Day #24 - Monitoring- Essential tools and approaches.

Kubernetes monitoring helps you identify issues and proactively manage Kubernetes clusters. Effective monitoring for Kubernetes clusters makes it easier to manage your containerized workloads, by tracking uptime, utilization of cluster resources and interaction between cluster components.

Kubernetes monitoring allows cluster administrators and users to monitor the cluster and identify issues such as insufficient resources, failures, pods that are unable to start, or nodes that cannot join the cluster.

Monitoring in Kubernetes focuses on collecting metrics from clusters, nodes, and pods to analyze performance and detect anomalies.

Key Aspects of Kubernetes Monitoring

• Resource Usage: Track CPU, memory, disk, and network usage.
• Application Performance: Measure application health using metrics such as latency, throughput, and error rates.
• Cluster Health: Monitor control plane components (e.g., etcd, API server, scheduler).
• Event Monitoring: Capture Kubernetes events for insights into deployments, scaling, and pod failures.

Essential Monitoring Tools

Kubernetes is a complex environment, and containerized applications can be distributed across multiple environments. Monitoring solutions must be able to aggregate metrics from across the distributed environment, and deal with the ephemeral nature of containerized resources. The following are popular monitoring tools designed for a containerized environment.

1. Prometheus: Open-source metrics collection and alerting system.
2. Grafana: Visualization and dashboarding tool.
3. Kube-State-Metrics: Generates metrics about the state of Kubernetes objects.
4. Thanos: Highly available Prometheus setup with long-term storage.

What to Monitor

• Cluster monitoring – Keeps track of the health of an entire Kubernetes cluster. Helps you verify if nodes are functioning properly and at the right capacity, how many applications run on a node, and how the cluster as a whole utilizes resources.
• Pod monitoring – Keeps track of issues affecting individual pods, such as resource utilization of the pod, application metrics, and metrics related to replication or autoscaling of the pod.
• Deployment metrics – When using Prometheus, you can monitor Kubernetes deployments. This metric shows cluster CPU, Kube state, cAdvisor, and memory metrics.
• Ingress metrics – Monitoring ingress traffic can help identify and manage various issues. You can use controller-specific mechanisms to configure ingress controllers to track workload health and network traffic statistics.
• Persistent storage – Setting up monitoring for volume health enables Kubernetes to implement CSI. You can also use the external health monitor controller to monitor node failures.
• Control plane metrics – You should monitor schedulers, API servers, and controllers to track and visualize cluster performance for troubleshooting purposes.
• Node metrics – Monitoring CPU and memory for each Kubernetes node can help ensure they never run out. Several conditions describe the status of a running node, such as Ready, MemoryPressure, DiskPressure, OutOfDisk, and NetworkUnavailable.

Best Practices for Monitoring

1. Centralize Logs and Metrics: Use tools like Prometheus and Fluentd to centralize and process data effectively.
2. Automate Alerts: Set up Prometheus Alertmanager to automate notifications for critical issues.
3. Retain Historical Data: Use long-term storage solutions like Thanos for metrics and Elasticsearch for logs.
4. Leverage Labels: Use Kubernetes labels to organize logs and metrics for easier filtering.
5. Secure Data: Encrypt logs and metrics, especially when transferring them to external systems.
6. Monitor Control Plane: Always monitor the Kubernetes control plane for critical events and anomalies.

Will discuss more about this