Setting up InfluxData for IoT
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The document outlines an agenda for a seasoned developers workshop focusing on IoT solutions, including sessions on InfluxDB, Telegraf plugins, and IoT data needs. It highlights the importance of time series databases for IoT applications and provides an overview of necessary components for cloud and edge architectures. Key topics include data ingestion, normalization, analytics, and visualization tools essential for effective IoT deployments.
Setting up InfluxData for IoT
- 2. Agenda: Seasoned Developers Track WORKSHOPAGENDA 8:00 AM – 9:00 AM Breakfast 9:00 AM – 10:00 AM InfluxDB Functional Query Language (IFQL) Paul Dix 10:00 AM – 10:50 AM Writing a Telegraf Plugin Noah Crowley 10:50 AM – 11:20 AM Break 11:20 AM – 12:10 PM Using InfluxDB for Open Tracing Chris Goller 12:10 PM – 1:10 PM Lunch 1:10 PM – 2:00 PM Advanced Kapacitor Michael DeSa 2:00 PM – 2:10 PM Break 2:10 PM – 3:10 PM Setting Up InfluxData for IoT David Simmons 3:10 PM – 4:00 PM A True Story About Database Orchestration Gianluca Arbezzano 4:00 PM Pizza and Beer
- 3. David Simmons IoT Developer Evangelist @davidgsIoT Setting Up InfluxData for IoT David Simmons is the IoT Developer Evangelist at InfluxData, helping developers around the globe manage the streams of data that their devices produce. He is passionate about IoT and helped to develop the very first IoT Developer Platform before “IoT” was even ‘a thing.’ David has held numerous technical evangelist roles at companies such as DragonFly IOT, Riverbed Technologies, and Sun. He studied Computer Science at the University of New Mexico and has a BA in Technical Writing from Columbia University.
- 4. Architecting an IoT Solution with InfluxData David G. Simmons @davidgsIoT 2/14/2018
- 5. Agenda • IoT Data Needs • Why does IoT need Time Series Databases – What other kinds of databases might work (or not) • What does an IoT Solution need – In the Cloud – At the edge • IoT Data Collection • IoT Data analysis
- 6. IoT Data Needs • IoT data MUST be – Timely – ingestion rates and query efficiency is key – Accurate – data integrity and platform reliability is important – Actionable – data visualization, anomaly detection & alerting are essential – Deployable in the datacenter and at the edge • IoT deployments are struggling to find efficient, scalable, data platform that meets all of these criteria
- 7. IoT Platform Needs • Extensive protocol support for data ingestion – BLE, Zigbee, Zwave, CoAP, MQTT, MODBUS • Robust offline data capability – Normalization of data – Storage for local data – Local event processing engine • Hardware-agnostic, scalable architecture • Comprehensive analytics and visualization tools Source: https://www.networkworld.com/article/3247801/internet-of- things/the-top-5-user-requirements-of-iot-edge-platforms.html
- 8. Protocol Support • Telegraf has over 150 plugins – More every release • Many IoT-Specific plugins – MQTT – RabbitMQ – Particle.io • Many more to come – CoAP – PPMP
- 9. Robust Offline Data Capability • Normalization of data – Use Kapacitor for data normalization • Storage for local data – Store locally on the edge – Forward upstream to cloud – Downsample before forwarding to reduce bandwidth usage • Local Even Processing Engine – Use Kapacitor for event processing
- 10. Hardware Agnostic, Scalable • Runs on x86 and ARM • Runs on servers and embedded platforms • Single code-base • Simple deployment
- 11. Comprehensive Analytics and Visualization • Use Chronograf for visualization – Also compatible with Grafana • Analytics via visualization, Kapacitor or CQs • Forward data to external analytics platforms
- 12. Why a Time Series Database?
- 13. • Relationships between different kinds of data • Transactional • Frequently updated • IoT Data is not transactional Relational Data
- 14. • Document storage • JSON Objects • NoSQL Databases • IoT data is not document data! Document Data
- 15. • Data over time – Stock prices • Event Data – event@time • Sensor Readings – temperature@time • IoT data is Time Series data Time Series Data
- 16. What Does an IoT Data Solution Need? • In the Cloud – High-capacity data ingestion – Flexible Data retention policies • Not all data needs to be around forever! – Dashboarding and visualization – Alerting • Response to data events
- 17. What Does an IoT Data Solution Need? • At the edge – Same needs as the cloud + – Small, lightweight, yet powerful – Data downsampling – Multi-protocol ingestion
- 19. An IoT Architecture InfluxData • Telegraf • Data Collection • InfluxDB • Short-term storage • Kapacitor • Local Alerts • Chronograf • Local Dashboard
- 20. An IoT Architecture • Run the same stack on the edge as the cloud – Lower cost of development – Faster Time to Awesome™ – Flexible deployment • Location-specific analytics – Shop-floor Dashboard – Backend Dashboard
- 21. IoT Edge Monitoring • Monitor the sensors • Monitor the network – Did the sensor die, or was it the wireless connection? • Monitor the platform – Battery? – CPU? – Storage?
- 22. Edge Dashboard
- 23. An End-to-End IoT Solution for IoT Demo
- 24. Thank You