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InfluxDB 2.0 and #fluxlang Paul Dix paul@influxdata.com @pauldix

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an open source time series database

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What is time series data?

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Stock trades and quotes

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Metrics

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Analytics

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Events

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Sensor data

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Two kinds of time series data…

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Regular time series t0 t1 t2 t3 t4 t6 t7 Samples at regular intervals

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Irregular time series t0 t1 t2 t3 t4 t6 t7 Events whenever they come in

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Data that you ask questions about over time

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Solve common problems

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data collector

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processing, ETL, monitoring, alerting

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UI, visualization, management

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TICK for time series data

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Common Schema

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Line Protocol cpu,host=serverA,num=1,region=west idle=1.667,system=2342.2 1492214400000000000

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Line Protocol Measurement cpu,host=serverA,num=1,region=west idle=1.667,system=2342.2 1492214400000000000

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Line Protocol cpu,host=serverA,num=1,region=west idle=1.667,system=2342.2 1492214400000000000 Tags

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Line Protocol cpu,host=serverA,num=1,region=west idle=1.667,system=2342.2 1492214400000000000 Fields

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float64, int64, bool, string

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Line Protocol cpu,host=serverA,num=1,region=west idle=1.667,system=2342.2 1492214400000000000 nanosecond epoch

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Query Language

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SQL-ish select percentile(90, value) from cpu where time > now() - 1d group by time(10m)

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No Common API

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Different Languages for Query & Monitoring

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2.0

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• MIT Licensed • TSDB (write, query) • UI & Visualizations, Dashboards • Pull Metrics (Prometheus & OpenMetrics) • Tasks (background processing, ETL, monitoring/alerting)

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> DB

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Officially Supported Client Libraries Go, Node.js, Ruby, Python, PHP, Java, C#, C, Kotlin

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Visualization Libraries

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Data Model • Organization • Dashboards • Tasks • Buckets • Scrapers & Telegraf configs • Labels • Users

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• Query planner • Query optimizer • Turing complete language, VM, and query engine • Multi-language support in Engine • Multi-data source support • InfluxDB, CLI, REPL, Go library

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Flux Language Elements

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// get all data from the telegraf db from(bucket:”telegraf/autogen”) // filter that by the last hour |> range(start:-1h) // filter further by series with a specific measurement and field |> filter(fn: (r) => r._measurement == "cpu" and r._field == "usage_system")

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// get all data from the telegraf db from(bucket:”telegraf/autogen”) // filter that by the last hour |> range(start:-1h) // filter further by series with a specific measurement and field |> filter(fn: (r) => r._measurement == "cpu" and r._field == "usage_system") Comments

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// get all data from the telegraf db from(bucket:”telegraf/autogen”) // filter that by the last hour |> range(start:-1h) // filter further by series with a specific measurement and field |> filter(fn: (r) => r._measurement == "cpu" and r._field == "usage_system") Named Arguments

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// get all data from the telegraf db from(bucket:”telegraf/autogen”) // filter that by the last hour |> range(start:-1h) // filter further by series with a specific measurement and field |> filter(fn: (r) => r._measurement == "cpu" and r._field == "usage_system") String Literals

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// get all data from the telegraf db from(bucket:”telegraf/autogen”) // filter that by the last hour |> range(start:-1h) // filter further by series with a specific measurement and field |> filter(fn: (r) => r._measurement == "cpu" and r._field == "usage_system") Buckets, not DBs

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// get all data from the telegraf db from(bucket:”telegraf/autogen”) // filter that by the last hour |> range(start:-1h) // filter further by series with a specific measurement and field |> filter(fn: (r) => r._measurement == "cpu" and r._field == "usage_system") Duration Literal

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// get all data from the telegraf db from(bucket:”telegraf/autogen”) // filter that by the last hour |> range(start:2018-11-07T00:00:00Z) // filter further by series with a specific measurement and field |> filter(fn: (r) => r._measurement == "cpu" and r._field == "usage_system") Time Literal

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// get all data from the telegraf db from(bucket:”telegraf/autogen”) // filter that by the last hour |> range(start:-1h) // filter further by series with a specific measurement and field |> filter(fn: (r) => r._measurement == "cpu" and r._field == "usage_system") Pipe forward operator

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// get all data from the telegraf db from(bucket:”telegraf/autogen”) // filter that by the last hour |> range(start:-1h) // filter further by series with a specific measurement and field |> filter(fn: (r) => r._measurement == "cpu" and r._field == "usage_system") Anonymous Function

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// get all data from the telegraf db from(bucket:”telegraf/autogen”) // filter that by the last hour |> range(start:-1h) // filter further by series with a specific measurement and field |> filter(fn: (r) => (r._measurement == "cpu" or r._measurement == “cpu") and r.host == “serverA") Predicate Function

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// variables some_int = 23

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// variables some_int = 23 some_float = 23.2

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// variables some_int = 23 some_float = 23.2 some_string = “cpu"

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// variables some_int = 23 some_float = 23.2 some_string = “cpu" some_duration = 1h

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// variables some_int = 23 some_float = 23.2 some_string = “cpu" some_duration = 1h some_time = 2018-10-10T19:00:00

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// variables some_int = 23 some_float = 23.2 some_string = “cpu" some_duration = 1h some_time = 2018-10-10T19:00:00 some_array = [1, 6, 20, 22]

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// variables some_int = 23 some_float = 23.2 some_string = “cpu" some_duration = 1h some_time = 2018-10-10T19:00:00 some_array = [1, 6, 20, 22] some_object = {foo: "hello" bar: 22}

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// defining a pipe forwardable function square = (tables=<-) => tables |> map(fn: (r) => {r with _value: r._value * r._value})

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// defining a pipe forwardable function square = (tables=<-) => tables |> map(fn: (r) => {r with _value: r._value * r._value}) Accepts a pipe forward assigns to tables variable

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// defining a pipe forwardable function square = (tables=<-) => tables |> map(fn: (r) => {r with _value: r._value * r._value}) from(bucket:"foo") |> range(start: -1h) |> filter(fn: (r) => r._measurement == "samples") |> square() |> filter(fn: (r) => r._value > 23.2)

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// defining a pipe forwardable function square = (tables=<-) => tables |> map(fn: (r) => {r with _value: r._value * r._value}) from(bucket:"foo") |> range(start: -1h) |> filter(fn: (r) => r._measurement == "samples") |> square() |> filter(fn: (r) => r._value > 23.2) Calling the function

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Data Model & Working with Tables

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Example Series _measurement=mem,host=A,region=west,_field=free _measurement=mem,host=B,region=west,_field=free _measurement=cpu,host=A,region=west,_field=usage_system _measurement=cpu,host=A,region=west,_field=usage_user

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Example Series _measurement=mem,host=A,region=west,_field=free _measurement=mem,host=B,region=west,_field=free _measurement=cpu,host=A,region=west,_field=usage_system _measurement=cpu,host=A,region=west,_field=usage_user Measurement

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Example Series _measurement=mem,host=A,region=west,_field=free _measurement=mem,host=B,region=west,_field=free _measurement=cpu,host=A,region=west,_field=usage_system _measurement=cpu,host=A,region=west,_field=usage_user Field

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Table _measurement host region _field _time _value mem A west free 2018-06-14T09:15:00 10 mem A west free 2018-06-14T09:14:50 10

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_measurement host region _field _time _value mem A west free 2018-06-14T09:15:00 10 mem A west free 2018-06-14T09:14:50 10 Column

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_measurement host region _field _time _value mem A west free 2018-06-14T09:15:00 10 mem A west free 2018-06-14T09:14:50 10 Record

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_measurement host region _field _time _value mem A west free 2018-06-14T09:15:00 10 mem A west free 2018-06-14T09:14:50 10 Group Key _measurement=mem,host=A,region=west,_field=free

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_measurement host region _field _time _value mem A west free 2018-06-14T09:15:00 10 mem A west free 2018-06-14T09:14:50 10 Every record has the same value! _measurement=mem,host=A,region=west,_field=free

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Table Per Series _measurement host region _field _time _value mem A west free 2018-06-14T09:15:00 10 mem A west free 2018-06-14T09:14:50 11 _measurement host region _field _time _value mem B west free 2018-06-14T09:15:00 20 mem B west free 2018-06-14T09:14:50 22 _measurement host region _field _time _value cpu A west usage_user 2018-06-14T09:15:00 45 cpu A west usage_user 2018-06-14T09:14:50 49 _measurement host region _field _time _value cpu A west usage_system 2018-06-14T09:15:00 35 cpu A west usage_system 2018-06-14T09:14:50 38

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input tables -> function -> output tables

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input tables -> function -> output tables // example query from(bucket:"telegraf") |> range(start:2018-06-14T09:14:50, stop:2018-06-14T09:15:01) |> filter(fn: r => r._measurement == “mem" and r._field == “free”) |> sum()

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input tables -> function -> output tables What to sum on? // example query from(bucket:"telegraf") |> range(start:2018-06-14T09:14:50, stop:2018-06-14T09:15:01) |> filter(fn: r => r._measurement == “mem" and r._field == “free”) |> sum()

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input tables -> function -> output tables Default columns argument // example query from(bucket:"telegraf") |> range(start:2018-06-14T09:14:50, stop:2018-06-14T09:15:01) |> filter(fn: r => r._measurement == “mem" and r._field == “free”) |> sum(columns: [“_value”])

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input tables -> function -> output tables _meas ureme host region _field _time _valu e mem A west free 2018-06- 14T09:1 10 mem A west free 2018-06- 14T09:1 11 _meas ureme host region _field _time _valu e mem B west free 2018-06- 14T09:15 20 mem B west free 2018-06- 14T09:14 22 Input in table form // example query from(bucket:”telegraf") |> range(start:2018-06-14T09:14:50, stop:2018-06-14T09:15:01) |> filter(fn: r => r._measurement == “mem" and r._field == “free”) |> sum()

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input tables -> function -> output tables _meas ureme host region _field _time _valu e mem A west free 2018-06- 14T09:1 10 mem A west free 2018-06- 14T09:1 11 _meas ureme host region _field _time _valu e mem B west free 2018-06- 14T09:15 20 mem B west free 2018-06- 14T09:14 22 sum() // example query from(bucket:"telegraf") |> range(start:2018-06-14T09:14:50, stop:2018-06-14T09:15:01) |> filter(fn: r => r._measurement == “mem" and r._field == “free”) |> sum()

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input tables -> function -> output tables // example query from(bucket:"telegraf") |> range(start:2018-06-14T09:14:50, stop:2018-06-14T09:15:01) |> filter(fn: r => r._measurement == “mem" and r._field == “free”) |> sum() _meas ureme host region _field _time _valu e mem A west free 2018-06- 14T09:1 10 mem A west free 2018-06- 14T09:1 11 _meas ureme host region _field _time _valu e mem B west free 2018-06- 14T09:15 20 mem B west free 2018-06- 14T09:14 22 sum() _meas ureme host region _field _time _valu e mem A west free 2018-06- 14T09:1 21 _meas ureme host region _field _time _valu e mem B west free 2018-06- 14T09:15 42

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N to N table mapping (1 to 1 mapping)

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N to M table mapping

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window // example query from(bucket:"telegraf") |> range(start:2018-06-14T09:14:30, stop:2018-06-14T09:15:01) |> filter(fn: r => r._measurement == “mem" and r._field == “free”) |> window(every:20s) 30s of data (4 samples)

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window // example query from(bucket:"telegraf") |> range(start:2018-06-14T09:14:30, stop:2018-06-14T09:15:01) |> filter(fn: r => r._measurement == “mem" and r._field == “free”) |> window(every:20s) split into 20s windows

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window _meas host region _field _time _valu mem A west free …14:30 10 mem A west free …14:40 11 mem A west free …14:50 12 mem A west free …15:00 13 _meas host region _field _time _valu mem B west free …14:30 20 mem B west free …14:40 22 mem B west free …14:50 23 mem B west free …15:00 24 // example query from(bucket:"telegraf") |> range(start:2018-06-14T09:14:30, stop:2018-06-14T09:15:01) |> filter(fn: r => r._measurement == “mem" and r._field == “free”) |> window(every:20s) Input

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window _meas host region _field _time _valu mem A west free …14:30 10 mem A west free …14:40 11 mem A west free …14:50 12 mem A west free …15:00 13 _meas host region _field _time _valu mem B west free …14:30 20 mem B west free …14:40 22 mem B west free …14:50 23 mem B west free …15:00 24 window( every:20s) // example query from(bucket:"telegraf") |> range(start:2018-06-14T09:14:30, stop:2018-06-14T09:15:01) |> filter(fn: r => r._measurement == “mem" and r._field == “free”) |> window(every:20s)

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window _meas host region _field _time _valu mem A west free …14:30 10 mem A west free …14:40 11 mem A west free …14:50 12 mem A west free …15:00 13 _meas host region _field _time _valu mem B west free …14:30 20 mem B west free …14:40 22 mem B west free …14:50 23 mem B west free …15:00 24 window( every:20s) // example query from(bucket:"telegraf") |> range(start:2018-06-14T09:14:30, stop:2018-06-14T09:15:01) |> filter(fn: r => r._measurement == “mem" and r._field == “free”) |> window(every:20s) _meas ureme host region _field _time _valu e mem A west free …14:30 10 mem A west free …14:40 11 _meas ureme host region _field _time _valu e mem B west free …14:50 23 mem B west free …15:00 24 _meas ureme host region _field _time _valu e mem B west free …14:30 20 mem B west free …14:40 22 _meas ureme host region _field _time _valu e mem A west free …14:50 12 mem A west free …15:00 13

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window _meas host region _field _time _valu mem A west free …14:30 10 mem A west free …14:40 11 mem A west free …14:50 12 mem A west free …15:00 13 _meas host region _field _time _valu mem B west free …14:30 20 mem B west free …14:40 22 mem B west free …14:50 23 mem B west free …15:00 24 window( every:20s) // example query from(bucket:"telegraf") |> range(start:2018-06-14T09:14:30, stop:2018-06-14T09:15:01) |> filter(fn: r => r._measurement == “mem" and r._field == “free”) |> window(every:20s) _meas ureme host region _field _time _valu e mem A west free …14:30 10 mem A west free …14:40 11 _meas ureme host region _field _time _valu e mem B west free …14:50 23 mem B west free …15:00 24 _meas ureme host region _field _time _valu e mem B west free …14:30 20 mem B west free …14:40 22 _meas ureme host region _field _time _valu e mem A west free …14:50 12 mem A west free …15:00 13 N to M tables

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Window based on time _start and _stop columns

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group // example query from(bucket:"telegraf") |> range(start:2018-06-14T09:14:30, stop:2018-06-14T09:15:01) |> filter(fn: r => r._measurement == “mem" and r._field == “free”) |> group(keys:[“region"])

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group // example query from(bucket:"telegraf") |> range(start:2018-06-14T09:14:30, stop:2018-06-14T09:15:01) |> filter(fn: r => r._measurement == “mem" and r._field == “free”) |> group(keys:[“region"]) new group key

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group _meas host region _field _time _valu mem A west free …14:30 10 mem A west free …14:40 11 mem A west free …14:50 12 mem A west free …15:00 13 _meas host region _field _time _valu mem B west free …14:30 20 mem B west free …14:40 22 mem B west free …14:50 23 mem B west free …15:00 24 // example query from(bucket:"telegraf") |> range(start:2018-06-14T09:14:30, stop:2018-06-14T09:15:01) |> filter(fn: r => r._measurement == “mem" and r._field == “free”) |> group(keys:[“region"])

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group _meas host region _field _time _valu mem A west free …14:30 10 mem A west free …14:40 11 mem A west free …14:50 12 mem A west free …15:00 13 _meas host region _field _time _valu mem B west free …14:30 20 mem B west free …14:40 22 mem B west free …14:50 23 mem B west free …15:00 24 group( keys: [“region”]) // example query from(bucket:"telegraf") |> range(start:2018-06-14T09:14:30, stop:2018-06-14T09:15:01) |> filter(fn: r => r._measurement == “mem" and r._field == “free”) |> group(keys:[“region"]) _meas ureme host region _field _time _valu e mem A west free …14:30 10 mem B west free …14:30 20 mem A west free …14:40 11 mem B west free …14:40 21 mem A west free …14:50 12 mem B west free …14:50 22 mem B west free …15:00 13 mem B west free …15:00 23 N to M tables M == cardinality(group keys)

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Group based on columns

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New Language?

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4GL

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Domain Specific Languages

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JavaScript?

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GUI

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Many Data Sources

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Optimize for each

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Cross compilation

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AST = API

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Distributed Engine

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Tables Everywhere

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from(bucket: "foo") |> range(start: -10m) |> filter(fn: (r) => r._measurement == "cpu") |> group(columns: ["_measurement"]) |> sort(columns: ["_value"]) Sorting by value!

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Group by anything

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Measurements, tags, fields don’t matter

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Beyond Queries

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option task = { name: "email alert digest", cron: "0 5 * * 0" } import "smtp" body = "" from(bucket: "alerts") |> range(start: -24h) |> filter(fn: (r) => (r.level == "warn" or r.level == "critical") and r._field == "message") |> group(columns: ["alert"]) |> count() |> group() |> map(fn: (r) => body = body + "Alert {r.alert} triggered {r._value} times\n") smtp.to( config: loadSecret(name: "smtp_digest"), to: "[email protected]", title: "Alert digest for {now()}", body: message)

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option task = { name: "email alert digest", cron: "0 5 * * 0" } import "smtp" body = "" from(bucket: "alerts") |> range(start: -24h) |> filter(fn: (r) => (r.level == "warn" or r.level == "critical") and r._field == "message") |> group(columns: ["alert"]) |> count() |> group() |> map(fn: (r) => body = body + "Alert {r.alert} triggered {r._value} times\n") smtp.to( config: loadSecret(name: "smtp_digest"), to: "[email protected]", title: "Alert digest for {now()}", body: message) tasks

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option task = { name: "email alert digest", cron: "0 5 * * 0" } import "smtp" body = "" from(bucket: "alerts") |> range(start: -24h) |> filter(fn: (r) => (r.level == "warn" or r.level == "critical") and r._field == "message") |> group(columns: ["alert"]) |> count() |> group() |> map(fn: (r) => body = body + "Alert {r.alert} triggered {r._value} times\n") smtp.to( config: loadSecret(name: "smtp_digest"), to: "[email protected]", title: "Alert digest for {now()}", body: message) cron scheduling

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option task = { name: "email alert digest", cron: "0 5 * * 0" } import "smtp" body = "" from(bucket: "alerts") |> range(start: -24h) |> filter(fn: (r) => (r.level == "warn" or r.level == "critical") and r._field == "message") |> group(columns: ["alert"]) |> count() |> group() |> map(fn: (r) => body = body + "Alert {r.alert} triggered {r._value} times\n") smtp.to( config: loadSecret(name: "smtp_digest"), to: "[email protected]", title: "Alert digest for {now()}", body: message) packages & imports

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option task = { name: "email alert digest", cron: "0 5 * * 0" } import "smtp" body = "" from(bucket: "alerts") |> range(start: -24h) |> filter(fn: (r) => (r.level == "warn" or r.level == "critical") and r._field == "message") |> group(columns: ["alert"]) |> count() |> group() |> map(fn: (r) => body = body + "Alert {r.alert} triggered {r._value} times\n") smtp.to( config: loadSecret(name: "smtp_digest"), to: "[email protected]", title: "Alert digest for {now()}", body: message) String interpolation

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option task = { name: "email alert digest", cron: "0 5 * * 0" } import "smtp" body = "" from(bucket: "alerts") |> range(start: -24h) |> filter(fn: (r) => (r.level == "warn" or r.level == "critical") and r._field == "message") |> group(columns: ["alert"]) |> count() |> group() |> map(fn: (r) => body = body + "Alert {r.alert} triggered {r._value} times\n") smtp.to( config: loadSecret(name: "smtp_digest"), to: "[email protected]", title: "Alert digest for {now()}", body: message) Ship data elsewhere

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option task = { name: "email alert digest", cron: "0 5 * * 0" } import "smtp" body = "" from(bucket: "alerts") |> range(start: -24h) |> filter(fn: (r) => (r.level == "warn" or r.level == "critical") and r._field == "message") |> group(columns: ["alert"]) |> count() |> group() |> map(fn: (r) => body = body + "Alert {r.alert} triggered {r._value} times\n") smtp.to( config: loadSecret(name: "smtp_digest"), to: "[email protected]", title: "Alert digest for {now()}", body: message) Store secrets in a store like Vault

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Monitoring as Code

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• Finalizing Spec • Error Handling • Test Runner & CLI • User Packages • Flow Control (if/else) Status

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Status • Alpha 7 this week • API, Tasks, Dashboards • Client Libraries (soon) • Monitoring & Alerting (soon)

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https://influxdata.com/download 2.0

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Thank you Paul Dix @pauldix paul@influxdata.com