Your devices are generating ever-increasing data loads in complex, volatile real-world conditions. To make use of that data, you need a robust data pipeline that can receive, store, and analyze it.
The closer your data infrastructure is to your devices, the faster the data transmission. And, the faster the data transmission, the faster you can make adjustments to critical systems or respond to a consumer app.
You can also quickly scale your hardware resources to your needs. For instance, if you’re sending data from HVAC sensors, you can increase capacity during months with extreme weather and decrease it during more temperate ones.
Apache Kafka is renowned for its ability to handle massive amounts of data at low latency. This means that your hot data can be handled immediately and your cold data can be batch processed for later analysis.
Kafka is popular because of its resilience, scalability, and speed. For instance, Comcast uses Aiven for Kafka to help deliver what they call a “truly smart home,” through the Xfinity Home platform.
From Kafka, you want to send your data for real-time and batch processing. For the former, you can include a stream processor such as Kafka Streams or Flink, then push your data into Cassandra for handling information such as last known device state.
For batch processing, it could be as simple as sending your data to S3 for full backups, batch analytics, or even machine learning training. The best part? Aiven can manage most of these components, letting you focus on tasks that add business value.
Comcast provides residential wireless security and automation services through Xfinity Home with the aim of creating a single experience that synthesizes customer home and automation needs. To accomplish this, they needed a low latency, scalable solution: Kafka...Download case study
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