At first glance, it might seem that microservices architecture–where application modules and functionality are decoupled and isolated to improve stability and development speed–has little to do with real-time, streaming Fast Data architecture.
That assumption, however, is reversed in a Lightbend recent survey, where 75% of over 2400 developers revealed that they are already using (or planning to use) microservices to enable real-time streaming use cases, showing that a key characteristic of Fast Data architectures is the use of microservices for streaming functionality:
Streaming, Fast Data systems promise near real-time access to information. These streaming systems, however, aren’t just faster versions of Big Data; they force architecture changes to meet new demands for reliability and dynamic scalability, more like microservices.
This means new challenges for your organization. Whereas a batch job might run for hours, a stream processing application might run for weeks or months. This raises the bar for making these systems resilient against traffic spikes, hardware and network failures, and so forth.
The good news is that there is a strong history of facing these demands in the world of microservices, as we see here in the progression of microservices adoption as advanced Fast Data use cases move towards production readiness:
Learn more about these trends in our 20-page report The Need For Speed: Fast Data Development Trends (PDF):