golang error log collection

Error handling is particularly important when developing a golang application. Error log collection is a very important link, because it can help us find problems in the program in time, and it can also speed up our steps to troubleshoot errors. Below we will introduce how to collect error logs in golang.

1. Use the log library to record error logs

Golang’s built-in log library provides a simple and powerful logging function that can meet most printing needs. Through the log library, we can output information to the console, file, or other different places. At the same time, the log library also supports recording logs of different levels.

The use of the log library is very simple. Just import the log library and call the Println() or Fatal() function in the code. For example:

import "log"

log.Println("This is a log message")
log.Fatalf("This is a fatal error message")

Use the Println() function to output information to the console and standard output. Use the Fatal() function to output error information and terminate the program.

2. Use third-party log libraries

In addition to using Golang’s built-in log library, we can also use some advanced third-party log libraries. Such as logrus, zap or zerolog, etc., these libraries can implement customized logging more flexibly, and can also better meet the logging requirements of different projects.

1. Use logrus

logrus is a structured logging library that can achieve efficient logging and supports multiple log formats. Using logrus you can easily export JSON format and send logs to remote systems or other third-party loggers, while also customizing log levels and formats. Logrus is also very convenient to use. You only need to import the logrus package and instantiate a log object. For example:

import (
  "github.com/sirupsen/logrus"
)

log := logrus.New()
log.SetFormatter(&logrus.JSONFormatter{})
log.SetLevel(logrus.DebugLevel)
log.WithFields(logrus.Fields{
  "animal": "walrus",
}).Info("A walrus appears")

2. Use zap

zap is a fast, structured logging library that is designed to achieve high performance and can be flexibly deployed in a production environment. In zap, logging is treated as a task, which includes logging to a specified output source (such as a file or MongoDB), and the log level and format can also be customized. Using zap can effectively record application activities, and you can easily find and locate problems when you need to troubleshoot them. For example:

package main

import (
    "go.uber.org/zap"
)

func main() {
    logger, _ := zap.NewProduction()
    defer logger.Sync()
    logger.Info("logrus-start")
}

3. Use distributed tracing system

In large distributed systems, using a log library to record error logs may not meet our needs. Because the number of error logs is huge and manual screening is required, this is often very cumbersome and time-consuming. In this case, we can consider using distributed tracing systems such as Jaeger, Zipkin, and SkyWalking. These systems can better help us track the request direction and error information of distributed systems.

The benefit of using these systems is that they can help us track and record requests in distributed systems, and enable transparent analysis of requests. When problems occur, these systems can help us detect faults in time and help us troubleshoot.

When using a distributed tracking system, we need to add the corresponding tracking code to the application. For example, when using Jaeger, we need to add the following code to the program:

package main

import (
    "net/http"

    "github.com/opentracing/opentracing-go"
    "github.com/uber/jaeger-client-go"
    "github.com/uber/jaeger-client-go/config"
)

func main() {
    cfg := &config.Configuration{
        Sampler: &config.SamplerConfig{
            Type:  "const",
            Param: 1,
        },
        Reporter: &config.ReporterConfig{
            LogSpans:            true,
            LocalAgentHostPort:  "127.0.0.1:6831",
            BufferFlushInterval: 1 * time.Second,
        },
    }
    tracer, closer, err := cfg.New(
        "my-golang-app",
        config.Logger(jaeger.StdLogger),
    )
    if err != nil {
        log.Fatalf("Failed to create tracer: %v", err)
    }
    defer closer.Close()
    opentracing.SetGlobalTracer(tracer)
    r := http.NewServeMux()
    r.HandleFunc("/", handler)
    http.ListenAndServe(":8080", r)
}

In the above code, we use the Jaeger distributed tracing system to track the Golang application. In the configuration, we set the sampler to 1, confirm the log reporting, the address used by the local agent is "127.0.0.1:6831", and the buffer refresh time is 1 second. After that, we defined a global tracker and set it as the global tracker for opentracing.

4. Summary

In the Golang development process, the collection of error logs is an indispensable part. Golang's standard library provides a simple and powerful logging library, while third-party logging libraries provide more flexible customization functions. Especially in large distributed systems, using distributed tracing systems can help us better collect and troubleshoot error logs. When using a log library, we need to choose a suitable log library based on specific project requirements and application scenarios, and pay attention to collecting key log information so that we can better locate and solve problems.

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