Lightbend Launches Kubernetes Optimized Fast Data Platform
- By John K. Waters
Lightbend, the company behind the Scala JVM language and developer of the Reactive Platform, unveiled the 2.0 version of its Fast Data Platform today at the Strata Data Conference in New York. This version of the one-year-old platform has been optimized for Kubernetes cluster deployment.
The Lightbend Fast Data Platform is a curated distribution of open source and commercial technologies for designing, building, and deploying streaming fast-data apps and microservices. It comes with the Fast Data Platform Manager application for full lifecycle management and monitoring of Fast Data Platform Clusters, as well as support for Kafka, Spark, Akka Streams, Kafka Streams, HDFS, the Lightbend Enterprise Suite, integration with OpsClarity for monitoring, and support tools.
The company actually released version 1.2 in August with updates to several component versions, a greatly simplified process for deploying the sample apps, improvements to Spark and Kubernetes integration on Mesos, and improved customization options for components during installation.
The big news in version 2.0 is the full optimization for the Kubernetes container orchestration solution. Enterprises now have "a one-stop shop for creating Reactive microservices for streaming data applications, and deploying and managing them on the cloud-native stack's most widely used orchestration solution," the company said in a statement.
Conceptualized in the "Reactive Manifesto," which was co-authored by Lightbend CTO and co-founder Jonas Bonér, reactive applications are apps that better meet the "contemporary challenges of software development" in a world in which applications are deployed to everything from mobile devices to cloud-based clusters running thousands of multicore processors. The Fast Data Platform is billed by the company as the industry's first platform to brings application responsiveness, resilience and elasticity -- the hallmarks of Reactive -- to the streaming data application stack, addressing streaming data requirements from development through production.
The thing to keep in mind about streaming apps is that they run continuously, often for days or months at a time, instead of short batch jobs. Consquently, this responsiveness, resilience, and elasticity are key concerns of microservice design for streaming data architectures. "Reactive microservices have emerged as the most successful pattern for first-movers on fast data and streaming data use cases," Lightbend says, and industry leaders are embracing Reactive.
"The fundamental shift is that we've moved from 'data at rest' to 'data in motion,'" Bonér said in a statement. "Because applications now rely on real-time analytics and model serving, these streaming pipelines become a crucial part of the application. They share the same availability and scalability concerns as microservices. And like microservices, they must be easy to update without impacting the application"
Scala, which was developed by Lightbend co-founder Martin Odersky, is a general purpose, multi-paradigm language designed to integrate features of object-oriented programming and functional programming. Scala runs on the Java Virtual Machine (JVM) and is compatible with existing Java programs. Several modern frameworks are written in Scala, including Spark, Kafka and Lightbend's own Akka. Lightbend is also the company behind the Lagom and Play frameworks.
John K. Waters is the editor in chief of a number of Converge360.com sites, with a focus on high-end development, AI and future tech. He's been writing about cutting-edge technologies and culture of Silicon Valley for more than two decades, and he's written more than a dozen books. He also co-scripted the documentary film Silicon Valley: A 100 Year Renaissance, which aired on PBS. He can be reached at email@example.com.