5 reasons why operating streaming ingestion as a service is difficult

Streaming data ingestion has become crucial as businesses increasingly rely on real-time analytics, yet transitioning a streaming ingestion system from a demo to a reliable 24/7 production service presents significant challenges. While setting up a basic pipeline with tools like Kafka Connect and Flink is straightforward, scaling it to handle real-world traffic requires robust monitoring, regular updates, a dedicated on-call team, and ongoing data maintenance. The system must also manage the bursty nature of streaming data, necessitating scalable architecture for both compute and storage. To alleviate these complexities, some companies, such as Starburst, offer Data Ingest as a Service solutions that promise to handle all operational burdens, allowing businesses to focus on delivering value to their customers. These services aim to offer a "white-glove" experience, ensuring seamless management of the streaming pipeline without any client-side operational responsibilities, thereby differentiating themselves from other SaaS offerings that might still require some user intervention.