case study / Marketing Technology / Advertising & Integrated data cloud solution

Advertising & Integrated data cloud solution

Delivering the effective programmatic media buying solutions.

Challenge

  • Re-architect its existing monolithic platform, in particular, build from scratch a single solution for managing data, media, and insights. A future product will be launched for direct clients’ usage to enable self-service.
  • Enhance existing analytics platform by adding the ability to provide low latency response based on near real-time data.
  • Improve existing monitoring solution to handle increasing data volume and load, in a short-term only for better performance metrics. Later extend the solution to automate signal processing to monitor changes and generate alerts if defined SLAs are violated.
  • Investigate, recover and stabilize existing solution for real-time user. segmentation. Reduce current hardware demands up to 50% and migrate to AWS.
  • Build a new streaming application used to enrich data from one stream with data from another. The future solution should be capable to process up to ~1m events per second.

Overview

Our client is a global programmatic media buying service with live operations in 50 countries, that builds software tools to deliver optimal return on its clients’ advertising goals. The company leverages high-load and big data having ~6B bid requests per day, ~100M targeted impressions per day an impressive ~8 PB datacenter storage.

Solution

  • Lohika implemented a new core platform based on microservice architecture using Spring Cloud, Mesos, and Marathon.
  • Lohika delivered a proof-of-concept for a new real-time solution based on Lambda architecture using Apache Spark.
  • Lohika implemented a new monitoring solution that included a query engine and streaming based on Apache Spark, mimic Graphite API that was successfully integrated with existing Grafana dashboards.
  • Lohika proposed to refactor existing Storm topology by parallelizing critical path that led to significantly increased topology throughput.
  • Lohika implemented a streaming application based on Apache Spark able to handle up to ~1m events per second.

Results

  • Delivered business critical components from architecture to deployment:
  • Lohika contributed valuable expertise on cutting edge technologies to achieve efficiency goals.
  • Lohika took ownership to provide domain experts not available on the client’s side.
  • Contributed valuable expertise on cutting edge technologies.

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