Case Study: Intent Media achieves 99% log-noise reduction and real-time visibility with Logz.io

How Intent Media Made Sense of 500 GB of Log Data Using Logz.io

Intent Media is a travel-tech company that uses machine learning to optimize revenue per visitor for hundreds of airline, hotel and travel partners worldwide. As its architecture grew across EC2 and ECS, so did log volume and management overhead: an in-house ELK deployment became costly to maintain and generated noisy, hard-to-analyze data (peaking at ~500 GB/day), so the team looked for a robust hosted ELK solution.

By moving to Logz.io and shipping logs with Filebeat, Intent Media quickly centralized and cleaned its log pipeline with help parsing multiline Java exceptions, setting alerts, using Live Tail and applying Logz.io’s machine-learning insights. The result: daily intake dropped from ~500 GB to ~5 GB, over 30 developers now use the platform, signal-to-noise improved dramatically (about 99% noise reduction per the company), and teams can detect and resolve errors in real time across siloed sub-accounts.

Intent Media

Rob Park

VP of Engineering