SVP Platform
Stream Processing & Visual Analytics Pipeline Engine
SVP Platform (Stream & Visual Processing) bridges complex data streaming backends like Apache Kafka and Apache Flink with high-clarity operational dashboards. Built for system architects and platform engineers, SVP simplifies windowed state auditing, consumer group rebalance tracking, and real-time stream transformation debugging.
Key Features & Architecture
Real-time Topology Inspector
Renders interactive DAG diagrams of live Kafka topics, stream processing nodes, and sink operators.
Flink Stateful Window Inspection
Inspects stateful stream window contents, checkpoint durations, and watermark lags in real time.
Consumer Group Lag Alerts
Configurable anomaly detection for unexpected partition lag spikes or partition unbalance.
Zero-Impact Passive Agent
Lightweight sidecar deployment requiring minimal memory overhead and zero cluster restart.
Product FAQs
Can SVP Platform be deployed on-premise or in private clouds?
Yes. SVP Platform is packaged as standard Docker containers and Helm charts for seamless Kubernetes and on-premise deployment.
Which messaging systems are supported?
Currently Apache Kafka, Apache Flink, RabbitMQ, and AWS Kinesis.
Release Notes
Flink 1.19 Compatibility & Multi-Cluster Routing
- Full support for Apache Flink 1.19 state backend introspection
- Multi-cluster switcher for monitoring hybrid cloud event streaming setups
Future Roadmap
End-to-end distributed transaction tracing from HTTP entry points down to event log persistence.
SVP Platform Privacy & Data Governance
Product-specific privacy statements, terms of service, and app store data deletion policies.