Building a RESTful real-time analytics system with Pyramid
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| Title | Building a RESTful real-time analytics system with Pyramid |
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| Part Number | 148 |
| Number of Parts | 173 |
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| License | You are free to use, adapt and copy, distribute and transmit the work or content in adapted or unchanged form for any legal and non-commercial purpose as long as the work is attributed to the author in the manner specified by the author or licensor and the work or content is shared also in adapted form only under the conditions of this license. |
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| Production Place | Bilbao, 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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