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ELK Stack Log Analysis Samples

Comprehensive ELK Stack (Elasticsearch, Logstash, Kibana) samples for log aggregation, processing, and visualization in distributed systems

Samples

Entries inside this sample collection

TextComplex

Elasticsearch Index Mapping Configuration

Advanced index mapping with custom analyzers, field types, and optimization for log data

Difficulty

6/10

Estimated time

15 min

Tags

elasticsearch, index, mapping, schema, analyzers, optimization

plaintext
{
  "mappings": {
    "properties": {
      "@timestamp": { "type": "date" },
      "level": {
        "type": "keyword",
        "fields": {
          "text": { "type": "text" }
        }
      },
      "message": {
        "type": "text",
        "analyzer": "standard",
        "fields": {
          "keyword": { "type": "keyword" }
        }
      },
      "service": { "type": "keyword" },
      "trace_id": { "type": "keyword" },
      "span_id": { "type": "keyword" },
      "user_id": { "type": "keyword" },
      "request_id": { "type": "keyword" },
      "response_time": { "type": "float" },
      "status_code": { "type": "integer" },
      "error": {
        "type": "object",
        "properties": {
          "type": { "type": "keyword" },
          "message": { "type": "text" },
          "stack_trace": { "type": "text" }
        }
      },
      "tags": { "type": "keyword" },
      "host": {
        "properties": {
          "name": { "type": "keyword" },
          "ip": { "type": "ip" },
          "os": { "type": "keyword" }
        }
      },
      "geoip": {
        "properties": {
          "location": { "type": "geo_point" },
          "country_name": { "type": "keyword" },
          "city_name": { "type": "keyword" }
        }
      }
    }
  },
  "settings": {
    "analysis": {
      "analyzer": {
        "log_analyzer": {
          "type": "custom",
          "tokenizer": "standard",
          "filter": ["lowercase", "stop"]
        }
      }
    },
    "number_of_shards": 3,
    "number_of_replicas": 1
  }
}
format
JSON
version
8.x
components
["mapping","analyzer","field-types"]
complexity
advanced
TextComplex

Logstash Data Processing Pipeline

Complete Logstash pipeline configuration for parsing, filtering, and enriching log data from multiple sources

Difficulty

8/10

Estimated time

25 min

Tags

logstash, pipeline, grok, filter, parse, enrich, transform

plaintext
input {
  beats {
    port => 5044
  }
  tcp {
    port => 5000
    codec => json_lines
  }
  file {
    path => "/var/log/*.log"
    start_position => "beginning"
  }
}

filter {
  # Parse JSON logs
  if [message] =~ /^{.*}$/ {
    json {
      source => "message"
      target => "parsed"
    }
  }

  # Parse timestamp
  date {
    # Parse the timestamp extracted by grok and normalize it into @timestamp
    match => [ "timestamp", "ISO8601", "yyyy-MM-dd HH:mm:ss.SSS" ]
    target => "@timestamp"
  }

  # Add GeoIP information
  if [client_ip] {
    geoip {
      source => "client_ip"
      target => "geoip"
    }
  }

  # Parse user agent
  if [user_agent] {
    useragent {
      source => "user_agent"
      target => "ua"
    }
  }

  # Extract fields from log messages
  grok {
    match => {
      "message" => "%{TIMESTAMP_ISO8601:timestamp} %{LOGLEVEL:level} \[%{DATA:thread}\] %{DATA:logger} - %{GREEDYDATA:log_message}"
    }
    tag_on_failure => ["_grokparsefailure"]
  }

  # Mutate and clean up fields
  mutate {
    add_field => { "service_name" => "%{[fields][service]}" }
    add_field => { "environment" => "%{[fields][environment]}" }
    remove_field => [ "host", "agent", "ecs", "input" ]
    convert => {
      "response_time" => "float"
      "status_code" => "integer"
    }
  }

  # Add fingerprint for deduplication
  fingerprint {
    source => ["message", "@timestamp", "service_name"]
    target => "fingerprint"
  }

  # Conditional routing based on log level
  if [level] == "ERROR" or [level] == "FATAL" {
    mutate {
      add_tag => ["error", "alert"]
    }
  }
}

output {
  elasticsearch {
    hosts => ["http://elasticsearch:9200"]
    index => "logs-%{+YYYY.MM.dd}"
    template_name => "logs"
    template_pattern => "logs-*"
    template => "/usr/share/logstash/templates/logs-template.json"
  }

  # Send critical errors to separate index
  if "alert" in [tags] {
    elasticsearch {
      hosts => ["http://elasticsearch:9200"]
      index => "alerts-%{+YYYY.MM.dd}"
    }
  }

  # Debug output to console
  if [@metadata][debug] {
    stdout {
      codec => rubydebug
    }
  }
}
format
CONF
version
8.x
components
["input","filter","output"]
features
["grok-patterns","date-parsing","geoip","mutate"]
TextComplex

Kibana Visualization Dashboard

Comprehensive Kibana dashboard with multiple visualizations for log analysis and monitoring metrics

Difficulty

5/10

Estimated time

20 min

Tags

kibana, dashboard, visualization, charts, metrics, monitoring

plaintext
{
  "dashboard": {
    "title": "System Log Analysis Dashboard",
    "panelsJSON": "[{"gridData":{"x":0,"y":0,"w":24,"h":15,"i":"1"},"panelIndex":"1","embeddableConfig":{},"panelRefName":"panel_1"},{"gridData":{"x":24,"y":0,"w":24,"h":15,"i":"2"},"panelIndex":"2","embeddableConfig":{},"panelRefName":"panel_2"},{"gridData":{"x":0,"y":15,"w":48,"h":15,"i":"3"},"panelIndex":"3","embeddableConfig":{},"panelRefName":"panel_3"}]",
    "timeRestore": false,
    "timeTo": "now",
    "timeFrom": "now-24h",
    "refreshInterval": {
      "pause": false,
      "value": 30000
    },
    "kibanaSavedObjectMeta": {
      "searchSourceJSON": "{"query":{"match_all":{}},"filter":[]}"
    },
    "description": "Comprehensive dashboard for monitoring system logs, errors, and performance metrics",
    "version": "8.0.0"
  },
  "timeField": "@timestamp",
  "panels": [
    {
      "id": "1",
      "type": "metric",
      "title": "Total Log Events",
      "visState": "{ "type": "metric", "aggs": [{ "id": "1", "type": "count", "schema": "metric", "params": {} }] }",
      "description": "Total number of log events in the selected time range"
    },
    {
      "id": "2",
      "type": "histogram",
      "title": "Log Levels Distribution",
      "visState": "{ "type": "histogram", "aggs": [{ "id": "1", "type": "count", "schema": "metric", "params": {} }, { "id": "2", "type": "terms", "schema": "segment", "params": { "field": "level", "size": 10 } }] }",
      "description": "Distribution of log levels across all services"
    },
    {
      "id": "3",
      "type": "line",
      "title": "Logs Timeline",
      "visState": "{ "type": "line", "aggs": [{ "id": "1", "type": "count", "schema": "metric", "params": {} }, { "id": "2", "type": "date_histogram", "schema": "segment", "params": { "field": "@timestamp", "interval": "1h" } }] }",
      "description": "Timeline of log events over time"
    }
  ]
}
format
JSON
version
8.x
components
["dashboard","visualization","saved-objects"]
visualizations
["bar-chart","line-chart","pie-chart","data-table","heatmap"]
TextSimple

Application Log Aggregation Format

Structured JSON log format for application logs with correlation IDs and metadata for distributed tracing

Difficulty

2/10

Estimated time

5 min

Tags

log-format, json, structured-logging, correlation-id, metadata

plaintext
{
  "@timestamp": "2025-12-07T10:30:45.123Z",
  "level": "INFO",
  "message": "User authentication successful",
  "service": "auth-service",
  "version": "2.1.3",
  "trace_id": "550e8400-e29b-41d4-a716-446655440000",
  "span_id": "550e8400-e29b-41d4-a716-446655440001",
  "parent_span_id": "550e8400-e29b-41d4-a716-446655440000",
  "user_id": "user_12345",
  "request_id": "req_67890",
  "session_id": "sess_abcde",
  "correlation_id": "corr_fghij",

  "context": {
    "host": "auth-server-01",
    "pod": "auth-service-7f8d9c2b-k4l5m",
    "namespace": "production",
    "environment": "prod",
    "region": "us-west-2"
  },

  "request": {
    "method": "POST",
    "path": "/api/v1/auth/login",
    "user_agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36",
    "client_ip": "192.168.1.100",
    "response_time": 145.67,
    "status_code": 200
  },

  "user": {
    "id": "user_12345",
    "email": "[email protected]",
    "roles": ["user", "premium"],
    "tenant": "company_xyz"
  },

  "security": {
    "auth_method": "jwt",
    "mfa_enabled": true,
    "login_attempts": 2,
    "risk_score": "low"
  },

  "performance": {
    "cpu_usage": 12.5,
    "memory_usage": 67.8,
    "disk_io": 2.1,
    "network_io": 15.3
  },

  "tags": ["authentication", "successful", "mfa"],
  "metadata": {
    "source": "application",
    "format_version": "1.0",
    "encoding": "utf-8"
  }
}
format
JSON
standard
Structured Logging
fields
["timestamp","level","message","service","trace-id","span-id","metadata"]
TextComplex

Advanced Elasticsearch Query Examples

Complex Elasticsearch queries including aggregations, filters, and full-text search for log analysis

Difficulty

7/10

Estimated time

30 min

Tags

elasticsearch, query, aggregation, filter, search, dsl

plaintext
{
  "query": {
    "bool": {
      "must": [
        {
          "range": {
            "@timestamp": {
              "gte": "now-24h",
              "lte": "now"
            }
          }
        },
        {
          "bool": {
            "should": [
              {
                "term": {
                  "level": "ERROR"
                }
              },
              {
                "term": {
                  "level": "FATAL"
                }
              }
            }
          }
        }
      ],
      "filter": [
        {
          "terms": {
            "service": ["auth-service", "api-gateway", "user-service"]
          }
        }
      ]
    }
  },
  "aggs": {
    "services": {
      "terms": {
        "field": "service",
        "size": 10
      },
      "aggs": {
        "error_types": {
          "terms": {
            "field": "error.type",
            "size": 5
          }
        },
        "hourly_distribution": {
          "date_histogram": {
            "field": "@timestamp",
            "calendar_interval": "1h"
          }
        },
        "avg_response_time": {
          "avg": {
            "field": "response_time"
          }
        }
      }
    },
    "geoip_distribution": {
      "terms": {
        "field": "geoip.country_name",
        "size": 20
      }
    },
    "user_analysis": {
      "cardinality": {
        "field": "user_id"
      }
    },
    "response_time_stats": {
      "stats": {
        "field": "response_time"
      }
    },
    "error_timeline": {
      "date_histogram": {
        "field": "@timestamp",
        "calendar_interval": "10m"
      },
      "aggs": {
        "top_error_messages": {
          "top_hits": {
            "size": 3,
            "sort": [
              {
                "@timestamp": {
                  "order": "desc"
                }
              }
            ],
            "_source": ["message", "error.message", "service"]
          }
        }
      }
    }
  },
  "sort": [
    {
      "@timestamp": {
        "order": "desc"
      }
    }
  ],
  "size": 100,
  "highlight": {
    "fields": {
      "message": {},
      "error.message": {}
    }
  }
}
format
JSON
queryType
DSL
features
["term-queries","range-queries","aggregations","bool-queries","nested-queries"]

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Title

ELK Stack Log Analysis Samples

Description

Comprehensive ELK Stack (Elasticsearch, Logstash, Kibana) samples for log aggregation, processing, and visualization in distributed systems

Overview

Comprehensive ELK Stack (Elasticsearch, Logstash, Kibana) samples for log aggregation, processing, and visualization in distributed systems

When to use

  • Use this sample set when you want reference inputs for ELK Stack Log Analysis Samples.
  • Use it to preview output formats and compare related sample variants.

How it works

  1. 1Open a sample entry to inspect the prepared example payload or asset.
  2. 2Compare it with related tools to understand how the workflow connects.

Use cases

  • Elasticsearch Index Mapping Configuration
  • Logstash Data Processing Pipeline
  • Kibana Visualization Dashboard
  • Application Log Aggregation Format
  • Advanced Elasticsearch Query Examples

FAQ

What is included in ELK Stack Log Analysis Samples?

This page includes curated sample entries, related tools, and neighboring sample collections for ELK Stack Log Analysis Samples.

Hub

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Derive a reviewable JSON Schema draft from representative JSON samples or XLSX rows, then inspect types, requiredness, nulls, and outliers before treating it as a contract.

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Observability Debugging from Logs, Traces, Webhooks, and JSON Payloads

Parse logs, decode traces, inspect webhook/API evidence, explore JSON payloads, and extract recurring patterns before writing an incident-ready debugging note.

Hub

Structured Signal Extraction from Text, HTML, Markdown, and Logs

Turn mixed text sources into reviewable links, attributes, dates, log fields, and sensitive-match inventories with a deliberate extraction path.

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Product, Publication, and Logistics Code Validation

Check ISBN, UPC/EAN/GTIN, and carrier tracking identifiers for supported formats and available check digits before a catalog or shipment handoff.

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