As an ISV and SaaS provider, understanding the users and their interactions with your product in real-time is beneficial to analyse the experience delivered when onboarding and as well as during regular use. Such insights in real-time aid the efforts to retain customers, acquire new ones and measure effectiveness of experiments.
In this session, we will cover data-streaming services available on AWS that will help you implement real-time analytics. We will discuss the features of relevant AWS services and step through the characteristics to help you choose which service to use and when. Also, we will cover how to get started to build real-time analytics applications. In this session you will also hear from Anita Miller, Software Engineer and Tim Cuthbertson, Senior Staff Software Engineer from Zendesk. With a global infrastructure spanning multiple, isolated production environments, hear how Zendesk powers real-time analytics and cross-product integrations with Amazon Kafka. Also, learn how their team built a globally interconnected event bus using a mix of self-managed Kafka clusters and Amazon MSK.
What you will learn:
- Features of different AWS streaming data services
- What are the use cases for each AWS service
- Different architecture pattern to build real-time analytics application
Data engineer, Architect, Tech Lead, Developer, CTO
Amazon Kinesis Data Streams, Amazon Managed Streaming for Apache Kafka (Amazon MSK), Amazon Kinesis Data Firehose and Amazon Kinesis Data Analytics
- Masudur Rahaman Sayem, Analytics Specialist Solutions Architect, AWS
- Tim Cuthbertson, Senior Staff Software Engineer, Zendesk
- Anita Miller, Software Engineer, Zendesk