Our great sponsors
- InfluxDB - Collect and Analyze Billions of Data Points in Real Time
- Onboard AI - Learn any GitHub repo in 59 seconds
- SaaSHub - Software Alternatives and Reviews
-
stream-smarts
Real-time anomaly detection using Kafka, KSQL User Defined Function and a pre-trained model
A bit of python code consumes the ANOMOLY_POWER topic and calls pushbullet. A consumer is established, and an event handler calls the notification service on receipt of a new Kafka events. Each message generates a new push notification.
-
ksql-udf-deep-learning-mqtt-iot
Deep Learning UDF for KSQL for Streaming Anomaly Detection of MQTT IoT Sensor Data
Inspiration for this project comes from Kai Waehner and his project Deep Learning UDF for KSQL. The notification system was inspired by Robin Moffatt and his blog on Event-Driven Alerting with Slack.
-
InfluxDB
Collect and Analyze Billions of Data Points in Real Time. Manage all types of time series data in a single, purpose-built database. Run at any scale in any environment in the cloud, on-premises, or at the edge.
Related posts
- My local Kafka instance stuck in "auto leader balancing"
- Recently joined a DE team and I've been asked to study async, multiprocessing, queuing, and Kafka. Can anybody tell me how to proceed and also share resources that I can use.
- Has anyone seen and handled this error successfully ? : /bin/sh^M: bad interpreter: No such file or directory
- New to kafka..
- How to use Kafka to stream files using three separate machines (one for the producer, one for the broker, and one for the broker)?