Data science and behaviour analysis


An intelligence-driven data science and behaviour change company which turns motion data into contextual insights and using behavioural change techniques to personalize engagement for safer and sustainable mobility and wellbeing experiences.


The company experienced bottlenecks in their existing data architecture and was in need of scaling and optimising its platform to collect and analyse data from mobile devices.


The company had built an AWS-based cloud platform to process data from their mobile application SDK by collecting smartphone sensor data.  This platform was designed according to a Lambda architecture with both a speed layer for real time processing and a batch layer for daily processing of sensor data. While the platform leverages cloud computing and modern technologies, a number of performance and scalability bottlenecks still remained and made that only a limited number of users where supported.  

Klarrio analysed the cloud architecture and conducted load tests to identify the performance bottlenecks. Over a short period of time, the most important bottlenecks were resolved and scalability improved with a factor of 50 at the same AWS cloud infrastructure cost.

The Technology behind

  • Scala
  • Apache Spark
  • Kafka
  • Elasticsearch

“Things work out best for those who make the best of how things work out.”

— John Wooden


Scale | Improved messaging layer from 4K to 200K supported persistent connections.

Cost | AWS cost remained the same despite the increase in scalability.

Speed | deployed within 3 months.

From 4K to 200K persistent connections
more concurrent connections
difference in cloud infrastructure costs

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Big Data engineering. Data science. Data Analytics. Site Reliability Engineering. Consulting. And customized Open Source projects for companies of all sizes. Learn more about what Klarrio can do for you today.

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