(every: v.windowPeriod, fn: mean, createEmpty: false)
|> yield(name: "mean")
staticLegend: {}
width: 10
xCol: _time
yCol: _value
yPos: 8
- colors:
- hex: '#00C9FF'
id: base
name: laser
type: text
decimalPlaces: 0
height: 2
kind: Single_Stat
name: Aircraft with Position
queries:
- query: |-
from(bucket: v.bucket)
|> range(start: v.timeRangeStart, stop: v.timeRangeStop)
|> filter(fn: (r) => r["_measurement"] == "dump1090_recent_aircraft_with_position")
|> aggregateWindow(every: v.windowPeriod, fn: last, createEmpty: false)
|> yield(name: "last")
staticLegend: {}
width: 2
xPos: 2
- colors:
- hex: '#00C9FF'
id: base
name: laser
type: text
decimalPlaces: 0
height: 2
kind: Single_Stat
name: Max Range
queries:
- query: |-
from(bucket: v.bucket)
|> range(start: v.timeRangeStart, stop: v.timeRangeStop)
|> filter(fn: (r) => r["_measurement"] == "dump1090_recent_aircraft_max_range")
|> max()
|> map(fn: (r) => ({
r with
_value: r._value / 1000.0
})
)
staticLegend: {}
suffix: ' km'
width: 2
xPos: 4
- colors:
- hex: '#00C9FF'
id: base
name: laser
type: text
decimalPlaces: 0
height: 2
kind: Single_Stat
name: Messages per Second
queries:
- query: |-
import "experimental/aggregate"
from(bucket: v.bucket)
|> range(start: -1m)
|> filter(fn: (r) => r["_measurement"] == "dump1090_messages_total")
|> aggregate.rate(every: 5s, unit: 1s)
staticLegend: {}
width: 2
xPos: 6
- axes:
- base: "10"
name: x
scale: linear
- base: "10"
name: y
scale: linear
colors:
- hex: '#00C9FF'
id: base
name: laser
type: text
decimalPlaces: 1
height: 2
kind: Single_Stat_Plus_Line
name: Signal Mean
position: overlaid
queries:
- query: |-
from(bucket: v.bucket)
|> range(start: v.timeRangeStart, stop: v.timeRangeStop)
|> filter(fn: (r) => r["_measurement"] == "dump1090_stats_local_signal_strength_dbFS")
|> aggregateWindow(every: v.windowPeriod, fn: mean, createEmpty: false)
|> yield(name: "mean")
staticLegend: {}
width: 2
xCol: _time
xPos: 8
yCol: _value
- height: 13
kind: Markdown
name: Name this Cell
note: |-
#### Recent Aircraft Total
The most recent number of aircraft reported
#### Aircraft with Position
The number of recently reported aircraft with position data
#### Max Range
The farthest report received
#### Messages per Second
The current count of messages per second received and decoded
#### Signal Mean
Mean signal expressed in [dBFS](https://en.wikipedia.org/wiki/dBFS)
#### Aircraft
* Observed aircraft
* Observed aircraft with position data
* Observed aircraft with [MLAT](http://multilateration.com/ads-b.html)
#### Distance from Receiver
Aircraft distance from receiver over time
staticLegend: {}
width: 2
xPos: 10
description: Metrics gathered from dump1090exporter to visualize your ADS-B flight
tracking station.
name: ADS-B Flight Tracker
---
apiVersion: influxdata.com/v2alpha1
kind: Telegraf
metadata:
name: sloppy-sinoussi-d84001
spec:
associations:
- kind: Label
name: fervent-dijkstra-184001
config: |-
# Configuration for telegraf agent
[agent]
## Default data collection interval for all inputs
interval = "10s"
## Rounds collection interval to 'interval'
## ie, if interval="10s" then always collect on :00, :10, :20, etc.
round_interval = true
## Telegraf will send metrics to outputs in batches of at most
## metric_batch_size metrics.
## This controls the size of writes that Telegraf sends to output plugins.
metric_batch_size = 1000
## For failed writes, telegraf will cache metric_buffer_limit metrics for each
## output, and will flush this buffer on a successful write. Oldest metrics
## are dropped first when this buffer fills.
## This buffer only fills when writes fail to output plugin(s).
metric_buffer_limit = 10000
## Collection jitter is used to jitter the collection by a random amount.
## Each plugin will sleep for a random time within jitter before collecting.
## This can be used to avoid many plugins querying things like sysfs at the
## same time, which can have a measurable effect on the system.
collection_jitter = "0s"
## Default flushing interval for all outputs. Maximum flush_interval will be
## flush_interval + flush_jitter
flush_interval = "10s"
## Jitter the flush interval by a random amount. This is primarily to avoid
## large write spikes for users running a large number of telegraf instances.
## ie, a jitter of 5s and interval 10s means flushes will happen every 10-15s
flush_jitter = "0s"
## By default or when set to "0s", precision will be set to the same
## timestamp order as the collection interval, with the maximum being 1s.
## ie, when interval = "10s", precision will be "1s"
## when interval = "250ms", precision will be "1ms"
## Precision will NOT be used for service inputs. It is up to each individual
## service input to set the timestamp at the appropriate precision.
## Valid time units are "ns", "us" (or "µs"), "ms", "s".
precision = ""
## Logging configuration:
## Run telegraf with debug log messages.
debug = false
## Run telegraf in quiet mode (error log messages only).
quiet = false
## Specify the log file name. The empty string means to log to stderr.
logfile = ""
## Override default hostname, if empty use os.Hostname()
hostname = ""
## If set to true, do no set the "host" tag in the telegraf agent.
omit_hostname = false
[[outputs.influxdb_v2]]
urls = ["$INFLUX_HOST"]
token = "$INFLUX_TOKEN"
organization = "$INFLUX_ORG"
bucket = "$INFLUX_BUCKET"
[[inputs.prometheus]]
urls = ["http://localhost:9105/metrics"]
description: Collect ADSB metrics from dump1090 Prometheus export
name: ADS-B