JUNE 16, 17:00 (Kyiv time)
Language: English
AWS meet-up
Where: Zoom
Streaming DynamoDB
DynamoDB is a serverless, autoscaling, NoSQL database from AWS. Its ability to scale on demand makes it a great use case for any workload that may have unpredictable bursts and fits in well with other Serverless architecture patterns. DynamoDB streams allow us to further decouple data writers and our event systems and thus help us scale our microservices.

During the event, we'll discuss how we can use DynamoDB Streams and Lambda together to build a serverless, high-throughput decoupled system at Just Eat Takeaway.

Ryan Cormack
About the speaker:
Ryan started his career in digital marketing before moving to software engineering. He's worked with AWS technologies for ten years and has recently started working with teams building full Serverless microservices and "breaking apart the monolith." Ryan has worked in various companies, from founding his startup to global companies like Just Eat. At Just Eat, he currently chairs the internal Lambda Guild. He enjoys working with .NET and Typescript and constantly learns more about AWS Serverless offerings.
What's on:
- An introduction to DynamoDB Streams
- How to use DynamoDB Streams with Lambda
- DynamoDB Streams usage for Event Carried State Transfer, Producer-Consumer Correctness, and scaling a decoupled Serverless system.
17:05 - 17:45
Tech Lead at Just Eat Takeaway
Cases of building modern Data Services in AWS Cloud, using Aurora PostgreSQL, Apache Spark, Snowflake, and AWS Glue
Vitalii Bondarenko
Head of Data & Analytics Centre of Excellence at Ciklum
About the speaker:
Vitalii Bondarenko has been designing data-centric systems for the last 20 years and has gained huge experience in OLTP, DW, and BI/ML platforms. During the last five years, Vitalii was involved as a Solution Architect in Cloud Data projects and has adopted different innovative approaches for Fast Data Processing and Machine Learning. Now, Vitalii's responsibility is to lead the Data and Analytics Centre of Excellence and build expertise in cloud data services.
What's on:
- AWS Data Platform overview: cases of building different types of data services and examples from real projects in AWS cloud
- Data Architecture design and implementation with Aurora PostgreSQL, Apache Spark, Snowflake, and AWS Glue technologies
- Case 1: Low latency data access
- Case 2: Cloud Data Analytics with DWH and Data Lake
- Case 3: ML in AWS Cloud
- Recap: Cloud Data Engineer: skillset and education path
    17:50 - 18:30
    Sign up if you are:

    - AWS developer;
    - Application developer;
    - Back-end developer;
    - Data engineer;
    - Data science engineer;
    - Data architect.
    Registration Form
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