Detecting Real-Time Financial Fraud with Cloudflow on Kubernetes
Easily Orchestrate Streaming Data Pipelines With Cloudflow
Have you ever received a notification from your bank about a questionable purchase, or had an online purchase blocked because of suspected fraud? As digital commerce continues to grow, financial fraud detection systems are evolving to provide more value and even predict fraudulent activity in real-time, and there is a lot going on behind the scenes.
Deploying a robust streaming data pipeline can be a daunting task when your company’s financial information is at risk. For starters, how do you ensure proper provisioning of resources? How do you preserve end-to-end application and data consistency? How do you make all of this work in the cloud with Kubernetes and avoid YAML hell? Answer: Cloudflow, a new open-source toolkit for simplifying the development, deployment, and operation of streaming data pipelines.
In this webinar, streaming systems expert, O’Reilly author, and Lightbend Principal Engineer Gerard Maas introduces you to Cloudflow. Together we will:
- Explore the Cloudflow API in action through a financial fraud detection application
- Learn how to assemble your own application blueprint and run it locally before deploying it–YAML free–to a Kubernetes cluster.
- Create your own streaming data pipeline and connect tools like Akka Streams, Apache Spark, and Apache Flink with Cloudflow.
Watch The Full Presentation (~60 Min)
More Resources To Enjoy
Check out these resources to get started with your journey with Cloudflow. If the time to move forward is right, you can schedule a demo with our experts below!
- Visit Cloudflow - get started with streaming apps on your local machine at https://cloudflow.io
- Read this white paper - Cloudflow: Accelerate Your Real-Time Streaming Journey
- Download a free O'Reilly eBook - Serving Machine Learning Models: A Guide to Architecture, Stream Processing Engines, and Frameworks