How Playtika delivers large-scale predictions
in real-time with streaming endpoints
Download the Presentation On-demand
Learn how Playtika – a leader in the gaming-entertainment industry – deployed large-scale and real-time predictions while increasing successful model throughput by up to 50% and reduced latency and errors to 0 with streaming endpoints on cnvrg.io. In this webinar we will learn how cnvrg.io customer, Playtika, delivers an exceptional, personalized gameplay experience to over 10 million daily active users with real-time machine learning applications.
In this webinar we’ll be joined by special guest, Avi Gabay, Director of Architecture at Playtika, where he will discuss how he worked with cnvrg.io to optimize their high volume ML deployments using Apache Kafka and created adaptive game environments for millions of players. See how cnvrg.io helps to solve key MLOps problems and ML production scalability for Playtika with one click streaming endpoints.
What you’ll learn:
How to decide between Web Services vs. Kafka Streams for your ML models
The best way to manage high-volume data and real-time deployments
How to set up the ideal architecture for Producer/Consumer interface endpoint
How to leverage Apache Kafka and AWS Kinesis for producer/consumer interface
How to quickly update models in production with 0 downtime using Kubernetes and Apache Kafka automation
Learn how Playtika – a leader in the gaming-entertainment industry – deployed large-scale and real-time predictions while increasing successful model throughput by up to 50% and reduced latency and errors to 0 with streaming endpoints on cnvrg.io. In this webinar we will learn how cnvrg.io customer, Playtika, delivers an exceptional, personalized gameplay experience to over 10 million daily active users with real-time machine learning applications.
In this webinar we’ll be joined by special guest, Avi Gabay, Director of Architecture at Playtika, where he will discuss how he worked with cnvrg.io to optimize their high volume ML deployments using Apache Kafka and created adaptive game environments for millions of players. See how cnvrg.io helps to solve key MLOps problems and ML production scalability for Playtika with one click streaming endpoints.
What you’ll learn:
How to decide between Web Services vs. Kafka Streams for your ML models
The best way to manage high-volume data and real-time deployments
How to set up the ideal architecture for Producer/Consumer interface endpoint
How to leverage Apache Kafka and AWS Kinesis for producer/consumer interface
How to quickly update models in production with 0 downtime using Kubernetes and Apache Kafka automation