Dashboards as Code by Tim Hall, VP of Product | InfluxData

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We are all used to building dashboards for great visualizations, but the issue becomes how to share and collaborate on instrumentation and dashboard design. In this talk, Tim Hall will drill down on dashboard sharing, how to iterate and improve on dashboards within a repository, and lessons learned in sharing and collaborating on dashboards.

Technology

Tim E. Hall / VP Products
Dashboards as Code

Journey
Time Series Database
Observability Platform
• Write less code
• Faster time to awesome
• Enable powerful ecosystem
• High performance
• Time to awesome
• Purpose built

• Interactive & Autonomous Monitoring
• InfluxDB 2.0 Dashboard Overview
• Dashboards as Code (Templates, API, Command Line)
• Visualization Components
• Sharing Expertise

Interactive & Autonomous Monitoring
Manual
Queries
Dashboards
Alerts /
Notifications
Autonomous MonitoringInteractive Monitoring

Manual Queries created via Flux Query Builder
• Data exploration is the start of the journey

Manual Queries created via Flux Script Editor
• Advanced Flux script manipulation and language features

Dashboards are created via Flux
• Creation of dashboards and cells allow for active monitoring

Dashboards are self contained…
• Variables

…and can be imported, exported & shared as templates
• Templates

Dashboards can be completely managed via the API
• Export or Templates can be
checked into source code
control – leverage existing
tooling for CI/CD
• Creating & modifying
dashboards and cells is
simple via the API
• See our Swagger.yml for full
details or /docs for interactive
docs

Templates allow you to instantiate multiple instances of Dashboards
• Admins can create/import Dashboard Templates
• Users don’t need to start from scratch

Dashboards as Code Summary
• Dashboards can be managed via the API
• Dashboards are self contained and can be exported / imported
easily
• Templates foster code reuse and sharing of expertise…but where
does this lead?

InfluxDB 2.x: Composable Solutions
Define and Share via User Defined Packages
Select
Queries & Scripts
Select
Dashboards
Select
Data Sources
Network Monitoring
IOT/Sensor System
Infrastructure Monitoring
Faster time to Awesome!

Introducing
Giraffe Clockface
https://github.com/influxdata/giraffe https://github.com/influxdata/clockface

Giraffe
• A React-based visualization library used to implement the InfluxDB 2.0
UI
• What’s in it?
– A high-level Grammar of Graphics style API that can specify a wide variety of
visualizations with a few simple concepts
– A columnar interface for input data that enables efficient interop with Web Workers
and Apache Arrow
– Easy reactivity and extensibility via React
– Self-contained configs in the style of Vega-Lite
– Support for mapping groupings of columns to a single visual aesthetic
• Docs being developed now

Clockface
• A React + Typescript UI Kit for building visualization applications

Rapidly build applications
• Leverage and reuse visualization components built for InfluxDB
• In conjunction with InfluxDB 2.0 JavaScript client library or stand-
alone
• All in Open Source

Call to Action
• Try it -> InfluxDB 2.0 Alpha or InfluxDB 2.0 Cloud
– Interactive Exploration and Monitoring
– Use Flux Query Builder and/or Flux Script Editor
• Explore Giraffe, Clockface and InfluxDB 2.0 JavaScript Client
Library
• Feedback Welcome!

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How a Heat Treating Plant Ensures Tight Process Control and Exceptional Quali...

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American Metal Processing Company ("AMP") is the US' largest commercial rotary heat treat facility with customers in the automotive, construction, military, and agriculture industries. They use their atmosphere-protected rotary retort furnaces to provide their clients with three primary hardening services: neutral hardening (quench and temper), carburizing, and carbonitriding. This furnace style ensures consistent, uniform heat treatment process vs. traditional batch-or-belt-style furnaces; excels at processing high volumes of smaller parts with tight tolerances; and improves the strength and toughness of plain carbon steels. Discover why AMP’s use of Telegraf, InfluxDB, Node-RED, and Grafana allows them to gain 24/7 insights into their plant operations and metallurgical results. Learn how they use time-stamped data to gain accurate metrics about their consumables usage, furnace profiles, and machine status. Join this webinar as Grant Pinkos dives into: American Metal Processing's approach to heat treating in a digitized environment through connected systems Their approach to collecting and measuring sensor data to enable predictive maintenance and improve product quality Why they need a time series database for managing and analyzing vast amounts of time-stamped data

How Delft University's Engineering Students Make Their EV Formula-Style Race ...

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Delft University is the oldest and largest technical university in the Netherlands with 25,000+ students. Since 1999, they have had a team of students (undergraduate and graduate) designing, building, and racing cars, as part of the Formula Student worldwide competition. The competition has grown to include teams from 1K+ universities in 20+ countries. Students are responsible for all aspects of car manufacturing (research, construction, testing, developing, marketing, management, and fundraising). Delft University's team includes 90 students across disciplines. Discover how Delft University's team uses Marple and InfluxDB to collect telemetry and sensor metrics while they develop, test, and race their electrics cars. They collect sensor data about their EV's control systems using a time series platform. During races, they are collecting IoT data about their batteries, accelerometer, gyroscope, tires, etc. The engineers are able to share important car stats during races which help the drivers tweak their driving decisions — all with the goal of winning. After races, the entire team are able to analyze data in Marple to understand what to do better next time. By using Marple + InfluxDB, their team are able to collect, share and analyze high frequency car data used to make their car faster at competitions. Join this webinar as Robbin Baauw and Nero Vanbiervliet dive into: Marple's approach to empowering engineers to organize, analyze, and visualize their data Delft University's collaborative methodology to building and racing their Formula-style race car How InfluxDB is crucial to their collaborative engineering and racing process

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balena.io helps companies develop, deploy, update, and manage IoT devices. By using Linux containers and other cloud technologies, balena enables teams to quickly and easily build fleets of connected devices. Developers are able to use containers with the language of choice and pull IoT sensor data from 70+ different single board computers into balenaCloud. Discover how to use balena.io to automate your InfluxDB deployments at the edge! During this one-hour session, experts from balena and InfluxData will demonstrate how to build and deploy your own air quality IoT solution. You will learn: The fundamentals of IoT sensor deployment and management using balena. How to use a time series platform to collect and visualize metrics from edge devices. Tips and tricks to using balenaCloud to automate InfluxDB deployments and Telegraf configurations. How to use InfluxDB's Edge Data Replication feature to collect sensor data and push it to InfluxDB Cloud for analysis. No coding experience required, just a curiosity to start your own IoT adventure.

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RudderStack — the creators of the leading open source Customer Data Platform (CDP) — needed a scalable way to collect and store metrics related to customer events and processing times (down to the nanosecond). They provide their clients with data pipelines that simplify data collection from applications, websites, and SaaS platforms. RudderStack's solution enables clients to stream customer data in real time — they quickly deploy flexible data pipelines that send the data to the customer's entire stack without engineering headaches. Customers are able to stream data from any tool using their 16+ SDK's, and they are able to transform the data in-transit using JavaScript or Python. How does RudderStack use a time series platform to provide their customers with real-time analytics? Join this webinar as Ryan McCrary dives into: RudderStack's approach to streamlining data pipelines with their 180+ out-of-the-box integrations Their data architecture including Kapacitor for alerting and Grafana for customized dashboards Why using InfluxDB was crucial for them for fast data collection and providing single-sources of truths for their customers

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This document outlines the schedule for Day 2 of InfluxDays 2022, an event hosted by InfluxData. The schedule includes sessions on building developer experience, how developers like to work, an overview of the InfluxDB developer console and API, demos of client libraries and the InfluxDB v2 API, tips for getting involved in the InfluxDB community and university, use cases for networking monitoring, crypto/fintech, monitoring/observability, and IIoT, and closing thoughts. Recordings of all sessions will be made available to registered attendees by November 7th. Upcoming events include advanced Flux training in London and resources through the community forums, Slack channel, and online university.

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This document contains the agenda for Day 2 of InfluxDays 2022, which includes: - Welcome and introductory remarks from Zoe Steinkamp and Jay Clifford of InfluxData. - Fireside chats and presentations on building great developer experiences, how developers like to work, and use cases for InfluxDB from companies like Tesla, InfluxData, and others. - Sessions on the InfluxDB developer console, APIs, client libraries, getting involved in the community, accelerating time to awesome with InfluxDB University, and tips for analyzing IoT data with InfluxDB. - Closing thoughts from Zoe Steinkamp and Jay Clifford, as well as

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The document summarizes the agenda and sessions for Day 1 of InfluxDays 2022. It includes sessions on InfluxDB data collection, scripting languages like Flux, the InfluxDB time series engine, tasks, storage, and a closing discussion. The agenda involves talks from InfluxData employees on building applications with real-time data, navigating the developer experience, solving problems, the InfluxDB platform, community, education, use cases in crypto/fintech and IIoT, and tips/tricks for analysis.

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2. Tim E. Hall / VP Products Dashboards as Code

3. InfluxDB 2.0 – Changing the Game

4. Journey Time Series Database Observability Platform • Write less code • Faster time to awesome • Enable powerful ecosystem • High performance • Time to awesome • Purpose built

5. • Interactive & Autonomous Monitoring • InfluxDB 2.0 Dashboard Overview • Dashboards as Code (Templates, API, Command Line) • Visualization Components • Sharing Expertise

6. Interactive & Autonomous Monitoring Manual Queries Dashboards Alerts / Notifications Autonomous MonitoringInteractive Monitoring

7. Manual Queries created via Flux Query Builder • Data exploration is the start of the journey

8. Manual Queries created via Flux Script Editor • Advanced Flux script manipulation and language features

9. Dashboards are created via Flux • Creation of dashboards and cells allow for active monitoring

10. Dashboard Visualization Types

11. Dashboards are self contained… • Variables

12. …and can be imported, exported & shared as templates • Templates

13. Dashboards as Code

14. Dashboards can be completely managed via the API • Export or Templates can be checked into source code control – leverage existing tooling for CI/CD • Creating & modifying dashboards and cells is simple via the API • See our Swagger.yml for full details or /docs for interactive docs

15. Templates allow you to instantiate multiple instances of Dashboards • Admins can create/import Dashboard Templates • Users don’t need to start from scratch

16. Dashboards as Code Summary • Dashboards can be managed via the API • Dashboards are self contained and can be exported / imported easily • Templates foster code reuse and sharing of expertise…but where does this lead?

17. InfluxDB 2.x: Composable Solutions Define and Share via User Defined Packages Select Queries & Scripts Select Dashboards Select Data Sources Network Monitoring IOT/Sensor System Infrastructure Monitoring Faster time to Awesome!

18. Visualization Components

19. Introducing Giraffe Clockface https://github.com/influxdata/giraffe https://github.com/influxdata/clockface

20. Giraffe • A React-based visualization library used to implement the InfluxDB 2.0 UI • What’s in it? – A high-level Grammar of Graphics style API that can specify a wide variety of visualizations with a few simple concepts – A columnar interface for input data that enables efficient interop with Web Workers and Apache Arrow – Easy reactivity and extensibility via React – Self-contained configs in the style of Vega-Lite – Support for mapping groupings of columns to a single visual aesthetic • Docs being developed now

21. Clockface • A React + Typescript UI Kit for building visualization applications

22. Rapidly build applications • Leverage and reuse visualization components built for InfluxDB • In conjunction with InfluxDB 2.0 JavaScript client library or stand- alone • All in Open Source

23. Call to Action • Try it -> InfluxDB 2.0 Alpha or InfluxDB 2.0 Cloud – Interactive Exploration and Monitoring – Use Flux Query Builder and/or Flux Script Editor • Explore Giraffe, Clockface and InfluxDB 2.0 JavaScript Client Library • Feedback Welcome!

24. Thank You!

Editor's Notes

We are building the next generation AI driven observability platform for better visibility in this drive to autonomy world...

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