In the first two parts of our Inside Flink blog series, we explored the benefits of stream processing with Flink and common Flink use cases for which teams are choosing to leverage the popular framework to unlock the full potential of streaming. Specifically, we broke down the key reasons why developers are choosing Apache Flink® as their stream processing framework, as well as the ways in which they are putting it into practice.
One of the most important questions in architecting a data platform is where to store and archive data. In a blog series, we’ll cover the different storage strategies for Kafka and introduce you to Lenses’ S3 Connector for backup/restore. But in this first blog, we must introduce the different Cloud storage options available. Later blogs will focus on specific solutions, explain in more depth how this maps to Kafka and then how Lenses manage your Kafka topic backups.
CNA worked with Google Cloud and several third-party data vendors to develop a solution to address challenges with underwriting flood risk assessment.
