The advantages of Grafana Kubernetes Monitoring

Grafana Kubernetes Monitoring provides the following advantages:

Priority issues at forefront

The Kubernetes Overview page provides a high-level look at counts for Kubernetes objects, CPU and memory usage by Cluster, and firing alerts for containers and Pods. You can filter this view by Clusters and namespaces, then identify issues that require attention to begin your problem solving.

Real-time alerts

Real-time alerts inform you as soon as problems begin. You can jump from alert to runbook for a quick solution, create your own alerts, and copy a built-in alert to customize it.

Logs and metrics correlation

While Kubernetes doesn’t provide a native storage solution for logs, Kubernetes Monitoring uses Grafana Loki as its log aggregator. Since Loki and Prometheus share labels, you can correlate metrics and logs to identify root causes faster without configuring and using multiple technologies.

Early error detection

You can use built-in alerting for anomolies such as CPU throttling to learn which settings need fine tuning. Network bandwidth and saturation is available by object. The time range selector in Kubernetes Monitoring provides a look into the history of an object, which reveals patterns such as spikes. Outlier Pod detection can uncover Pods with CPU usage differences that may lead to issues.

Cost visibility and management

Nodes, load balancers, and Persistent Volumes usually incur a separate cost from your provider, making it important to keep track of them. Auto-scaling architectures let you adapt in real-time to changing demand, but can lead to rapidly spiraling costs. Kubernetes Monitoring provides visibility into these costs to identify where cost can be reduced. With cost prediction, you can view potential, future costs.

Resource efficiency management

You can mitigate the threat of an unstable infrastructure by monitoring resource usage to:

• Ensure that there are enough allocated resources and decrease the risk of Pod eviction, as well as prevent performance degradation of your microservices and applications.
• Eliminate unused or stranded resources.

Then you can make scheduling adjustments, such as setting affinities and anti-affinities, to enhance performance and reliability.

Resource usage forecasts

By looking at a prediction of resource usage, you can better forecast for a project or activity.