Microservices Can Help Businesses Embrace Real-Time Data, Survey Finds
A recent global survey from Lightbend reveals that Java Virtual Machine developers are relying less on app server architectures and are moving to containers and microservices for distributed apps that emphasize real-time data streams.
This transition presents major challenges and opportunities for developers. According to TechRepublic, it may become necessary for businesses to embrace real-time data either by utilizing container technologies or microservices in order to stay relevant.
Adopting Fast Data Systems
“Fast data systems need to behave like reactive microservice-based systems,” Mark Brewer, CEO of Lightbend, told TechRepublic. This may present a challenge to early adopters, as this technology is unlike the core characteristics of big data systems. This change will require data engineers to learn the skills of microservices developers. To utilize the technology, developers will also need to improve the way they handle data and account for latency, volume, transformation and integration requirements.
Despite these challenges, the capability to obtain fast data is integral for today’s businesses.
“To compete in the digital era, the necessity is rising for enterprises to use data faster,” the Lightbend report notes. “This need for speed is expanding beyond analytics to applications that adapt to changing conditions in real-time, personalize customer engagement and power the internet of everything.”
Lightbend is also partnering with IBM to build an integrated platform to advance cognitive solutions and artificial intelligence for businesses. The concerted effort will allow Java and Scala developers to easily build and deploy cognitive apps and AI both on-premises and in cloud environments.
Readiness Varies for Fast Data
The Lightbend survey reveals that when it comes to fast data, enterprises are at various points on the adoption curve. Brewer notes that there are two categories of companies ready for fast data adoption, with a third category emerging, TechRepublic reports.
The first category of companies utilizes batch processing for use cases like personalization, anomaly detection and targeted ads. To get the full value of this information, these companies should extract data in real time. The second category includes businesses in microservices environments that need to process their ever-increasing volumes of data with greater speed. The emerging subcategory is companies that want to use the technology to train models in real time in order to better meet their customers’ needs.
Moreover, the survey reveals that more than half of developers are choosing new frameworks and languages based on fast data requirements. With the proper tools, enterprises can prepare to embrace the technology and propel the adoption and growth of fast data systems.