What logs and metrics are most useful for Calico?

Monitoring Calico involves analyzing specific logs and metrics to ensure the effectiveness of network policies, performance, and security within Kubernetes clusters. Key logs include the Calico Node logs, Felix logs, Kubelet logs, and the Calico CNI plugin logs, while essential metrics encompass network throughput, error rates, and policy enforcement statistics.
Calico, Kubernetes, Network Policies, Logs, Metrics, Monitoring, Felix, CNI Plugin, Network Throughput
<?php // Example of fetching Calico metrics using cURL $url = "http://"; $ch = curl_init($url); curl_setopt($ch, CURLOPT_RETURNTRANSFER, true); $response = curl_exec($ch); curl_close($ch); // Decode the JSON response $metrics = json_decode($response, true); // Print some useful metrics echo "Network Throughput: " . $metrics['network']['throughput'] . "<br>"; echo "Error Rate: " . $metrics['network']['error_rate'] . "<br>"; echo "Policies Enforced: " . $metrics['policies']['enforced_count'] . "<br>"; ?>

Calico Kubernetes Network Policies Logs Metrics Monitoring Felix CNI Plugin Network Throughput

Related Questions

How do I avoid rehashing overhead with std::set in multithreaded code?

How do I find elements with custom comparators with std::set for embedded targets?

How do I erase elements while iterating with std::set for embedded targets?

How do I provide stable iteration order with std::unordered_map for large datasets?

How do I reserve capacity ahead of time with std::unordered_map for large datasets?

How do I erase elements while iterating with std::unordered_map in multithreaded code?

How do I provide stable iteration order with std::map for embedded targets?

How do I provide stable iteration order with std::map in multithreaded code?

How do I avoid rehashing overhead with std::map in performance-sensitive code?

How do I merge two containers efficiently with std::map for embedded targets?