Google Cloud platform

For cluster participants
  • percent30%

The third GDG Cloud Kharkiv meetup provides an overview of  the Google Cloud platform (GCP).

There will be two lectures from the best GCP experts in Ukraine: 


  • Artem Nikulchenko, Chief Software Architect in Cloud Works: Using Google Cloud Platform Tools for Big Data Processing and Analysis.⠀
  • Andrey Bereznikov, Customer Engineer at Google: Overview of the Features of the Google Cloud Platform. 


Don’t miss the opportunity to learn from experts at a special price.


As we want to gather the relevant community, participation in our meetups will be
charged in 2020:

  • «Early birds» — 100 UAH, until 19 February.
  • «Last moment» — 200 UAH, until 26 February. 

Students can use the promo code “student” during the registration to get a 50% discount. 

About lectures

Talk #1 — Overview of the Features of the Google Cloud Platform by Andrey Bereznikov. 

Despite the fact that cloud technologies have been used for a long time, even now many people have questions about how to start. This presentation will tell you what types of services Google Cloud provides, which groups they are divided into, in which cases they can be useful to you, and in which cases it is better to consider other options. The creation of a simple virtual infrastructure will also be demonstrated and described.


Talk #2 — Using Google Cloud Platform Tools for Big Data Processing and Analysis by Artem Nikulchenko.

Google Cloud Platform (GCP) provides lots of tools for different purposes, including computing, storing, pre-processing, processing, analysis,and visualization for Big Data. In fact, there are so many of those tools, and each of those tools is worth at least one separate one-hour session.Depending on the use-case, several of those tools can be combined into a powerful solution. In this session, we will try to focus on Data Processing use-cases only, and I hope that we will have enough time to discuss such tools as Dataprep, Datalab, Datastudio, BigQuery, CloudComposer, DataFusion, Dataflow, Cloud ML as well as several more. We will discuss differences between those tools, when to use each of those tools, and finally, we will finish with a small demo.