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.
In the dynamic landscape of microservices and cloud-native architectures, the role of service meshes has become increasingly crucial. These programmable frameworks empower users to seamlessly connect, secure, and observe their microservices, relieving them of the complexities associated with these critical tasks within their applications. Istio, a leading service mesh project, has been at the forefront of this evolution since its inception in 2017.
Logz.io is excited to announce Service Map, a new way to visualize the data flow, dependencies, and critical performance metrics throughout your microservices architecture, which makes it easy to gather critical troubleshooting context as you investigate production issues.
Here at Logz.io, we realize Kubernetes is the most common infrastructure component that organizations are running on to keep their applications going. In return, we’ve made a big investment to support Kubernetes properly and give customers the tools they need to investigate and troubleshoot any issues that arise.
If you missed KubeCon North America 2023 in Chicago, or you were there and spent more time in the “hallway tracks,” you may have missed some of the big news that came out of the show. We covered the big happenings in the open source cloud native and observability realm in the latest episode of OpenObservability Talks!
When things go wrong, we’d all love the ability to go back in time, return things to the way they were, and fix whatever issues pop up at the start so they never happen in the first place. This is no different when maintaining complex microservices-based architectures. With any complex system, things are bound to go wrong from time to time.
Do you find yourself lying awake late at night, worried that your greatest observability fears will materialize as one of the most horrific specters of Kubernetes-driven chaos reaches up through your mattress to consume your very soul?
