(22) go-micro microservice kibana use

A kibana introduction

• Kibana: is an open source analytics and visualization platform designed to work with Elasticsearch. Kibana provides the ability to search, view , and interact with data stored in Elasticsearch indexes. Developers or operators can easily perform advanced data analysis and visualize data in various charts, tables and maps .

Two main functions of Kibana

• The Kibana architecture is customized for Elasticsearch, and any structured and unstructured
  data can be added to the Elasticsearch index.

• Kibana can better handle massive amounts of data, and create column charts, line charts, scatter plots, histograms, pie charts, and maps based on them for users to view.

• Kibana improves Elasticsearch's analysis capabilities, can analyze data more intelligently, perform mathematical transformations, and split data into chunks as required.

• Using Kibana can create, save, and share data more easily, and quickly communicate visual data.

• Kibana is very simple to configure and enable, and the user experience is very friendly. Kibana comes with a web server that can be up and running quickly.

• Kibana can easily integrate data from Logstash, ES-Hadoop, Beats or third-party technologies

Three Kibana sidebars

• Discover (data exploration): search, filter and display selected index model (Index Pattern) document data
• Visualize: Create visualization controls for data
• Dashboard (dashboard): display the saved set of visual results
• Canvas: very free and flexible visual layout and display of data
• Maps: display aggregated information in the form of a map
• Machine Learning
• Infrastructure (infrastructure monitoring): monitor basic services through metricbeat. Such as: redis, rocketmq
• Metrics: Explore metrics about systems and services across the ecosystem
• Logs: Tracks relevant log data in real time; provides a compact, console-like display. Real-time log tailing
• APM (Application Performance Monitoring-application performance monitoring): business tracking and monitoring.
• Uptime (Uptime): Monitor applications and services for availability issues; monitor the status of network endpoints via HTTP/S, TCP, and ICMP
• SIEM (Security Information & Event Management-Security Information and Event Management): A highly interactive workspace for security analysts
• Dev Tools: Includes console, query analysis, and aggregation
• Stack Monitoring (ELK monitoring): visual monitoring data
• Management (Kibana management): including the initial setting and continuous configuration of the index mode, etc.

Four Kibana installation

1. Pull the image

docker pull kibana

2. Run the command

docker run --name kibana -d -p 5601:5601 kibana

3. Check whether it is running

docker ps

Five Kibana uses

• In order to facilitate the use of ELK at the same time, create a new directorydocker-elk

• Create a new one in the docker-elk directorykibana/config/kibana.yml

• In kibana.yml, enter the following code:

---
server.name: kibana
server.host: 0.0.0.0
elasticsearch.hosts: ["http://elasticsearch:9200"]
monitoring.ui.container.elasticsearch.enabled: true

elasticsearch.username: elastic
elasticsearch.password: pwd

• Create a docker-stack.yml in the docker-elk directory and start ELK at the same time

• Enter the following code:

version: '3.3'
services:
  kibana:
    image: kibana:latest
    ports:
      - "5601:5601"
    volumes:
      - ./kibana/config/kibana.yml:/usr/share/kibana/config/kibana.yml

• So far, logstash has been used so far

Six Kibana graphical interface

• run:

docker run --name kibana -d -p 5601:5601 kibana

• Browser address input: http://127.0.0.1:5601/

seven last

• So far, the use of kibana in the go-micro microservice project has been officially completed.

• Next, I started to write codes for client development (using load balancing). I hope you pay attention to bloggers and columns, and get the latest content as soon as possible. Every blog is full of dry goods.