Problem
Trend analysis based on batch reports misses emerging signals.
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Trend Metrics
Streaming platform that detects news trends in real time.
KafkaSparkAirflowCassandraGrafanaPrometheus
Overview
Focus
Streaming platform that spots topic momentum and sentiment changes every minute.
Value
Kafka for ingestion, Spark for NLP, Cassandra as the store, Airflow for orchestration, Grafana for dashboards. Designed for horizontal scale and observability.
Solution
Kafka + Spark + NLP pipelines detect shifts and feed Grafana dashboards.
How it works
Feeds land in Kafka, Spark stages NLP, metrics persist in Cassandra, dashboards refresh in Grafana.
Architecture
Kafka, Spark, Cassandra, Airflow, Prometheus, Grafana tied via Helm charts.
Security
Mutual TLS between clusters, ACLs on Kafka topics, and Prometheus guards ensure compliance for sensitive signal processing.
Operations
Airflow retries, Prometheus lag monitors, and autoscaling keep Kafka/Spark pipelines resilient while dashboards expose ingestion health.
Observability
Grafana dashboards highlight lag, resource usage, and alert conditions so operations can prioritize capacity changes.
Runbook
Consumer lag → add partitions or scale consumers.
Job failed → examine Airflow logs and rerun DAG.
Alert fired → notify the analytics team.
Results
Low-latency trend detection surfaces KPIs early and keeps resource usage transparent.