Kibana
Open-source data visualization and exploration tool designed to work with Elasticsearch. Provides rich visualization options, machine learning anomaly detection, and geospatial mapping capabilities.
Server
Kibana
Overview
Kibana is an open-source data visualization and exploration tool designed to work with Elasticsearch. It provides rich visualization options, machine learning anomaly detection, and geospatial mapping capabilities. As the visualization component of the ELK stack, it maintains high adoption rates and continues growing in the enterprise market with machine learning integration, advanced analytics, and real-time visualization capabilities.
Details
Kibana serves as the visualization component of the ELK stack with high adoption rates in enterprise environments. It continues growing with machine learning integration, advanced analytics capabilities, and real-time visualization features. The platform offers intuitive data exploration, custom dashboard creation, and comprehensive analytics tools. With strong integration with Elasticsearch and the broader Elastic ecosystem, Kibana provides powerful insights into log data, metrics, and business intelligence across diverse use cases.
Key Technical Features
- Rich Visualizations: 30+ visualization types including charts, maps, and tables
- Machine Learning Integration: Built-in anomaly detection and forecasting
- Real-time Dashboards: Live data streaming and auto-refresh capabilities
- Geospatial Analysis: Advanced mapping and location-based analytics
- Advanced Analytics: Statistical analysis and data modeling tools
- Canvas: Pixel-perfect infographic and presentation creation
Use Cases
- Log analysis and troubleshooting
- Security information and event management (SIEM)
- Business intelligence and reporting
- Application performance monitoring
- Infrastructure monitoring and alerting
- Operational dashboards and KPI tracking
Pros and Cons
Pros
- Seamless Elasticsearch Integration: Native compatibility with Elasticsearch
- Intuitive Interface: User-friendly drag-and-drop dashboard builder
- Advanced Visualizations: Comprehensive chart types and mapping capabilities
- Machine Learning Features: Built-in anomaly detection and forecasting
- Real-time Processing: Live data updates and streaming capabilities
- Enterprise Security: Role-based access control and audit logging
Cons
- Elasticsearch Dependency: Requires Elasticsearch as primary data source
- Resource Intensive: High memory and CPU usage with large datasets
- Learning Curve: Complex features require significant training
- Performance Issues: Slow rendering with complex visualizations
- Limited Data Sources: Primarily designed for Elasticsearch integration
- Licensing Complexity: Mixed licensing model can be confusing
Reference Pages
Code Examples
Installation and Basic Setup
# Docker installation
docker pull docker.elastic.co/kibana/kibana:8.16.0
# Run Kibana container
docker run -d \
--name kibana \
-p 5601:5601 \
-e "ELASTICSEARCH_HOSTS=http://elasticsearch:9200" \
-e "SERVER_NAME=kibana.example.com" \
docker.elastic.co/kibana/kibana:8.16.0
# Using Docker Compose
cat > docker-compose.yml << EOF
version: '3.8'
services:
elasticsearch:
image: docker.elastic.co/elasticsearch/elasticsearch:8.16.0
container_name: elasticsearch
environment:
- discovery.type=single-node
- xpack.security.enabled=false
ports:
- "9200:9200"
volumes:
- elasticsearch-data:/usr/share/elasticsearch/data
kibana:
image: docker.elastic.co/kibana/kibana:8.16.0
container_name: kibana
ports:
- "5601:5601"
environment:
- ELASTICSEARCH_HOSTS=http://elasticsearch:9200
- SERVER_NAME=kibana.example.com
- XPACK_SECURITY_ENABLED=false
depends_on:
- elasticsearch
volumes:
- ./kibana.yml:/usr/share/kibana/config/kibana.yml
volumes:
elasticsearch-data:
EOF
# Package installation (Ubuntu/Debian)
wget -qO - https://artifacts.elastic.co/GPG-KEY-elasticsearch | sudo gpg --dearmor -o /usr/share/keyrings/elasticsearch-keyring.gpg
echo "deb [signed-by=/usr/share/keyrings/elasticsearch-keyring.gpg] https://artifacts.elastic.co/packages/8.x/apt stable main" | sudo tee /etc/apt/sources.list.d/elastic-8.x.list
sudo apt-get update && sudo apt-get install kibana
# Start service
sudo systemctl enable kibana
sudo systemctl start kibana
Configuration File
# kibana.yml
server.port: 5601
server.host: "0.0.0.0"
server.name: "kibana-production"
server.publicBaseUrl: "https://kibana.example.com"
# Elasticsearch configuration
elasticsearch.hosts: ["http://elasticsearch-01:9200", "http://elasticsearch-02:9200"]
elasticsearch.username: "kibana_system"
elasticsearch.password: "your_password_here"
elasticsearch.ssl.verificationMode: certificate
elasticsearch.ssl.certificateAuthorities: ["/etc/kibana/certs/ca.crt"]
elasticsearch.ssl.certificate: "/etc/kibana/certs/kibana.crt"
elasticsearch.ssl.key: "/etc/kibana/certs/kibana.key"
# Security settings
xpack.security.enabled: true
xpack.security.encryptionKey: "your_32_character_encryption_key_here"
xpack.security.session.idleTimeout: "1h"
xpack.security.session.lifespan: "30d"
xpack.security.loginAssistanceMessage: "Please contact your administrator"
# Authentication providers
xpack.security.authc.providers:
basic.basic1:
order: 0
enabled: true
saml.saml1:
order: 1
realm: "saml_realm"
oidc.oidc1:
order: 2
realm: "oidc_realm"
# Logging configuration
logging.level: info
logging.dest: "/var/log/kibana/kibana.log"
logging.rotate.enabled: true
logging.rotate.everyBytes: 10485760 # 10MB
logging.rotate.keepFiles: 7
# Advanced settings
server.maxPayloadBytes: 1048576
server.keepAliveTimeout: 120000
server.socketTimeout: 120000
elasticsearch.requestTimeout: 30000
elasticsearch.shardTimeout: 30000
elasticsearch.pingTimeout: 3000
# Monitoring
monitoring.enabled: true
monitoring.kibana.collection.enabled: true
monitoring.kibana.collection.interval: 10000
# Machine Learning
xpack.ml.enabled: true
xpack.ml.node_concurrent_job_allocations: 2
# Watcher (Alerting)
xpack.watcher.enabled: true
# Maps
xpack.maps.enabled: true
map.includeElasticMapsService: true
# Reporting
xpack.reporting.enabled: true
xpack.reporting.encryptionKey: "your_reporting_encryption_key_here"
xpack.reporting.kibanaServer.hostname: "kibana.example.com"
xpack.reporting.kibanaServer.protocol: "https"
xpack.reporting.kibanaServer.port: 5601
# Canvas
xpack.canvas.enabled: true
# Spaces
xpack.spaces.enabled: true
xpack.spaces.maxSpaces: 1000
# Index lifecycle management
xpack.ilm.enabled: true
# Data views (formerly index patterns)
data.search.aggs.shardDelay.enabled: true
data.search.sessions.enabled: true
# Telemetry
telemetry.enabled: false
telemetry.optIn: false
# Development settings (disable in production)
csp.strict: true
csp.warnLegacyBrowsers: true
Index Pattern and Data View Setup
// Create index pattern via API
const createIndexPattern = async () => {
const response = await fetch('http://localhost:5601/api/saved_objects/index-pattern', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
'kbn-xsrf': 'true'
},
body: JSON.stringify({
attributes: {
title: 'logs-*',
timeFieldName: '@timestamp',
fields: JSON.stringify([
{
name: '@timestamp',
type: 'date',
searchable: true,
aggregatable: true
},
{
name: 'level',
type: 'string',
searchable: true,
aggregatable: true
},
{
name: 'message',
type: 'string',
searchable: true,
aggregatable: false
},
{
name: 'service',
type: 'string',
searchable: true,
aggregatable: true
},
{
name: 'host.name',
type: 'string',
searchable: true,
aggregatable: true
}
])
}
})
});
return response.json();
};
// Create data view with field mappings
const createDataView = async () => {
const response = await fetch('http://localhost:5601/api/data_views/data_view', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
'kbn-xsrf': 'true'
},
body: JSON.stringify({
data_view: {
title: 'application-logs-*',
timeFieldName: '@timestamp',
fieldFormats: {
'response_time': {
id: 'duration',
params: {
inputFormat: 'milliseconds',
outputFormat: 'humanizePrecise'
}
},
'bytes': {
id: 'bytes'
}
},
fieldAttrs: {
'user.ip': {
customLabel: 'User IP Address'
},
'http.status_code': {
customLabel: 'HTTP Status'
}
},
runtimeFieldMap: {
'status_category': {
type: 'keyword',
script: {
source: `
if (doc['http.status_code'].size() > 0) {
int status = doc['http.status_code'].value;
if (status >= 200 && status < 300) {
emit('success');
} else if (status >= 400 && status < 500) {
emit('client_error');
} else if (status >= 500) {
emit('server_error');
} else {
emit('other');
}
}
`
}
}
}
}
})
});
return response.json();
};
Advanced Visualizations
// Create complex aggregation visualization
const createVisualization = async () => {
const visualization = {
title: 'Error Analysis Dashboard',
type: 'lens',
attributes: {
title: 'Error Rate by Service',
visualizationType: 'lnsXY',
state: {
datasourceStates: {
indexpattern: {
layers: {
layer1: {
columnOrder: ['x-axis', 'y-axis', 'breakdown'],
columns: {
'x-axis': {
label: 'Timestamp',
dataType: 'date',
operationType: 'date_histogram',
sourceField: '@timestamp',
isBucketed: true,
scale: 'interval',
params: {
interval: 'auto'
}
},
'y-axis': {
label: 'Error Rate %',
dataType: 'number',
operationType: 'formula',
isBucketed: false,
scale: 'ratio',
params: {
formula: 'count(kql=\\'level:ERROR\\') / count() * 100',
isFormulaBroken: false
},
references: []
},
'breakdown': {
label: 'Service',
dataType: 'string',
operationType: 'terms',
sourceField: 'service',
isBucketed: true,
scale: 'ordinal',
params: {
size: 10,
orderBy: {
type: 'column',
columnId: 'y-axis'
},
orderDirection: 'desc'
}
}
}
}
}
}
},
visualization: {
legend: {
isVisible: true,
position: 'right'
},
valueLabels: 'hide',
fittingFunction: 'Linear',
axisTitlesVisibilitySettings: {
x: true,
yLeft: true,
yRight: true
},
tickLabelsVisibilitySettings: {
x: true,
yLeft: true,
yRight: true
},
gridlinesVisibilitySettings: {
x: true,
yLeft: true,
yRight: true
},
preferredSeriesType: 'line',
layers: [
{
layerId: 'layer1',
accessors: ['y-axis'],
position: 'top',
seriesType: 'line',
showGridlines: false,
xAccessor: 'x-axis',
splitAccessor: 'breakdown'
}
]
},
query: {
query: '',
language: 'kuery'
},
filters: []
}
}
};
const response = await fetch('http://localhost:5601/api/saved_objects/lens', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
'kbn-xsrf': 'true'
},
body: JSON.stringify(visualization)
});
return response.json();
};
Dashboard Creation and Management
// Create comprehensive dashboard
const createDashboard = async () => {
const dashboard = {
attributes: {
title: 'Application Monitoring Dashboard',
hits: 0,
description: 'Comprehensive monitoring dashboard for application logs and metrics',
panelsJSON: JSON.stringify([
{
version: '8.16.0',
type: 'lens',
gridData: {
x: 0,
y: 0,
w: 24,
h: 15,
i: 'panel-1'
},
panelIndex: 'panel-1',
embeddableConfig: {
attributes: {
title: 'Request Volume Over Time',
type: 'lens',
visualizationType: 'lnsXY'
}
},
panelRefName: 'panel_panel-1'
},
{
version: '8.16.0',
type: 'lens',
gridData: {
x: 24,
y: 0,
w: 24,
h: 15,
i: 'panel-2'
},
panelIndex: 'panel-2',
embeddableConfig: {
attributes: {
title: 'Error Rate by Service',
type: 'lens',
visualizationType: 'lnsMetric'
}
}
},
{
version: '8.16.0',
type: 'map',
gridData: {
x: 0,
y: 15,
w: 48,
h: 20,
i: 'panel-3'
},
panelIndex: 'panel-3',
embeddableConfig: {
attributes: {
title: 'Geographic Distribution of Requests',
type: 'map'
}
}
}
]),
optionsJSON: JSON.stringify({
useMargins: true,
syncColors: false,
syncCursor: true,
syncTooltips: false,
hidePanelTitles: false
}),
version: 1,
timeRestore: true,
timeTo: 'now',
timeFrom: 'now-24h',
refreshInterval: {
pause: false,
value: 300000
},
kibanaSavedObjectMeta: {
searchSourceJSON: JSON.stringify({
query: {
query: '',
language: 'kuery'
},
filter: [
{
meta: {
alias: null,
disabled: false,
key: 'environment',
negate: false,
params: {
query: 'production'
},
type: 'phrase'
},
query: {
match_phrase: {
environment: 'production'
}
}
}
]
})
}
}
};
const response = await fetch('http://localhost:5601/api/saved_objects/dashboard', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
'kbn-xsrf': 'true'
},
body: JSON.stringify(dashboard)
});
return response.json();
};
Machine Learning and Anomaly Detection
// Create ML job for anomaly detection
const createMLJob = async () => {
const jobConfig = {
job_id: 'web_traffic_anomaly_detection',
description: 'Detect anomalies in web traffic patterns',
analysis_config: {
bucket_span: '15m',
detectors: [
{
detector_description: 'High request rate',
function: 'high_count',
detector_index: 0
},
{
detector_description: 'Rare status codes',
function: 'rare',
by_field_name: 'http.status_code',
detector_index: 1
},
{
detector_description: 'Unusual response times',
function: 'high_mean',
field_name: 'response_time',
detector_index: 2
}
],
influencers: ['user.ip', 'service', 'http.method']
},
data_description: {
time_field: '@timestamp',
time_format: 'epoch_ms'
},
model_plot_config: {
enabled: true,
terms: 'user.ip,service'
},
analysis_limits: {
model_memory_limit: '512mb',
categorization_examples_limit: 4
},
datafeed_config: {
datafeed_id: 'datafeed-web_traffic_anomaly_detection',
job_id: 'web_traffic_anomaly_detection',
indices: ['logs-nginx-*'],
query: {
bool: {
must: [
{
range: {
'@timestamp': {
gte: 'now-7d'
}
}
}
]
}
},
scroll_size: 1000,
chunking_config: {
mode: 'auto'
}
}
};
const response = await fetch('http://localhost:9200/_ml/anomaly_detectors/web_traffic_anomaly_detection', {
method: 'PUT',
headers: {
'Content-Type': 'application/json'
},
body: JSON.stringify(jobConfig)
});
return response.json();
};
// Create ML datafeed
const createDatafeed = async () => {
const datafeedConfig = {
datafeed_id: 'datafeed-web_traffic_anomaly_detection',
job_id: 'web_traffic_anomaly_detection',
indices: ['logs-nginx-*'],
query: {
bool: {
filter: [
{
term: {
'log.level': 'info'
}
},
{
range: {
'response_time': {
lte: 30000
}
}
}
]
}
},
aggregations: {
buckets: {
date_histogram: {
field: '@timestamp',
fixed_interval: '15m'
},
aggregations: {
'@timestamp': {
max: {
field: '@timestamp'
}
},
request_count: {
value_count: {
field: '_id'
}
},
avg_response_time: {
avg: {
field: 'response_time'
}
},
status_codes: {
terms: {
field: 'http.status_code',
size: 10
}
}
}
}
},
scroll_size: 1000,
frequency: '450s',
query_delay: '60s'
};
const response = await fetch('http://localhost:9200/_ml/datafeeds/datafeed-web_traffic_anomaly_detection', {
method: 'PUT',
headers: {
'Content-Type': 'application/json'
},
body: JSON.stringify(datafeedConfig)
});
return response.json();
};
Alerting and Monitoring
// Create alert rule
const createAlertRule = async () => {
const alertRule = {
name: 'High Error Rate Alert',
consumer: 'alerts',
enabled: true,
alertTypeId: '.es-query',
schedule: {
interval: '1m'
},
params: {
index: ['logs-*'],
timeField: '@timestamp',
esQuery: {
query: {
bool: {
filter: [
{
range: {
'@timestamp': {
gte: 'now-5m'
}
}
},
{
term: {
'level': 'ERROR'
}
}
]
}
}
},
threshold: [10],
thresholdComparator: '>',
termSize: 5,
termField: 'service',
timeWindowSize: 5,
timeWindowUnit: 'm'
},
actions: [
{
id: 'slack-action',
group: 'threshold met',
params: {
message: 'High error rate detected: {{context.value}} errors in the last 5 minutes for service {{context.conditions.0.value}}'
}
},
{
id: 'email-action',
group: 'threshold met',
params: {
to: ['[email protected]'],
subject: 'Alert: High Error Rate',
message: 'Error rate has exceeded threshold. Please investigate.'
}
}
],
tags: ['monitoring', 'errors', 'critical']
};
const response = await fetch('http://localhost:5601/api/alerting/rule', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
'kbn-xsrf': 'true'
},
body: JSON.stringify(alertRule)
});
return response.json();
};
Troubleshooting
# Check Kibana status
sudo systemctl status kibana
curl -I http://localhost:5601/status
# View logs
sudo journalctl -u kibana -f
tail -f /var/log/kibana/kibana.log
# Check Elasticsearch connectivity
curl -X GET "localhost:9200/_cluster/health?pretty"
# Kibana API health check
curl -X GET "localhost:5601/api/status"
# Clear browser cache and cookies
# In browser: F12 -> Application -> Storage -> Clear storage
# Reindex system indices (if corrupted)
curl -X POST "localhost:9200/_reindex?pretty" -H 'Content-Type: application/json' -d'
{
"source": {
"index": ".kibana_old"
},
"dest": {
"index": ".kibana_new"
}
}'
# Reset Kibana configuration
rm -rf /usr/share/kibana/optimize
sudo systemctl restart kibana
# Check index patterns
curl -X GET "localhost:5601/api/saved_objects/_find?type=index-pattern" -H "kbn-xsrf: true"
# Memory usage analysis
ps aux | grep kibana
cat /proc/$(pgrep kibana)/status
# Check Node.js version compatibility
node --version
npm --version
# Validate configuration
/usr/share/kibana/bin/kibana --help
/usr/share/kibana/bin/kibana --config /etc/kibana/kibana.yml --verbose
# Plugin management
/usr/share/kibana/bin/kibana-plugin list
/usr/share/kibana/bin/kibana-plugin install plugin-name
/usr/share/kibana/bin/kibana-plugin remove plugin-name
# Performance monitoring
curl -X GET "localhost:5601/api/stats?extended=true" -H "kbn-xsrf: true"