Kubernetes has become a cornerstone for managing containerized applications in the cloud. It simplifies the deployment, scaling, and operations of application containers, but the complexity of these systems requires robust observability to ensure their health and performance. AI and Generative AI are revolutionizing how we approach observability. This blog post will delve into how AI
In the rapidly evolving landscape of cloud-native infrastructure, developers and cloud operators face a myriad of challenges in ensuring effective observability. The dynamic nature of these environments, coupled with the prevalence of technologies like Kubernetes and the diversity of deployment models (public, private, and hybrid cloud), presents a complex observability landscape. Understanding and addressing these
What does it mean to be “cloud native”? Cloud-native infrastructure refers to the design, deployment, and management of IT resources that leverage cloud computing principles. It involves building and running applications that take full advantage of the dynamic, scalable, and distributed nature of cloud environments. Characteristics include microservices architecture, containerization (e.g., Docker), and orchestration tools
In today’s digital world, many services we rely on, like online shopping, social media, and streaming, run on complex software systems. When something goes wrong with these systems, it can affect thousands or even millions of users. Observability helps engineers understand how these systems are performing and quickly find and fix issues. This blog post