Introduction to Debugging and Diagnostics Part 2

In this blog we will continue our exploration into debugging in dot net core. If you missed the first blog you can read it here.

While debugging is typically employed when a known issue or error needs to be resolved, diagnostics take a more proactive approach, aiming to understand the overall health and behavior of an application. The landscape of diagnostics in .NET Core is vast, and it plays a crucial role in developing and maintaining high-performing and reliable applications.

Diagnostics provide valuable insights into an application’s runtime behavior, which cannot be captured during static code analysis or unit testing. Understanding these insights can have a profound impact on an application’s performance, scalability, and stability.

Firstly, diagnostics can help identify performance bottlenecks in an application. For instance, tracking CPU and memory usage can help detect leaks or high-CPU utilization spots in the code.

Secondly, diagnostics are invaluable when investigating issues in a production environment, where active debugging is not feasible. Log files, event traces, and metrics can provide vital clues about the problem’s nature and origin.

Lastly, as applications move towards microservices and cloud-based architectures, diagnostics become even more critical. They help monitor the health of individual components and their interactions, ensuring that the whole system functions as expected.

.NET Core provides a rich set of diagnostic tools to capture various types of application data:

1. Logging: Built-in support for flexible and configurable logging that can capture application events for later review. Libraries like NLog and Serilog can also be used for advanced logging scenarios.

public static IHostBuilder CreateHostBuilder(string[] args) =>
    Host.CreateDefaultBuilder(args)
        .ConfigureLogging(logging =>
        {
            logging.ClearProviders();
            logging.AddConsole();
        });

2. Metrics and Telemetry: .NET Core is compatible with several metrics and telemetry collection tools like Prometheus and Application Insights. These tools collect data like request rates, response times, and failure rates to analyze application performance.

3. Event Tracing: .NET Core includes EventSource and EventListener classes for low-overhead, high-speed logging, particularly suitable for tracing and profiling.

4. Dumps: A snapshot of the process’s memory, dumps can be incredibly useful for post-mortem diagnostics. Tools like dotnet-dump can be used to collect and analyze dumps.

5. Counters: .NET Core includes many counters to track metrics like CPU usage, garbage collection statistics, exception rates, and more. The dotnet-counters tool can monitor these counters in a running application.

6. Trace Analysis: The dotnet-trace tool can collect traces from a .NET Core application for performance analysis.

These tools, when used effectively, can offer invaluable insights into your .NET Core applications, helping you keep them performant, scalable, and reliable.

Diagnostics in .NET Core involves various tools and strategies for identifying and resolving performance issues. To properly diagnose performance problems, it’s essential to understand the concepts of performance counters, how to analyze CPU usage and memory consumption, and the various profiling tools at your disposal.

Performance counters in .NET Core provide a way to collect and monitor various metrics about your application’s performance. There are numerous performance counters available, tracking everything from exception rates to CPU and memory usage.

The dotnet-counters tool is specifically designed to observe these performance counters in a .NET Core application. It can be used to monitor the performance of your application in real-time, which is particularly useful for identifying performance bottlenecks.

# To monitor all counters
dotnet-counters monitor

# To monitor specific counters
dotnet-counters monitor --counters System.Runtime[cpu-usage]

Analyzing CPU usage and memory consumption is fundamental to diagnosing performance issues in an application. High CPU usage may indicate an infinite loop, a busy wait, or a complex computation, while growing memory usage may be a sign of a memory leak.

You can use the dotnet-counters tool to monitor CPU usage and memory consumption:

# Monitor CPU usage and GC heap size
dotnet-counters monitor --counters System.Runtime[cpu-usage,gc-heap-size]

Additionally, the dotnet-dump tool can be used to collect a memory dump of your .NET Core application, which can then be analyzed for high memory usage:

# Collect a dump
dotnet-dump collect

# Analyze the dump
dotnet-dump analyze ./path/to/dump

.NET Core offers several profiling tools to help identify performance issues in your application:

• dotnet-trace: This tool helps collect performance traces from a .NET Core application, which can then be analyzed using a tool like PerfView or Speedscope.

# Collect a trace
dotnet-trace collect --process-id 12345

# The trace can then be viewed in a viewer like PerfView

• Visual Studio Performance Profiler: Visual Studio’s built-in profiler provides an easy-to-use interface for profiling .NET Core applications. It can track CPU usage, memory consumption, and more.

To use the profiler, go to Debug > Performance Profiler, select the metrics you want to track, and then run your application.

By using these tools and techniques effectively, you can gain deep insights into the performance of your .NET Core applications and efficiently diagnose and resolve performance issues.

Logging and tracing are two types of diagnostics tools used for interrogating application behavior. They are used for debugging, monitoring and other activities related to quality assurance. These tools have become increasingly important in today’s software applications due to their ability to provide visibility into application issues.

Logging and tracing are important for identifying application issues and ensuring software quality. Logging enables developers to track program state and capture user interactions while tracing allows them to analyze the sequence of program operations. This can help to detect performance issues, identify errors, and determine how a software system is being used.

The ability to diagnose problems quickly and accurately helps to reduce maintenance costs and increase productivity. Logging and tracing alsoare important when deploying applications in the cloud, as it is difficult for developers to identify issues in systems they cannot access.

.NET Core provides a logging framework, which allows developers to log structured information about application state. This framework contains a set of components and a logging API which can be used to write logs to the file system, event log, database, or any other structured medium.

The following sample code shows how to write a log in .NET Core:

// Create a logger
ILogger Logger = ...;
 
// Log a message
Logger.LogInformation("Processing file {FileName}", fileName);

The framework supports multiple logging levels, such as LogDebug, LogInformation, LogWarning, LogError and LogFatal. Each logging level has its own significance, which should be considered when deciding whether to log a particular message.

Diagnostic tracing allows developers to observe the program execution over time, tracing individual requests and responses. It can be used to detect performance and scalability issues in complex distributed systems.

NET Core provides a tracing framework which allows developers to instrument their applications and capture trace information. This framework allows developers to define and capture traces using a set of APIs.

The following sample code shows how to capture a trace:

// Create a trace listener & Event source
TraceListener listener = ...;
EventSource source = ...;
 
// Start capturing traces
source.TraceInformation("Processing file {FileName}", fileName);

Tracing information is logged to a stream or store, using an implementation provided by the developer. This data can then be used to analyze application issues or identify trends in application performance.

Logging and tracing are important diagnostics tools for software applications, and .NET Core provides frameworks for both. These tools help to reduce maintenance costs and increase productivity, by providing visibility into application issues.