Case Study: Tenable achieves reliable data platform observability with Monte Carlo

How Tenable Built a Reliable Data Platform at Terabyte Scale with Monte Carlo

Tenable Networks, a company that provides cybersecurity exposure management, faced the challenge of ensuring data quality and reliability at a massive terabyte scale for its next-generation data platform. Their existing manual approach to data quality testing was unsustainable, creating a monolithic codebase that consumed engineering time and failed to prevent pipeline incidents. They sought a solution to proactively monitor their data and maintain the integrity of their customer-facing reporting and machine learning algorithms, leading them to partner with the vendor Monte Carlo.

The solution was the implementation of Monte Carlo's data observability platform. Monte Carlo provided out-of-the-box monitoring for freshness, volume, and schema, along with the capability to create custom monitors as code for their unique needs. This allowed Tenable to formalize data contracts and gain proactive alerts on data issues. As a result, the team experienced fewer data issues and was able to detect pipeline breaks much faster than before, building greater trust in their data platform and ensuring reliable service for their customers.

Tenable Networks

Vinny Gilcreest

Senior Director of Engineering, Data and Analytics