This documentation provides a comprehensive guide for monitoring the Kubernetes-Client/Csharp project in a production environment. The focus will be on leveraging built-in metrics, logging, and observability principles relevant to Kubernetes applications.

1. Metrics Collection

Metrics are essential for determining the health, performance, and resource utilization of applications running in Kubernetes.

A. Built-in Metrics Using HttpClient

Kubernetes-Client/Csharp utilizes the built-in metrics available in the HttpClient provided by .NET, using the System.Diagnostics.DiagnosticsSource. This allows for efficient tracking of HTTP requests and responses, essential for diagnosing performance issues or resource bottlenecks.

Code Example:

To integrate metrics collection, ensure your application is set up to automatically record metrics. Here’s an example showcasing how to set up and access these metrics:

using System;
using System.Diagnostics;

public class MetricsExample
{
    private static readonly HttpClient _client = new HttpClient();

    public async Task FetchDataAsync(string requestUrl)
    {
        var request = new HttpRequestMessage(HttpMethod.Get, requestUrl);

        // Track metrics for the HTTP request
        var stopwatch = new Stopwatch();
        stopwatch.Start();

        var response = await _client.SendAsync(request);
        stopwatch.Stop();

        // log metrics
        LogMetrics(response.StatusCode, stopwatch.ElapsedMilliseconds);
    }

    private void LogMetrics(HttpStatusCode statusCode, long duration)
    {
        Console.WriteLine($"Request completed with status: {statusCode}, duration: {duration}ms");
    }
}

For further information on these built-in metrics, refer to Built-in metrics in System.Net.

B. Custom Metrics Collection and Exposure

While the Kubernetes client does not dictate how metrics are consumed or exposed, it allows developers to implement their own solutions. A common approach is to use a metrics server or a time-series database like Prometheus.

Example of Metrics Exposure Using Prometheus

To expose metrics for collection:

1. Add the Prometheus client NuGet package to your project:

dotnet add package prometheus-net

2. Implement the metrics in your application:

using Prometheus;

public class MetricsServer
{
    private static readonly Counter requestCounter = Metrics.CreateCounter("http_requests_total", "Total number of HTTP requests.");
    
    public void Start()
    {
        // Start the metrics server
        var server = new MetricServer(port: 1234);
        server.Start();
    }

    public void TrackRequest()
    {
        requestCounter.Inc();
    }
}

Expose your metrics endpoint for scraping by Prometheus.

Refer to Metrics Collection Documentation for comprehensive information.

2. Logging

Logging critical events and operational details is fundamental in monitoring applications. The Kubernetes-Client/Csharp allows you to configure logging formats and backends as per your needs.

A. Example of Structured Logging

Use a structured logging library like Serilog or NLog:

using Serilog;

public class LoggingExample
{
    public LoggingExample()
    {
        Log.Logger = new LoggerConfiguration()
            .MinimumLevel.Debug()
            .WriteTo.Console()
            .CreateLogger();
    }

    public void LogInformation(string message)
    {
        Log.Information(message);
    }
}

B. Error Handling and Logging

Properly logging errors where they occur will help in diagnosing issues quickly. Here’s an outline for logging exceptions:

public async Task ExecuteWithLoggingAsync(Func<Task> action)
{
    try
    {
        await action();
    }
    catch (Exception ex)
    {
        Log.Error(ex, "An error occurred.");
    }
}

3. Observability Integration

Implementing observability standards will provide insights into the application’s state and help detect anomalies early.

A. Use of OpenTelemetry

OpenTelemetry can be used to gather telemetry data (logs, metrics, traces) from applications.

Example Setup for OpenTelemetry

1. Add OpenTelemetry packages to your project:

dotnet add package OpenTelemetry
dotnet add package OpenTelemetry.Exporter.Console

2. Configure OpenTelemetry:

using OpenTelemetry;
using OpenTelemetry.Trace;

public class TracingSetup
{
    public void InitializeTracing()
    {
        Sdk.CreateTracerProviderBuilder()
            .AddSource("my-company-name.HelloWorld")
            .AddConsoleExporter()
            .Build();
    }
}

For more detailed configuration and integration, refer to the respective documentation of OpenTelemetry.

Conclusion

Monitoring your Kubernetes-Client/Csharp application in production involves strategically implementing metrics collection, logging, and observability standards. Taking advantage of built-in .NET capabilities, along with popular tools like Prometheus and OpenTelemetry, will greatly support the reliability and performance of your application.

For further reading, refer to:

• Built-in metrics in System.Net
• Metrics Collection Documentation