In this training webinar, we will walk you through the basics of InfluxDB – the purpose-built time series database. InfluxDB has everything you need from a time series platform in a single binary – a multi-tenanted time series database, UI and dashboarding tools, background processing and monitoring agent. This one-hour session will include the training and time for live Q&A. What you will learn Core concepts of time series databases An overview of the InfluxDB platform How to ingesting and query data in InfluxDB

1. June 2021
Russ Savage | Director of Product Management
Virtual Training:
Intro to InfluxDB

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2
Agenda
1. What is InfluxDB
2. Basic Concepts
3. Demo

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3
What is InfluxDB?

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A massive community of open source & cloud developers
• Self-starters
• Production teams
• Expect OSS & usage-based
models
• Industrial IoT
• End-user & consumer IoT
• Real-time analytics
• Networks & transactions
by cloud
by
language
& tool
Builders of Apps From Technical Ecosystems Use Case Focused

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Get started quickly
with more tools
• Rest API
• OSS integrations
• Cloud delivery
and less code.
A POWERFUL API & TOOL SET FOR BUILDING REAL-TIME APPS
Collect
using hundreds of
integrations &
OSS tools
Write/Query
in multiple
languages built for
real-time data
Abstract
using client
libraries for your
preferred language
Manage
applications &
account via the
developer console
INFLUXDATA API & TOOLS
DEVELOPER APPLICATIONS
Io
T
Transactions Analytics

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Run apps in
production with
absolute confidence
on the only
purpose-built time
series engine.
High Speed Ingest
via both batch &
streaming
Flexible Schema
learns & adapts
as it goes
High & Low
Fidelity
retention &
storage
Managed Functions
hosted in
the cloud
A HIGH-PERFORMANCE ENGINE TO HANDLE REAL-TIME
DATA WORKLOADS
INFLUXDATA API & TOOLS
INFLUXDATA REAL-TIME ENGINE
TIME SERIES
DATABASE

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INFLUXDB ENTERPRISE
Self Managed, High
Availability & Secure
priced per node
INFLUXDB
Open source
time series database.
High performing,
Schemaless, Smart
extraction of data (raw,
sliding, aggregates)
INFLUXDB EDGE
Extend your applications to
the IoT edge for real-time
insights in connected,
disconnected, or hybrid
environments.
INFLUXDB CLOUD
Elastic Serverless
Time Series as a Service
pay per use
INFLUXDB PLATFORM
PRODUCT OFFERINGS

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InfluxDB
Time Series
Platform
EMPOWERS DEVELOPERS
TO BUILD IOT,
ANALYTICS, &
MONITORING SOFTWARE.
– Designed for time series analysis
– Easy to share, easy to extend
– Multi data source
– Open Source (MIT license)
– Easy to get started, powerful to
scale

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Powerful APIs, Tools, & Ecosystem
Developers using the InfluxDB platform build their applications
with less effort, less code, and less configuration.
Unrestricted developer
productivity
Client and server
libraries in everything
from React, JavaScript,
Go, Python and more.
Get a head-start with
templates
Inspiring templates for
every use case. Easy to
create and share — find
what’s right for you.
Vibrant open source
community
A diverse and highly
motivated community,
making contributions in
code, & documentation.
Powerful & active
ecosystem
200+ Telegraf plugins,
integrations with
Grafana or data sources
like Google Bigtable.

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Current Data Acquisition - All Methods
Agent-based Push (aka Telegraf)
Agentless Pull (aka Scrapers)
Client Libraries
Native/Ecosystem
● 200+ Telegraf plugins
● Regular cadence of releases
● Why use it?
○ No code
○ Large community
○ Lightweight but powerful
○ Customizable
● Prometheus scraper (OSS only)
● Flux prometheus.from
● Flux csv.from(url)
● Why use them?
○ Get data in quickly
○ Doesn’t require agent downloads on
monitoring device
● 11 Libraries: Python, C#, Java, GO,
Javascript/Node.js, Ruby, PHP, Scala, Swift,
Kotlin, Arduino
● Handles batching, chunking, setting right
headers, etc.
● Why use them?
○ Easy way to get started
○ Need libraries when building custom
applications
● Source system speaks line protocol
● Examples: JMeter, NiFi, Vector, FluentD
● Influx CLI CSV Import
● Why use them?
○ Know what you want to monitor,
quick and easy integration

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InfluxData Platform Architecture

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Get InfluxDB
InfluxDB Cloud
https:/
/cloud2.influxdata.com/signup
Download OSS
https:/
/portal.influxdata.com/downloads/

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Using InfluxDB

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Concepts: Data Model
● Measurement
○ A name to a group of data at a high level
● Tag set
○ A set of key-value pairs to group data at a low level (values are strings)
● Field set
○ A set of key-value pairs to represent data (values are numerical & strings)
● Timestamp
○ Time of the data with nanosecond precision
● Series
○ A unique combination of measure+tags

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Data model vs ingestion & storage
Measurement
Tag set
Field set
Timestamp
Ingestion Storage
Series
Buckets
(set of series)

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Concepts: Time Series Database Schema
Data Ingestion Format
• Points are written to InfluxDB using the Line Protocol, which
follows the following format:
<measurement>[,<tag-key>=<tag-value>] [<field-key>=<field-value>]
[unix-nano-timestamp]
Reference: https://docs.influxdata.com/influxdb/v2.0/reference/syntax/line-protocol/
Tag Set
hostname=server02, us_west=az
Measurement
cpu_load
Field Set
temp=24.5, volts=7
Timestamp
1234567890000000

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Bucket physical view
● Columnar Data Stores
● Best for column selection and aggregation thanks to
- Disk and memory locality
- Cache locality
_time
1492...1
1492...0
_m
obs
obs
host
ovenB
ovenA
num
1
1
line
west
west
temp
301
125
humidity
23
75
_m=_measurment tags fields

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Schema Considerations
• Tags are indexed. Fields are not.
• Field Types are immutable
• Store data in tags if you plan to use them with GROUP BY()
• Store data in fields if you plan to use them with Flux function
• Store data in fields if you need them to be something other than a string
• The best schema depends primarily on what queries you want to run. At a high level:
– You can't GROUP BY fields, only tags
– You can't do math on tags or across measurements
– Queries that filter by tags are fast
– Queries that filter by fields are slower
– Be aware of series cardinality . . . It matters
Concepts: InfluxDB Schema Best Practices

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Series Cardinality
• The number of unique database, measurement, and tag set combinations in an InfluxDB
instance.
• For example, assume that an InfluxDB instance has a single database and one
measurement.
– The single measurement has two tag keys: email and status.
– If there are three different emails, and each email address is associated with two different statuses then the
series cardinality for the measurement is 6: (3 * 2 = 6)
Concepts: InfluxDB Schema Best Practices
email status
lorr@influxdata.com start
lorr@influxdata.com finish
marv@influxdata.com start
marv@influxdata.com finish
cliff@influxdata.com start
cliff@influxdata.com finish
Reference:
https://docs.influxdata.com/influxdb/v2.0/write-data/best-practices/resolve-high-cardinality/

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Series Cardinality Example
• Now imagine that a measurement has two tag keys:
– containerId and processId
– Each tag has 10,000 possibilities
– In this series cardinality for the measurement is 100,000,000 (10,000 x 10,000)
– Further let’s assume that each series takes up 1k in memory, that equates to 102.4GB of
RAM. . . you begin to see the problem
• We call this “Run-away series cardinality”
• Read more about this
– https://www.influxdata.com/blog/tldr-influxdb-tech-tips-monitoring-tasks-and-finding-th
e-source-of-runaway-cardinality/
– Index and Time-Structured Merge Tree (TSM) Overview in InfluxDB 1.5
Concepts: InfluxDB Schema Best Practices

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Introducing Flux
A functional data scripting language designed for querying, analyzing, and
acting on data. It is intended to be usable, readable, flexible, composable,
testable, contributable, and shareable.
“
I don't want to have to write query
code in one language and processing
code in another language.
– Paul Dix, CTO InfluxData

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Demo

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What’s Next
– Build an IoT application workshop | August 5, 2020
○ https://www.influxdata.com/resources/iot-center-workshop/
– Get your cloud account
○ And try InfluxDB Templates
– Check out
○ https://www.influxdata.com/products/influxdb-templates/gallery/
– Performance Tips
– Index and Time-Structured Merge Tree (TSM) Overview
– Integrations
○ https://docs.influxdata.com/telegraf/v1.18/
○ https://www.influxdata.com/products/integrations/

24. Thank You