Challenges in Kubernetes Monitoring

Kubernetes and container monitoring is critical to managing application performance, service uptime and troubleshooting. However, though Kubernetes dramatically simplifies application deployment in containers and across clouds, it also adds a new set of complexities for managing, securing and troubleshooting applications. Here are a few:

• Dynamic containers: Container-based applications are dynamic, and the monitoring challenge lies in navigating these dynamics. The life of containers is very short - it can live for any duration between 10 seconds to 5 minutes. This creates a high level of churn. Once a container dies, everything inside is gone. You cannot SSH or look at logs. Containers are great for operations as we can package and isolate applications to consistently deploy them everywhere, but at the same time, this makes them black boxes, which are hard to troubleshoot.
• Increased infrastructure complexity: Dynamic provisioning via Infrastructure as a Service, automated configuration management tools, and orchestration platforms like Kubernetes enable efficiency but also add to monitoring and troubleshooting complexity. Therefore, there is a need for a new approach to gain the visibility you need to deploy and manage cloud services.
• Microservices architecture: In addition to increased infrastructure complexity, applications are being designed using microservices, where the number of components is increased by an order of magnitude. Each service can be distributed across multiple instances, and containers move across your infrastructure as needed. Monitoring the Kubernetes orchestration state is key to understanding if Kubernetes is keeping all of the service instances up and running.
• Component explosion and scale requirements: When we adopt containerized architectures, the number of components and monitoring metrics grows exponentially. A monitoring system has to keep up with this explosion. With legacy application architectures, we knew how many instances we had of each service component and where they were located. This is no longer the case in a containerized architecture. Kubernetes adds multidimensional levels like cluster, node, namespace, or service, as well as cardinality. The different aggregations, or perspectives, that need to be monitored can be staggering in volume!

eG Enterprise helps mitigate these challenges!