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Data runs business. We’ve been told this now immutable truth countless times throughout the early dawn and later progression of the information age. The entire act of so-called digital transformation involves processes designed to encode, quantity, manage and process workplace functions, events and objects into digital values in the shape of data.
Bricks-and-mortar headquarters buildings housing office environments are still an option, but in a world where jobs and tasks can be expressed in terms of numerical values - and in a world where those same work functions can be explained and rationalized in terms of algorithmic logic - the presence of data in the operational fabric of any organization is fundamental to its ability to operate.
Data becomes a commodity
As with all services that find a nestle perfectly (or near perfectly) into place, efficiently created, ingested, transmitted, analyzed, managed, stored and secured data moves towards being a core commodity within this notion of digital business that we are painting here. Not to downgrade its value with this term, commoditization in this sense means that data can be deployed as ‘regular’ form (as in fries, coffee or cola), enhanced and augmented, accelerated and sped up, slowed down or even rechanneled into new pipelines, new services or new applications.
Working very much at the sped-up end of the data spectrum is data streaming platform company Confluent, Inc. Now working to enable new methods of creating data streams for data pipelines, real-time applications and analytics, the company has brought forward Confluent Cloud for Apache Flink. This is a fully managed service for Apache Flink (a unified stream processing framework that can process data subject to iterative changing algorithms across multiple microprocessors) that enables organizations to process data in real-time and create high-quality, reusable data streams.
Organizations across every vertical are obviously under pressure to make profits, act sustainably and keep customers happy. The technology proposition on offer here is designed to streamline business operations for technology use cases such as fraud detection, predictive maintenance as well as real-time inventory and supply chain management functions.
Act on data now, why wait?
Confluent chief product officer Shaun Clowes suggests that Stream processing is a critical part of bringing these real-time experiences to life because it enables organizations to act on data as it arrives rather than waiting to process it in batches when the data is often already stale and out-of-date.
“Stream processing allows organizations to transform raw streams of data into powerful insights,” said Shaun Clowes, chief product officer at Confluent. “Flink’s high-performance, low latency and strong community make it the best choice for developers to use for stream processing. With Kafka and Flink fully integrated in a unified platform, Confluent removes the technical barriers and provides the necessary tools so organizations can focus on innovating instead of infrastructure management.”
Confluent Cloud for Apache Flink is available across Amazon AWS, Google Cloud, and Microsoft Azure. Backed by Confluent’s 99.99% uptime SLA, Confluent’s cloud-native service for Flink enables reliable, serverless stream processing from the leading Kafka and Flink experts.
What is a reusable data stream?
Not always considered as part of the whole effort to move towards technology platforms that deliver on Environmental, Social & government (ESG) concerns, the notion of a reusable data stream still has an essential place in the mission to enable zero carbon computing. It also has a significant role in the wider mission to enable so-called green coding and eradicate ‘code bloat’ i.e. software application code that is built to process data with more lines and procedures than necessarily needed, sometimes written in an inefficient software language for the task at hand.
As the compute layer in the data streaming infrastructure, stream processing helps teams filter, join and enrich data in real-time to make it more usable and valuable for sharing with downstream applications and systems. This creates high-quality data streams that can be reused for multiple projects and provides improved agility, data consistency and cost savings compared to traditional batch processing solutions. That, in a nutshell, is cleaner code and greener data.
For its part in this essential IT infrastructure story, Confluent of course claims that Apache Flink is the de facto stream processing standard. Spoiler alert, yes of course the company originally created the open source entity of project before its commercially supported iterations. Today we can say that Apache Flink is relied upon by companies including AirBnB, Uber, Netflix and TikTok to support mission-critical streaming workloads.
According to Clowes and team, Flink’s popularity has surged and in 2023, it was downloaded (by developers and data engineers) almost one million times. As the industry’s only cloud-native, serverless Flink offering, he says that Confluent Cloud for Apache Flink enables customers to easily build high-quality, reusable data streams to power all of their real-time applications and analytics needs.
“Apache Flink is becoming a prominent stream processing framework in this shift towards real-time insights,” said Stewart Bond, research VP for data integration and data intelligence software at IDC. “Flink and Apache Kafka are commonly used together for real-time data processing, but differing data formats and inconsistent schemas can cause integration challenges and hinder the quality of streaming data for downstream systems and consumers. A fully managed, unified Kafka and Flink platform with integrated monitoring, security, and governance capabilities can provide organizations with a seamless and efficient way to ensure high-quality and consistent data streams to fuel real-time applications and use cases, while reducing operational burdens and costs.”
Apache Flink enables customers to build streaming data pipelines, event-driven applications and real-time analytics to power use cases like personalized recommendations, dynamic pricing and anomaly detection. Confluent Cloud for Apache Flink is intended to offer an easier way for companies to get started with these stream processing use cases.
"Conditions in the automotive logistics industry can change rapidly, requiring immediate action to address delays, reroute vehicles, and update systems and customers," said Jeffrey Jennings, senior consultant for data & integration services at automotive logistics platform company Acertus. “Confluent's serverless Flink service will enable us to instantly and efficiently transform, integrate and enrich massive volumes of data in our transportation management system, providing real-time visibility into the status and location of vehicles for both systems and customers."
Windowing, not on Windows
Flink can analyze streams of data and immediately trigger an alert when a particular event or pattern happens in event-driven applications. Time is often a critical part of this equation and Flink offers advanced windowing capabilities (virtual time window periods that give customers control over how data is grouped for processing) – for example, analyzing transactions over a specific time-period for anomalies.
Confluent Cloud for Apache Flink is now generally available on all three major clouds. Unlike its batch counterparts, Flink can analyze real-time data streams to generate insights and help businesses accelerate decision-making. Flink can process very large amounts of data quickly with sub-second latency and be enable data scientists and developers to use it for interactive queries and advanced pattern recognition functions.
If data has become something of a commodity or utility, then being able to treat it differently based on the needs thrown up by different use cases for different types of digital tasks is a natural progression. But of course, this is data in its potentially smallest possible grade of size (singular datum even) that needs to be aggregated to massive data resources from data lakes to data warehouses to databases in every shape and size including the new darling breed of vector database technologies. Confluent integrates with leading database vendors, such as Elastic, Pinecone, Rockset, Singlestore and Zilliz to simplify and accelerate the development of generative AI initiatives further.
Data has increased its importance, its cadence, its variety and its speed such that much of our continuous computing always-on world now needs real-time data and stream processing. This is massive speedy stuff. As they say in Apache territory, Flink and you’ll miss it.
