Using Elasticsearch, In-House Built Logstash, and Kibana to Build a Log Management Platform

Scenarios

Overview

Figure 1 shows the architecture of the log management platform using Elasticsearch and Logstash.

Figure 1 ELKB architecture

1. Collection
   • As a data collector, Beats gather data from various sources and send it to Logstash.
   • Logstash can independently collect data or receive it from Beats to filter, transform, and enhance the data.
2. Data processing

   Before sending data to Elasticsearch, Logstash performs necessary processing, such as parsing structured logs and filtering out irrelevant information.

3. Data storage

   As a core storage component, Elasticsearch indexes and stores data from Logstash, providing quick search and data retrieval functions.

4. Data analysis and visualization

   Kibana is used to analyze and visualize data in Elasticsearch, allowing users to create dashboards and reports to visualize the data.

For details about the version compatibility of ELKB components, see https://www.elastic.co/support/matrix#matrix_compatibility.

Advantages

• Real-time: Provide real-time data collection and analysis capabilities.
• Flexibility: Support various data sources and flexible data processing flows.
• Ease of use: The user-friendly interface simplifies data operations and visualization.
• Scalability: Offer strong horizontal expansion capabilities, enabling the processing of petabyte-level data.

Prerequisites

• You have created an Elasticsearch cluster in non-security mode. For details, see Creating an Elasticsearch Cluster.
• You have applied for an ECS and installed the Java environment. For details about how to purchase an ECS, see Purchasing and Logging In to a Linux ECS.

Procedure

1. Log in to the ECS, deploy and configure Filebeat.
   1. Download Filebeat. The recommended version is 7.6.2. Download it at https://www.elastic.co/downloads/past-releases#filebeat-oss.
   2. Configure the Filebeat configuration file filebeat.yml.
      For example, to collect all the files whose names end with log in the /root/ directory, configure the filebeat.yml file is as follows:

      filebeat.inputs:
      - type: log
        enabled: true
        # Path of the collected log file
        paths:
          - /root/*.log
      
      filebeat.config.modules:
        path: ${path.config}/modules.d/*.yml
        reload.enabled: false
      # Logstash hosts information
      output.logstash:
        hosts: ["192.168.0.126:5044"]
      
      processors:

2. Deploy and configure Logstash in-house.
   

   To achieve better performance, you are advised to set the JVM parameter to half of the ECS or docker memory for in-house built Logstash.

   1. Download Logstash. The recommended version is 7.6.2. Download it at https://www.elastic.co/downloads/past-releases#logstash-oss.
   2. Ensure that Logstash and the CSS cluster are connected. Run the curl http:// {ip}:{port} command on the VM to test the connectivity between the VM and the Elasticsearch cluster. If 200 is returned, they are connected.
   3. Configure the Logstash configuration file logstash-sample.conf.

      The content of the logstash-sample.conf file is as follows:

      input {
        beats {
          port => 5044
        }
      }
      # Split data.
      filter {
          grok {
              match => {
                  "message" => '\[%{GREEDYDATA:timemaybe}\] \[%{WORD:level}\] %{GREEDYDATA:content}'
              }
          }
          mutate {
            remove_field => ["@version","tags","source","input","prospector","beat"]
          }
      }
      # CSS cluster information
      output {
        elasticsearch {
          hosts => ["http://192.168.0.4:9200"]
          index => "%{[@metadata][beat]}-%{+YYYY.MM.dd}"
          #user => "xxx"
          #password => "xxx"
        }
      }

      

      You can use Grok Debugger (https://grokdebugger.com/) to configure the filter mode of Logstash.

3. Configure the index template of the Elasticsearch cluster.
   1. Log in to the CSS management console.
   2. In the navigation pane on the left, choose Clusters > Elasticsearch.
   3. In the cluster list, locate the target cluster and click Kibana in the Operation column to log in to Kibana.
   4. Click Dev Tools in the navigation tree on the left.
   5. Create an index template.

      For example, create an index template. Let the index use three shards and no replicas. Fields such as @timestamp, content, host.name, level, log.file.path, message and timemaybe are defined in the index.

      PUT _template/filebeat
      {
        "index_patterns": ["filebeat*"],
        "settings": {
          # Define the number of shards.
          "number_of_shards": 3,
          # Define the number of copies.
          "number_of_replicas": 0,
          "refresh_interval": "5s"
        },
        # Define a field.
        "mappings": {
              "properties": {
                "@timestamp": {
                  "type": "date"
                },
                "content": {
                  "type": "text"
                },
                "host": {
                  "properties": {
                    "name": {
                      "type": "text"
                    }
                  }
                },
                "level": {
                  "type": "keyword"
                },
                "log": {
                  "properties": {
                    "file": {
                      "properties": {
                        "path": {
                          "type": "text"
                        }
                      }
                    }
                  }
                },
                "message": {
                  "type": "text"
                },
                "timemaybe": {
                  "type": "date",
                  "format": "yyyy-MM-dd HH:mm:ss||strict_date_optional_time||epoch_millis||EEE MMM dd HH:mm:ss zzz yyyy"
                }
              }
          }
      }

4. Prepare test data on ECS.

   Run the following command to generate test data and write the data to /root/tmp.log:

   bash -c 'while true; do echo [$(date)] [info] this is the test message; sleep 1; done;' >> /root/tmp.log &

   The following is an example of the generated test data:

   [Thu Feb 13 14:01:16 CST 2020] [info] this is the test message

5. Run the following command to start Logstash:

   nohup ./bin/logstash -f /opt/pht/logstash-6.8.6/logstash-sample.conf &

6. Run the following command to start Filebeat:

   ./filebeat

7. Use Kibana to query data and create reports.
   1. Enter the Kibana page of the Elasticsearch cluster.
   2. Click Discover in the navigation tree on the left, as shown in Figure 2.
      Figure 2 Discover page