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"With AWS Lambda, our various engineering teams can tap into a parallel data stream to create microservices independently from the main analytics application. It helps us get new services to our customers faster. For a startup, faster time to market is key", Mohit Dilawari, Director of Engineering
The Challenge
The Solution
The Benefits
The Challenge
- Supports pipeline with billions of data points uploaded every day from different mobile applications running Localytics analytics software.
- Engineering team needed to access subsets of data for creating new services, but this led to additional capacity planning, utilization monitoring, and infrastructure management.
- Platform team wanted to enable self-service for engineering teams.
The Solution
- Uses AWS to send about 100 billion data points monthly through Elastic Load Balancing to Amazon Simple Queue Service, then to Amazon Elastic Compute Cloud, and finally into an Amazon Kinesis stream.
- For each new feature of the marketing software, a new microservice using AWS Lambda is created to access the Amazon Kinesis data stream. Each microservice can access the data stream in parallel with others.
The Benefits
- Decouples product engineering efforts from the platform analytics pipeline, enabling creation of new microservices to access data stream without the need to be bundled with the main analytics application.
- Eliminates the need to provision and manage infrastructure to run each microservice .
- Lambda automatically scales up and down with load, processing tens of billions of data points monthly.
- Speeds time to market for new customer services, since each feature is a new microservice that can run and scale independently of every other microservice.
