Streaming data pipelines through queuing technologies such as Kafka and RabbitMQ plays a crucial role in powering event-driven applications to enable real-time data processing and analysis. However, the asynchronous and distributed nature of these applications makes it hard to effectively keep track of the interdependencies between application services and the queues within your streaming data pipeline, as well as resolve delays before they create negative cascading effects downstream. In this session, you’ll discover how Datadog Data Streams Monitoring (DSM) addresses these challenges through automatic topology mapping, out-of-the-box latency and consumer lag metrics, and other troubleshooting tools that are unique to the APM market. Learn how DSM fits into your observability journey with Datadog, enabling you to proactively detect delays, localize the source of bottlenecks, and mitigate message backups. Join us to learn how you can reduce downtime and deliver exceptional user experiences.