Systems | Development | Analytics | API | Testing

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Predicting 1st-Day Churn in Real-Time - MLOps Live #7 - With Product Madness (an Aristocrat co.)

Michael Leznik - Head of Data Science Matthieu Glotz - Data Scientist Yaron Haviv - CTO & Co-Founder We discuss how technology and new work processes can help the gaming and mobile app industries predict and mitigate 1st-day (or D0) user churn in real time — down to minutes and seconds using modern streaming data architectures such as KAPPA. Also, we explore feature engineering improvements to the RFM (Recency, Frequency, and Monetary) churn prediction framework: The Discrete Wavelet Transform (DWT).

Observability For Your Microservices Using Kong, Kubernetes, and Prometheus

In this video, Kevin Chen, Developer Advocate at Kong, will explain how to set up Prometheus monitoring with Kong Gateway to get black box metrics and observability for all of your services deployed on Kubernetes. This guide can also be applied to other solutions like StatsD, Datadog, Graphite, InfluxDB etc.

How to Properly Leverage Elasticsearch and User Behavior Analytics for API Security

Kibana and the rest of the ELK stack (Elasticsearch, Kibana, Logstash) is great for parsing and visualizing API logs for a variety of use cases. As an open-source project, it’s free to get started (you need to still factor in any compute and storage cost which is not cheap for analytics).

What is Serverless Computing?

The shift to cloud computing fundamentally changed the way software is built and consumed by developers. Multiple code snippets or functions are logically connected to form a complex application. Since the platform deals with one function at a time, and functions are the fundamental deployment units, this model is often called as Functions as a Service (FaaS).

How to Move from Basic to Advanced Marketing Analytics in Four Steps

Advanced marketing analytics can improve campaign relevance, increase customer lifetime value, accelerate insights, reduce acquisition costs, and drive ROI. But moving to advanced analytics requires a thoughtful investment in the right infrastructure for storing, tracking, and analyzing customer data, which can be daunting to companies that only have basic analytics capabilities.