Horse Telemetry Observability

Horse Telemetry & Observability

Native Telemetry Hook (AddOnTelemetry)

Horse provides a high-precision, native, and Zero-Allocation telemetry hook based on stack-allocated TStopwatch. This hook allows monitoring and logging the total processing latency of all requests passing through the server pipeline.

The telemetry callback is defined as follows:

THorseOnTelemetry = {$IF DEFINED(FPC)}procedure{$ELSE}reference to procedure{$ENDIF}(const ARequest: THorseRequest; const AResponse: THorseResponse; const AExecutionTimeMS: Double);

Registering the Telemetry Hook

1. Global Registration

For applications using the standard static THorse facade, register the telemetry hook globally during the bootstrap process:

uses
  Horse, System.SysUtils;

begin
  THorse.AddOnTelemetry(
    procedure(const Req: THorseRequest; const Res: THorseResponse; const ExecutionTimeMS: Double)
    begin
      Writeln(Format('[Telemetry] %s %s - Status: %d - Latency: %.2f ms', 
        [Req.Method, Req.PathInfo, Res.Status, ExecutionTimeMS]));
    end);

  THorse.Get('/ping',
    procedure(Req: THorseRequest; Res: THorseResponse)
    begin
      Res.Send('pong');
    end);

  THorse.Listen(9000);
end.

2. Multi-Instance Registration

For applications utilizing THorseInstance, register telemetry hooks directly on each instance. Telemetry is fully isolated per port and polymorphically resolved based on the incoming request port:

var
  LInstance1, LInstance2: THorseInstance;
begin
  LInstance1 := THorseInstance.Create;
  LInstance1.AddOnTelemetry(
    procedure(const Req: THorseRequest; const Res: THorseResponse; const ExecutionTimeMS: Double)
    begin
      Writeln(Format('[Instance 1 - Port %d] Latency: %.2f ms', [Req.RawWebRequest.ServerPort, ExecutionTimeMS]));
    end);

  LInstance2 := THorseInstance.Create;
  LInstance2.AddOnTelemetry(
    procedure(const Req: THorseRequest; const Res: THorseResponse; const ExecutionTimeMS: Double)
    begin
      Writeln(Format('[Instance 2 - Port %d] Latency: %.2f ms', [Req.RawWebRequest.ServerPort, ExecutionTimeMS]));
    end);
end;

Design Safeguards & AI Best Practices

1. Catch Internal Exceptions: Always wrap the code inside custom telemetry callbacks with a try-except block (or rely on Horse's native try-except boundary) to ensure failures during metrics collecting (like database logging or APM networking errors) never interrupt the HTTP response loop or crash the socket execution thread.
2. Zero-Allocation Logging: To maintain Horse's zero-allocation characteristics, avoid dynamic heap allocations (such as concatenating strings or creating new logger objects) inside the telemetry callback. Prefer reusing static buffers or writing to stack-allocated variables.
3. Multi-Instance Port Resolution: Always use Req.RawWebRequest.ServerPort if you need to determine the active port of the incoming request dynamically inside the telemetry handler.
4. FPC/Lazarus Compatibility: In FPC (Lazarus), the callback type is a standard procedural pointer. Do not use inline anonymous methods (procedure begin end) when compiling libraries or handlers for Lazarus.