☁️ Introduction

Full stack .NET applications, with a backend (ASP.NET Core), frontend (React, Angular, or Blazor), and cloud services, require robust monitoring and logging for:

Detecting errors and exceptions

Tracking performance and latency

Auditing user activity

Proactively alerting on issues

Cloud environments provide scalable tools to collect, analyze, and visualize logs and metrics.

🧩 1. Logging in ASP.NET Core

.NET Core has a built-in logging abstraction: ILogger. It supports multiple providers like Console, Debug, File, and Cloud providers.

Example: Configure Logging in Program.cs

var builder = WebApplication.CreateBuilder(args);

builder.Logging.ClearProviders();

builder.Logging.AddConsole();

builder.Logging.AddDebug();

builder.Logging.AddAzureWebAppDiagnostics(); // Logs to Azure if deployed

var app = builder.Build();

app.MapGet("/", (ILogger<Program> logger) =>

{

logger.LogInformation("Request received at {Time}", DateTime.UtcNow);

return "Hello World!";

});

app.Run();

✅ Key Points:

Use structured logging ({Placeholder}) instead of string concatenation

Use different log levels: Trace, Debug, Information, Warning, Error, Critical

Log enough context (user ID, request ID, correlation ID)

📦 2. Centralized Logging with Cloud Services

Azure Options:

Azure Monitor / Application Insights:

Automatically collects requests, dependencies, exceptions, and performance metrics

Supports distributed tracing for full stack apps

Log Analytics: Query logs using Kusto Query Language (KQL)

Example: Add Application Insights

dotnet add package Microsoft.ApplicationInsights.AspNetCore

In Program.cs:

builder.Services.AddApplicationInsightsTelemetry(builder.Configuration["ApplicationInsights:InstrumentationKey"]);

Then track custom events or exceptions:

var telemetry = app.Services.GetRequiredService<TelemetryClient>();

telemetry.TrackEvent("CustomEvent");

telemetry.TrackException(new Exception("Test exception"));

💡 Benefits:

Correlates backend API calls with frontend requests

Detects performance bottlenecks

Provides alerts and dashboards

🔄 3. Logging from the Frontend

Frontend logs are also critical, especially for SPAs:

Use console logging during development

Send client-side logs to backend using a logging API

Use Application Insights JavaScript SDK for monitoring:

import { ApplicationInsights } from '@microsoft/applicationinsights-web';

const appInsights = new ApplicationInsights({

config: {

instrumentationKey: "<YOUR_KEY>"

}

});

appInsights.loadAppInsights();

appInsights.trackPageView();

appInsights.trackException({ error: new Error("Frontend error") });

✅ This allows you to correlate frontend errors with backend logs.

📊 4. Monitoring Performance Metrics

Monitoring is as important as logging:

Key Metrics to Track:

Backend API:

Request count & duration

HTTP status codes (4xx, 5xx)

Database query performance

Memory and CPU usage

Frontend:

Page load times

Resource load failures

SPA routing performance

Database / Cloud Services:

Connection pool usage

Query latency

Storage capacity

Tools:

Azure Monitor for full-stack metrics

Application Insights dashboards

Prometheus + Grafana (for Kubernetes deployments)

🚨 5. Setting Up Alerts

Alerts help you proactively detect issues:

Define thresholds, e.g., Server response time > 1s or HTTP 500 > 5/min

Use Azure Monitor alerts or Application Insights alert rules

Integrate with Teams, Slack, or email for notifications

Example: Alert when 500 Internal Server Error rate exceeds 1%

🧠 6. Distributed Tracing

Full stack apps often involve multiple services. Distributed tracing links requests across services:

Backend: Use Activity and OpenTelemetry

Frontend: Correlate with backend via request-id headers

Azure Application Insights automatically handles correlation if configured

builder.Services.AddOpenTelemetryTracing(tracerProviderBuilder =>

{

tracerProviderBuilder

.AddAspNetCoreInstrumentation()

.AddHttpClientInstrumentation()

.AddAzureMonitorTraceExporter(options =>

{

options.ConnectionString = "<YOUR_CONNECTION_STRING>";

});

💡 Best Practices

Practice Recommendation

Structured logs Use JSON format for easier analysis

Centralized logging Avoid logs scattered across VMs or containers

Log levels Use Information for routine, Error for failures

Correlation IDs Track requests across frontend, backend, and database

Sensitive data Never log passwords, tokens, or PII

Monitoring dashboards Set up dashboards for KPIs and SLA metrics

Alerts Always have actionable alerts for errors and performance degradation

💬 Summary

Monitoring and logging in cloud-hosted full stack .NET applications involve structured logging, centralized collection, performance metrics, distributed tracing, and alerts. Using tools like Application Insights, Azure Monitor, and OpenTelemetry, you can gain full visibility into both backend and frontend, allowing proactive maintenance and faster issue resolution.

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November 12, 2025