Detailed explanation of how to perform distributed log management and log analysis in Vue

Logging is an important feature in modern applications to help developers and operations staff understand and troubleshoot applications. As the size and complexity of applications increase, log management and analysis become increasingly difficult. This article will introduce how to implement distributed log management and log analysis functions in Vue applications.

What is distributed log management

Distributed log management is a method of distributing the log collection, storage, and analysis of applications across multiple computers. By storing logs in multiple places, the reliability and scalability of the system can be improved. Distributed log management usually involves the following components:

• Log Collector: Used to collect and send the logs of the application to the central log store.
• Central log storage: Used to store logs for all applications.
• Log Analysis Tool: Used to analyze logs stored in the central log store.

How to implement distributed log management

Implementing distributed log management in Vue applications requires the following steps:

1. Add a log collector

Vue applications can use various log collectors to collect logs. Some popular log collectors include:

log4js: Logging framework suitable for.

Winston: General log library, supports multiple transmission methods.

Bunyan: JSON logger for use.

Here, take log4js as an example, and introduces how to add a log collector in a Vue application.

First, install log4js:

npm install log4js

Then, add the following code to the entry file of the Vue application (for example):

import log4js from 'log4js';

({
  appenders: {
    console: { type: 'console' },
    file: { type: 'file', filename: 'logs/' },
  },
  categories: {
    default: { appenders: ['console', 'file'], level: 'debug' },
  },
});

const logger = ('app');

This will add a logger named "app" and log the logs to the console and logs/files.

2. Centralized log storage

Central log storage can be implemented using various technologies, such as relational databases, non-relational databases, file systems, etc. In this article, we will use Elasticsearch and Logstash as solutions for log storage and analysis.

Elasticsearch is a real-time distributed search and analysis engine that can be used to store and search large amounts of structured and unstructured data. Logstash is an open source data collection engine that collects data from different data sources and sends it to Elasticsearch for storage and analysis.

First, install Elasticsearch and Logstash. It can be downloaded and installed from the official website, or it can be used with Docker containers.

Then, create an index called "vue-logs" and define an index template to correctly parse the logs of the Vue application. You can use the following command to create an index template:

curl -XPUT -H "Content-Type: application/json" http://localhost:9200/_template/vue-logs -d '
{
  "index_patterns": ["vue-logs-*"],
  "settings": {
    "number_of_shards": 1
  },
  "mappings": {
    "properties": {
      "timestamp": { "type": "date" },
      "level": { "type": "keyword" },
      "message": { "type":"text" },
      "logger": { "type": "keyword" },
      "stack_trace": { "type": "text" },
      "context": { "type": "object" }
    }
  }
}'

This creates an index called "vue-logs" and defines the index template to correctly parse fields in the log.

Next, configure Logstash to collect logs from Vue applications and send them to Elasticsearch. The following configuration files are available:

input {
  tcp {
    port => 5044
  }
}
filter {
  json {
    source => "message"
  }
}
output {
  elasticsearch {
    hosts => ["localhost:9200"]
    index => "vue-logs-%{+}"
  }
}

This will receive the logs from TCP port 5044 and parse the log messages using a JSON filter. Then, send the log to Elasticsearch, using the index name in the format "" which is the date of the log.

Finally, start Logstash and make sure the log collector of the Vue application sends the log to the TCP port 5044 of Logstash.

3. Log Analysis

The logs for all Vue applications are now stored in Elasticsearch and can be used for log analysis using Kibana.

Kibana is an open source data visualization tool for searching, analyzing and visualizing large amounts of structured and unstructured data. It can be used with Elasticsearch for quick and intuitive analysis of logs.

First, install Kibana. It can be downloaded and installed from the official website, or it can be used with Docker containers.

Then, open Kibana and define an index pattern called "vue-logs" to correctly parse the logs of the Vue application. You can use the following steps to create an index pattern:

1. In Kibana, click the "Management" tab in the menu on the left.

2. On the "Index Patterns" page, click the "Create index pattern" button.

3. Enter "vue-logs-*" as the index mode and click the "Next step" button.

4. Select "timestamp" as the time field and click the "Create index pattern" button.

Kibana's various features can now be used to search, analyze, and visualize the logs of Vue applications. For example, you can use the Discover page to search for logs and use the Visualize page to create a dashboard to visualize log data.

in conclusion

In this article, we describe how to implement distributed log management and log analysis capabilities in Vue applications. By distributing log collection, storage, and analysis across multiple computers, the reliability and scalability of the system can be improved. Using Elasticsearch and Logstash as solutions for log storage and analysis, and using Kibana for log analysis, it is easy to search, analyze and visualize log data for Vue applications.

The above is a detailed explanation of how to conduct distributed log management and log analysis in Vue. For more information about Vue distributed log management analysis, please pay attention to my other related articles!