Real-time stream processing is growing exponentially in recent years, businesses need to gather insights from real-time data as soon as it’s generated. To do this, developers and software architects use various pipelines and tools to capture and process data in motion. Real-time stream processing has its own challenges such as testing and life-cycle management, scaling and performance, event time and late events, streaming fault tolerance, and processing guarantees. In this talk, I will address those challenges and demonstrate the best practices for real-time stream processing, from data ingestion to data processing with ultra-low latency at scale and at speed, using the Hazelcast platform. I will discuss how you can optimize your real-time streaming projects in the following areas: scalability, performance, failover, reliability, and data recovery.