Real-time data pipelinesContinuous AI trainingApache KafkaTensorFlowAILLMs
Real-Time ML Training Pipelines with Apache Kafka and TensorFlow
8 min read · 1,464 wordsBy Orandi Felix
Don't confuse "online learning" with "real-time training". Online learning updates weights one sample at a time. Real-time training orchestrates model updates across streams, mini-batches, and validation checks—while meeting SLA latency targets.
TensorFlow's `from_generator` gives you control over Kafka consumer offsets—you're now responsible for committing offsets manually. I use a simple counter every 100 batches; production would tie this to validation metrics.
Start with synthetic data—generate Poisson-distributed transactions with controllable drift distributions. Only after the pipeline works should you risk real data.