Safer deployment of streaming applications

This post introduces a new deployment strategy for Flink applications that addresses the challenges of state consistency and safe rollbacks in stateful streaming. Key contributions include: 1. Implementing Flink's savepointing feature to capture application state before deployment, ensuring consistent starting states for new versions and enabling easier rollback. 2. Modifying the deployment process to ensure only one Flink application instance consumes Kafka messages at a time, preventing data loss and ensuring accuracy. 3. Enhancing monitoring with automated health probes and Slack notifications for deployment status. 4. Refining rollback mechanisms for configuration changes by leveraging Kubernetes' versioned ConfigMaps and for resource provision changes by using metadata annotations to store previous replica counts. The new flow is visualized in Spinnaker, reducing manual monitoring and stress for engineers.