Many industries today strive to deliver better services by analyzing real-time streaming data, rather than relying on more traditional historical data sources. Open source technologies like Apache Kafka, Apache Spark, and TensorFlow—all spearheaded by leading social media companies—play a central role in the migration towards real-time streaming data. By leveraging these powerful technologies, and using architecture designed to process data at scale, Klarrio helps companies to build cloud-enabled data analytics platforms. “Klarrio is a one-stop shop for integrating solutions that are cloud agnostic, cost-effective, and custom designed,” says Dirk Van de Poel, CPO and co-founder at Klarrio.
As a vendor-neutral solution integrator, Klarrio advises clients towards a public cloud or an on-premise environment, based on their use-cases, volume of data, and the demand for real-time actionable information. While the company has several successes in deploying data analytics platforms hosted on Amazon Web Services, Google Cloud, and Microsoft Azure, it also has the unique ability to implement the analytics platform in on-premise data centers, or a combination of both (hybrid cloud). Klarrio’s cutting-edge solutions provide agility, elasticity, and portability, and a standardized architecture ready to power future use-cases with accurate real-time data.
Powered by a cloud-agnostic platform, our clients achieve a state-of-the-art and future-proof analytics solution that is free of vendor lock-in
“We leverage Apache Kafka’s publish-subscribe messaging principle that allows multiple apps to use a data source seamlessly,” says Van de Poel. Kafka’s scalable events-based architecture allows any number of apps and users to subscribe and receive events. This architecture, in combination with containerized apps and modules, makes the analytics platform modular and extensible. As the volume of data increases, newer versions of apps and new use cases can be added on top of the existing architecture and data streams, allowing millions of messages to be analyzed per second. Powered by a cloud-agnostic platform, clients achieve a state-of-the-art and future-proof analytics solution that is free of vendor lock-in. In this way, the young company with more than 120 years of collective R&D experience supplants inefficient, expensive off-the-shelf solutions with cloud-native, distributed open source technology.
To ensure the best outcome, Klarrio begins the client engagement process by defining the business problem, collecting sample data, and running analytics through its distributed architecture on the public cloud. Through this proof-of-concept process, the company’s data scientists assess the potential added value of a distributed analytics solution. The data is then taken to the client to discuss how the client’s existing business systems and databases can be cleanly and efficiently integrated into the platform.
For example, Klarrio built a solution for the Dutch telecommunications company KPN to enable the smart mobility project Talking Traffic. This project required a data and analytics platform to ingest mobility data from sources throughout the entire Netherlands, process and analyze it, and distribute traffic information to millions of commuters, all in real-time. Various partners run their advanced analytics models on top of this platform, which today runs in production.
Klarrio provides round-the-clock support for their clients via its teams in Australia, Belgium, Germany, Netherlands, and U.S.. As the year ends, Van de Poel looks forward to further growth of the Klarrio team, and the deepening of its expertise in distributed cloud-native data processing and advanced analytics.
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