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Everactive relies on Aiven for IoT data
Everactive, a provider of batteryless IoT tech, set up a sensor data pipeline on top of Aiven for Apache Kafka®. Find out how it went.
Everactive, a pioneer in a new category of batteryless Internet of Things technology, sought a pipeline for huge amounts of sensor data, a solution that they wouldn’t have to manage themselves. In Aiven they found a flexible, reliable and secure partner, and Aiven for Apache Kafka® now forms the backbone of their data infrastructure.
- Groundbreaking green innovation in sensor technology.
- Using Apache Kafka as a message broker between IoT devices and longterm storage databases.
- Small team + big data: needed a managed solution.
"With Aiven, things just work better than they did before."
Rob Cook
Principal Software Engineer at Everactive
Founded in 2012 with roots going back to pioneering M.I.T. research, Everactive provides an IoT platform based on self-powered sensor devices and low-power wireless communication. “We’re trying to remove the batteries from the Internet of Things,” says Carlos Olmos, Senior Principal Software Engineer at Everactive.
The company’s low-power devices run on low levels of energy harvested from the environment, for example solar panels, radio waves, thermal gradients and vibrations. The feats of electrical engineering that created their offering, however, are only a part of the story. They also have to provide their customers with a performant data pipeline from sensor to storage to visualization.
“It’s not enough just to have hardware,” says Rob Cook, Principal Software Engineer at Everactive. “For the system to be useful, you have to make it easy for people to utilize it, not just in terms of building other hardware on top of it but also consuming the streams of data that it generates.”
The company’s first application was a self-powered Steam Trap Monitoring solution, released in 2018, which reduces energy waste and carbon emissions. In 2020 they made available a Machine Health Monitoring solution that analyzes vibrations of industrial rotating machines like motors and compressors. These are definitely not just hardware solutions; instead, they put data to work and employ innovative algorithms to process it to gain insights that no other systems can.
When Everactive constructed their first data pipeline in 2014, they started with Apache NiFi and OpenTSDB. Very soon they outgrew this setup. “We weren’t able to automate anything in that system, and management was a pain,” says Rob, “Then we ran into performance issues, and upgrading into a cluster wasn’t feasible.” If they couldn’t manage one single server, how would they ever manage a whole cluster?
Next they tried out an Apache Pulsar cluster, but this had essentially the same problems. “In theory, it was inexpensive to run our own cluster, but we couldn’t both run it and do our actual jobs,” Rob explains. “And we couldn’t find anybody we could pay money to run it for us.”
In the meantime, performance issues were accumulating. Sensor installations were taking too long, because the signals from the sensor had to travel through a bottlenecked system, which took up to 5 minutes per sensor.
At this point, too, the concept was fully commercialized and business was really taking off. They needed a solution. Now, at least, they had a much better idea of what they were looking for: a system that would be…
- … able to ingest huge amounts of data and pass it into a time-series database for processing.
- … easily scalable.
- … fault tolerant.
- … managed for Everactive by experts.
Fortunately, there was Apache Kafka®, a widely used solution available as a managed service.
"[With Kafka and Terraform] we’ve managed to automate almost everything: configuration, deployment, and maintenance."
Carlos Olmos
Senior Principal Software Engineer at Everactive
Apache Kafka is designed for rapid high-volume throughput and is a staple of IoT and streaming architectures. It’s no wonder that Everactive found it suitable for their needs, too. Today, Aiven for Apache Kafka is very much at the heart of their data infrastructure. It receives time series data from millions of self-powered sensors and stores it temporarily. According to the original use case, the events are then ingested into a PostgreSQL database where customer systems can retrieve them.
Everactive has moved forward from the initial concept, however. Now their Apache Kafka instance serves data also to the monitoring system and elsewhere, because connectors are easily available.
Is it more expensive for Everactive? “Possibly,” Carlos says, “if you just count the wages of the staff. But every hour we spend trying to reboot a server is an hour we don't spend developing our core business.”
He continues: “Having our clusters managed by experts is also an insurance policy. Just one event, if it’s bad enough, can destroy the entire value you’ve built. If you’re buying a managed service, you know that there's a whole company devoted to preventing or fixing that event, and they’ll do it much more efficiently than we would do it internally.”
"Having our clusters managed by experts is also an insurance policy."
Carlos Olmos
Senior Principal Software Engineer at Everactive
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