• 28 июня, четверг
  • Москва, 123112, Moscow, ul. Presnenskaya Naberezhnaya, 10, Tower on the Embankment, block C, 11 floor 123112, г. Москва, ул. Пресненская набережная, д. 10, Башня на Набережной, блок С, 11 этаж

Alibaba Tech Meetup #1

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86 дней назад
28 июня c 18:00 до 21:30
Москва
123112, Moscow, ul. Presnenskaya Naberezhnaya, 10, Tower on the Embankment, block C, 11 floor 123112, г. Москва, ул. Пресненская набережная, д. 10, Башня на Набережной, блок С, 11 этаж

Hi everyone! Welcome to the first Alibaba Tech Meetup in Moscow!

The event will take place Thursday 28 June in Alibaba Moscow Office. (Please don’t forget your passport/id to get inside). The language of the event is English.

This time we are discussing:
Cloud architecture — pitfalls and problems of the migration.
If something goes wrong in JVM, which internal mechanics would help you to find a root cause?
Data Pipelines. How to get from zero to cloud scale?

18:00 — 18:30 Registration and welcome coffee
18:30 — 19:15 Zen in the cloud
19:15 — 19:30 Coffee break
19:30 — 20:15 JVM Health Rhythm
20:15 — 20:30 Coffee break
20:30 — 21:15 Data Pipelines. From zero to cloud scale
 
Our speakers:
Fedor Morozov — Yandex Zen Engineer
Alexey Ragozin -  Deutsche Bank Solution Architect
Artem Pyanykh — Head of analytics at Toptal
 
Zen in the cloud by Fedor Morozov
Zen is a personal recommendation service provided by Yandex. At its core lies the recommender system — Java application deployed on a few hundred servers that provide personal feeds in dozens of languages. Some time ago we started a migration to Yandex internal cloud platform, in this talk I would like to discuss it with the following key points:
- Zen architecture and how it was affected by the cloud
- Problems we had to solve: orchestration, service discovery, load balancing
- Containerization and deploy automation
- Advantages and disadvantages of migration to the cloud
 
JVM Health Rhythm by Alexey Ragozin 
Java Virtual Machine is a very sophisticated system. Usually, it just
works and you can care less about all the magic behind the scene.
Though, if something goes wrong, understanding internal mechanics of
JVM would help you to find a root cause.

There is no lack in Java profilers both commercial and open source.
There are bunch of metrics typical Java profiler can show. But how to
distinguish healthy metrics from a symptom of the hidden problem?

We would walk through common metrics exposed by JVM and uncover what
patterns you should expect and what problem symptoms can manifest
themselves through these metrics.

 

Data Pipelines. From zero to cloud scale by Artem Pyanykh
Data is one of the most important assets that can give a competitive advantage to your business. Back then you would probably have to build your own Hadoop cluster which requires big investments and incurs significant maintenance costs. Luckily things have changed and now building a data processing pipeline can actually be quick, easy and fun thanks to awesome open-source libraries and cloud infrastructure!

In this talk, Artem will explain what are the main components of a data processing pipeline, show how to manage ETL tasks with an open-source tool called Luigi, discuss potential issues with resiliency and scalability of the solution, and how cloud services like Google Cloud Storage, Google BigQuery, and Google Dataflow can remedy them. He’ll conclude with an overview of operational costs for the system, both in terms of development and maintenance effort and service bills.

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