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This article mainly explains "how to monitor the container environment in which Kubernetes runs". The content in the article is simple and clear, and it is easy to learn and understand. Please follow the editor's train of thought to study and learn "how to monitor the container environment in which Kubernetes runs".

1. Centralize logs and metrics. Orchestrating your containerized services and workloads through Kubernetes will bring order, but keep in mind that your environment is still fragmented. If you centralize your logs and metrics, it will be much easier to deal with.

two。 Consider the ephemeral container. The beauty of container choreography is that it can easily start, stop, kill, and clean the container in a short time. However, monitoring them may not be easy. Even if the service is in progress, you still need to debug the problem and monitor cluster activity. The trick is to get it before the logs and metrics disappear. If you don't, your indicator looks more like the one on the left than the one on the right.

3. Simplify, simplify, simplify. For all mobile parts of the container environment (services, API, containers, orchestration tools), you need to monitor without introducing unnecessary complexity. Instead of using various monitoring agents to extend the container, you need to abstract monitoring and management tools from the content you monitor and manage. This will also help your engineers focus on building and delivering software rather than on the operation and maintenance delivery platform.

4. Clearly monitor each floor. You need to collect logs and monitor the various layers of the environment for errors, failures, and performance problems (pod\ container and controller manager). For example, you need to be able to troubleshoot pod, make sure the container is running properly, and collect runtime metrics in the controller manager.

5. Ensure data consistency across tiers. In order to debug quickly and accurately, you need to ensure data consistency across all layers in the container environment. Such as accurate timestamps, consistent units of measurement (such as milliseconds and seconds), and collecting a common set of metrics and logs in applications and components will help you troubleshoot and debug all layers quickly and accurately.

The way to accomplish these to-dos in a simple and direct way is to monitor the containers in the Kubernetes environment without touching the application containers. This can be achieved by introducing DaemonSet or sidecar into a Kubernetes environment that is juxtaposed with containerized services and includes logging and metrics collection agents. Deployment using this approach ensures consistency in data collection, * reduces the changes required by the application container, and, most importantly, eliminates the possibility of blind selection in a production environment.

Several implementation methods include:

1. Use DaemonSet with Fluentd logging agent (this will provide you with logging rather than metrics). If you already have a configured ELK cluster, this is an option.

two。 Use DaemonSet or sidecar with Prometheus metrics agents (CoreOS does a great job of integrating Prometheus and Kubernetes). Running Prometheus on your Kubernetes cluster will provide you with metrics detection, queries, and alerts.

3. Many metrics and performance monitoring tools, including Heapster, DataDog, cAdvisor, New Relic, Weave / VMware, also provide DaemonSet or sidecar options for Kubernetes monitoring.

Thank you for reading, the above is the content of "how to monitor the container environment running Kubernetes". After the study of this article, I believe you have a deeper understanding of how to monitor the container environment running Kubernetes, and the specific use needs to be verified in practice. Here is, the editor will push for you more related knowledge points of the article, welcome to follow!

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