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Building a RESTful real-time analytics system with Pyramid

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Titel
Building a RESTful real-time analytics system with Pyramid
Serientitel
Teil
148
Anzahl der Teile
173
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CC-Namensnennung - keine kommerzielle Nutzung - Weitergabe unter gleichen Bedingungen 3.0 Unported:
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Identifikatoren
Herausgeber
Erscheinungsjahr2015
SpracheEnglisch
ProduktionsortBilbao, Euskadi, Spain

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Abstract
Andrii Chaichenko - Building a RESTful real-time analytics system with Pyramid CeleraOne tries to bring its vision to Big Data by developing a unique platform for real-time Big Data processing. The platform is capable of personalizing multi-channel user flows, right-in time targeting and analytics while seamlessly scaling to billions of page impression. It is currently tailored to the needs of content providers, but of course not limited to. - The platform’s architecture is based on four main layers: - Proxy/Distribution -- OpenResty/LUA for dynamic request forwarding - RESTful API -- several Python applications written using Pyramid web framework running under uWSGI server, which serve as an integration point for third party systems; - Analytics -- Python API for Big Data querying and distributed workers performing heavy data collection. - In-memory Engine -- CeleraOne’s NoSql database which provides both data storage and fast business logic. In the talk I would like to give insights on how we use Python in the architecture, which tools and technologies were chosen, and share experiences deploying and running the system in production.
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