Home Backend Development Golang The practice of go-zero and ElasticStack: building a high-performance distributed logging, monitoring, and tracking system

The practice of go-zero and ElasticStack: building a high-performance distributed logging, monitoring, and tracking system

Jun 22, 2023 am 09:15 AM
Distributed Systems go-zero elasticstack

With the continuous development of Internet technology and the continuous expansion of application scenarios, the application of distributed systems is becoming more and more widespread. For distributed systems, monitoring, logging and tracing are very important components. They can help us find and solve problems in time and improve the reliability and performance of the system.

This article will introduce a practical method of distributed logging, monitoring, and tracking systems based on go-zero and ElasticStack. This system can help us collect and store logs, monitor system status and display it visually, and track the flow of requests in the distributed system, thereby achieving comprehensive system monitoring and troubleshooting.

  1. Introduction to go-zero

go-zero is an open source Go language microservice framework with high performance, ease of use, and flexibility. It is based on open source frameworks such as Gin and gRPC, provides a wealth of functions and components, and supports full-process management from business code to operation and maintenance, and deployment.

For us, the most important thing is that go-zero provides very convenient logging, monitoring, and tracking components. We can use them very conveniently in business code, which brings us great benefits when building distributed systems. Great convenience and convenience.

  1. Introduction to ElasticStack

ElasticStack is an open source distributed search and analysis engine. It was originally open sourced by Elastic Company. Its core components include Elasticsearch, Logstash, Kibana and Beats.

Among them, Elasticsearch is the core of the distributed search and analysis engine. It provides very powerful search and aggregation functions and can be used to store and search large amounts of structured and unstructured data; Logstash is a A data processing engine that can be used to collect, convert and send data; Kibana is a data visualization tool that can display data in rich charts; Beats is a series of lightweight data collectors that can easily collect and send Various types of data.

We can use ElasticStack to build a logging, monitoring and tracking platform, store the collected data in Elasticsearch, perform visual display and analysis through Kibana, and collect system or application information through Beats.

  1. Building a distributed logging, monitoring and tracing system

Next, we will introduce how to use go-zero and ElasticStack to build distributed logging, monitoring and tracing system.

First, we need to introduce go-zero's logging, monitoring and tracking components into the business code. Taking logs as an example, we can use the logx component. In the business code, we only need to call the relevant methods of the logx package where logs need to be recorded. For example:

logx.WithContext(r.Context()).Info("this is a log message")

Next, we need to use Beats to collect business logs. We can use the Filebeat component to achieve this, which can monitor specified log files, collect log data in real time, and send the data to the specified server. For example, we can configure Filebeat to monitor business log files and send the data to Logstash.

At the same time, we need to integrate the Opentracing component in go-zero to implement the tracking function. We can use the go.opentracing package and the jaeger-client-go package to achieve this. We only need to call the corresponding method in the business code, for example:

span, ctx := opentracing.StartSpanFromContext(r.Context(), "request")
defer span.Finish()

At the same time, we need to use Jaeger or Zipkin as the storage of Opentracing and viewing platforms. We can use Jaeger as the storage platform and use the UI interface in Jaeger to view tracking information.

Finally, we need to use the Metric component to implement the monitoring function. We can use the Prometheus package to achieve this. We only need to call the corresponding method in the business code and configure the Prometheus address and port in the go-zero configuration file. For example:

metric.NewCounter("requests_total").Add(1)

We can use Prometheus components to collect, store and display monitoring data, and we can use Grafana as a visual interface for monitoring data.

  1. Summary

Through the above introduction, we can see that it is very convenient and convenient to use go-zero and ElasticStack to build distributed logging, monitoring and tracking systems. We only need to introduce relevant components into the business code and configure the corresponding parameters, which is very suitable for quickly building a distributed system.

At the same time, we can also use other similar components and frameworks to build distributed systems, such as Logrus, Zipkin, etc. You can choose according to your own needs and actual conditions.

The above is the detailed content of The practice of go-zero and ElasticStack: building a high-performance distributed logging, monitoring, and tracking system. For more information, please follow other related articles on the PHP Chinese website!

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