MoniGo is a performance monitoring library for Go applications. It provides real-time insights into application performance with an intuitive user interface, enabling developers to track and optimize both service-level and function-level metrics.

• Real-Time Monitoring: Access up-to-date performance metrics for your Go applications.
• Detailed Insights: Track and analyze both service and function-level performance.
• Customizable Dashboard: Manage performance data with an easy-to-use UI.
• Visualizations: Utilize graphs and charts to interpret performance trends.
• Custom Thresholds: Configure custom thresholds for your application's performance and resource usage.

To install MoniGo, use the following command:

go get github.com/iyashjayesh/monigo@latest

package main

import (
    "github.com/iyashjayesh/monigo"
)

func main() {

	monigoInstance := &monigo.Monigo{
		ServiceName:             "data-api", // Mandatory field
		DashboardPort:           8080,       // Default is 8080
		DataPointsSyncFrequency: "5s",       // Default is 5 Minutes
		DataRetentionPeriod:     "4d",       // Default is 7 days. Supported values: "1h", "1d", "1w", "1m"
		TimeZone:                "Local",    // Default is Local timezone. Supported values: "Local", "UTC", "Asia/Kolkata", "America/New_York" etc. (https://en.wikipedia.org/wiki/List_of_tz_database_time_zones)
		// MaxCPUUsage:             90,         // Default is 95%
		// MaxMemoryUsage:          90,         // Default is 95%
		// MaxGoRoutines:           100,        // Default is 100
	}

   	monigo.TraceFunction(highCPUUsage) // Trace function, when the function is called, it will be traced and the metrics will be displayed on the dashboard

	go monigoInstance.Start() // Starting monigo dashboard
	log.Println("Monigo dashboard started at port 8080")

  	// Optional
	// routinesStats := monigoInstance.GetGoRoutinesStats() // Get go routines stats
	// log.Println(routinesStats)

  	select {} // To keep the program running
}

// highCPUUsage is a function that simulates high CPU usage
func highCPUUsage() {
	// Simulate high CPU usage by performing heavy computations
	var sum float64
	for i := 0; i < 1e8; i++ { // 100 million iterations
		sum += math.Sqrt(float64(i))
	}
}

For more detailed usage instructions, refer to the documentation. By default, the dashboard will be available at http://localhost:8080/ else at the port you have provided.

The monigo.TraceFunction(func()) method accept func(){} as a type.

func apiHandler(w http.ResponseWriter, r *http.Request) {
    // Trace function: when the highMemoryUsage function is called, it will be traced.
    monigo.TraceFunction(highMemoryUsage)
    w.Write([]byte("API1 response: memexpensiveFunc"))
}

func highMemoryUsage() {
    // Simulate high memory usage by allocating a large slice
    largeSlice := make([]float64, 1e8) // 100 million elements
    for i := 0; i < len(largeSlice); i++ {
        largeSlice[i] = float64(i)
    }
}

1. Load Statistics: Provides an overview of the overall load of the service, CPU load, memory load, and system load.

2. CPU Statistics: Displays the total number of cores, cores used by the service, and cores used by the system.

3. Memory Statistics: Shows the total system memory, memory used by the system, memory used by the service, available memory, GC pause duration, and stack memory usage.

4. Memory Profile: Provides information on heap allocation by the service, heap allocation by the system, total allocation by the service, and total memory by the OS.

5. Network IO: Displays the number of bytes sent and received.

6. Health Metrics: Provides an overall health percentage for the service.

• You can access the MoniGo API by visiting the following URL: http://localhost:8080/monigo/api/v1/ (replace <endpoint> with the desired endpoint).
• API endpoints are available for the following:

We welcome contributions! If you encounter any issues or have suggestions, please submit a pull request or open an issue.

If you find MoniGo useful, consider giving it a star! ⭐

For questions or feedback, please open an issue or contact me at iyashjayesh@gmail.com or at LinkedIn

This project is licensed under the Apache 2.0 License - see the LICENSE file for details.