Building on Quicksand – MicroServices Architecture

Micro services are increasingly used to tackle complexity of addressing business requirements. Understanding MicroServices architecture needs some understanding trade off involved in distributed systems. In the talk, I’ve tried to highlight how the model shifts from strong consistency to eventual consistency in Micro services. I will talk about some interesting techniques I’ve used in projects to tackle challenges posed by distributed components. I will also talk about various consistency models( viz. Read My Writes, Consistent Prefix) which developers/architects can used to make interesting tradeoffs. This is talk is going to be on architectural patterns and not related to any specific technology.


Shripad-Agashe-75Shripad Agashe has more than 17 years of IT experience in executing projects for a broad range of business problems for various large organizations including several Fortune 500 companies. He specializes in Performance and Scalability of compute intensive applications…

GR8 Road to #fame – Building & scaling a live streaming mobile platform

#fame is the India’s first mobile only Live streaming mobile platform. The application is backed by the Micro service based architecture using Grails and Java based Frameworks. So I am going to talk about the how we architect the live streaming platform and how quickly we went bigger in terms of user base & traffic. What proactive measures were taken to make the application scalable, with over 5 million installs, 1 million registered users and counting.

Areas covered during the talk:
● What is Live stream?
● Some video domain terminology like RTSP, HLS, DVR, Player, Transcoding, Adaptive bitrate etc
● Architecture of the application
● Challenges faced while scaling the application
● Load stats and success stories
● How we used for generating recommendations: Recommendation system on Grails
● Use of hadoop and spark for realtime processing

Key takeaways:
● Better understanding of Video domain based and live streaming applications
● Getting started with Micro services
● How one can quickly move away from Monolith
● Spending less and still not using the Monolith approach
● How one can scale the application quickly to handle load
● On demand scaling : Auto scaling
● etc…


Rishabh-Jain-75Harkesh-Kumar-75Rishabh Jain is a Big Data Consultant for #Fame. Harkesh Kumar is the Lead Developer for #Fame ….