Flink SQL in Action, Low latency decision for Bot and Flink goes Cloud Native

Bonjour à tous,

Nous avons le plaisir de vous recevoir chez Critéo le 14 novembre prochain pour 3 "Fast Data" talks avec Apache Flink:

• Fabian Hueske (dataArtisans) montrera Flink SQL en Action,
• Benjamin Fabre et Philippe Loulidi (DataDome) présenteront leur retour d'expérience sur la mise en place d'une stack Kafka/Flink à faible latence dans le cadre d'une solution de Bot Management,
• Pierre Bittner (WeeFin) donnera son retour d'XP sur l'utilisation de Flink avec les services managés d'AWS (EKS, Kinesis,.. ).

Merci beaucoup à Critéo de sponsoriser ce meetup et de nous héberger. Un espace networking sera disponible jusque 22h.

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Détails des présentations:

Flink SQL in Action par Fabian Hueske (@fhueske) - PMC member of @ApacheFlink - Co-Founder of @DataArtisans

Abstract:
Stream processing is rapidly adopted by the enterprise. While in the past, stream processing frameworks mostly provided Java or Scala-based APIs, stream processing with SQL is recently gaining a lot of attention because it makes stream processing accessible to non-programmers and significantly reduces the effort to solve common tasks.

About three years ago, the Apache Flink community started adding SQL support to process static and streaming data in a unified fashion. Today, Flink SQL powers production systems at Alibaba, Huawei, Lyft, and Uber.

In this talk, I will discuss the current state of Flink’s SQL support and explain the importance of Flink’s unified approach to process static and streaming data. Once the basics are covered, I will present common real-world use cases ranging from low-latency ETL to pattern detection and demonstrate how easily they can be addressed by Flink SQL.

Duration: ≈ 40 minutes

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Title: Engineering low latency decision loops for bot management

Speakers: Benjamin Fabre (@bfabre), DataDome (@data_dome) Cofounder & CTO, Philippe Loulidi, lead R&D engineer

Duration: ≈ 30 minutes

Abstract:
As bot threats become more and more complex and massively distributed, they are getting harder to detect. At DataDome, we analyze 2 billion hits per day to protect all the vulnerability endpoints of our customers' websites and applications. We would like to share our use case, on how we are doing event analysis using Flink/Kafka to detect new threats with low latency.

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Title: Flink <3 AWS

Speakers: Pierre Bittner (@BittnerPierre), WeeFin (@weefin_) Cofounder & CEO/CTO

Duration: ≈ 20 minutes

Abstract:
In this talk, we will give our REX of our recent move to AWS services for our Data Pipeline. As our engineering team were spending a lot of time to setup a resilient data stack on Mesos and Kubernetes, how we leverage on AWS managed service (EKS, Kinesis, Elasticsearch,... ), serverless and Flink to focus on business value and stay innovative.

WeeFin is a "Green FinTech" that give a sense to your investments
by assessing your environment and social impact.