With 2023 drawing to a close, the final OpenObservability Talks of the year focused on what happened this year in open source, DevOps, observability and more, with an eye towards the future. I was delighted to be joined by a special guest, Kelsey Hightower, a renowned figure in the tech community, especially known for his contributions to the Kubernetes ecosystem.

For businesses reliant on customers’ positive digital experiences to achieve their goals, the seamless operation of cloud applications and infrastructure is paramount for financial success. Observability holds a pivotal role in modern enterprises, offering critical insights into your IT system’s health and performance. However, persistent issues of complexity and high costs have plagued the observability landscape.

As we continue to navigate the ongoing evolution of the observability landscape, Logz.io is constantly striving to provide our customers with the advanced platform capabilities needed to make sense of their increasingly complex environments. Sometimes that means taking a new approach to long-standing practices.

As applications in the cloud become more distributed and complex, the Mean Time To Resolution (MTTR) for production issues is getting longer. Modern systems are built with hundreds of distinct, ephemeral, and interconnected cloud components, which can make it exceptionally hard for engineers to understand the current state of their applications, what problems are impacting customers, and why those problems are occurring.

Years before founding Logz.io, I was a software engineer, working with various tools to ensure my products and services performed correctly. There were few tools I dreaded using more than application performance management (APM), and I know that I’m not alone. I hated traditional APM. It’s heavy. It’s hard to implement. It’s expensive. It takes a very long time to derive business value.