Traditional observability tools built in C++, Java and Go often become part of the problem they're meant to solve, crashing under load, leaking memory during critical incidents, and introducing race conditions that corrupt data. Extremely high resource consumption leads to increased costs and complexity in managing infrastructure.

Rust offers a compelling alternative, providing memory safety without a garbage collector, which translates to more reliable and efficient observability systems. Coupled with its strong ecosystem for building high-performance data processing pipelines, Rust enables the creation of observability tools that are not only robust, highly performant and also cost-effective.

This session explains how we used rust to build a next-generation observability platform that addresses the shortcomings of existing solutions.

You will see real world examples on how Rust's unique features lead to significant improvements in reliability, performance, and cost-efficiency for observability systems.

Prabhat Sharma is the founder of OpenObserve, bringing extensive expertise in cloud computing, Kubernetes, and observability. His interests also encompass machine learning, liberal arts, economics, and systems architecture.