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Deploy and manage the ELK Stack (Elasticsearch, Logstash, Kibana) for log aggregation and analysis.
---
name: elk-stack
description: Deploy and manage the ELK Stack (Elasticsearch, Logstash, Kibana) for
log aggregation and analysis.
category: devops
risk: critical
source: https://github.com/BagelHole/DevOps-Security-Agent-Skills
source_repo: BagelHole/DevOps-Security-Agent-Skills
source_type: community
date_added: '2026-09-20'
license: MIT
license_source: https://github.com/BagelHole/DevOps-Security-Agent-Skills/blob/main/LICENSE
compatibility: Requires the relevant platform CLIs (kubectl, helm, terraform, git,
CI runners) and authorized access to the target environment. Docs-only; helper scripts
and templates not bundled.
metadata:
author: devops-skills
version: '1.0'
---
# ELK Stack
Centralize and analyze logs with Elasticsearch, Logstash, and Kibana.
## When to Use This Skill
Use this skill when:
- Centralizing logs from multiple sources
- Building log search and analytics platforms
- Creating log-based dashboards and alerts
- Implementing full-text search for logs
- Processing and transforming log data
## Prerequisites
- Docker or server infrastructure
- Sufficient disk space for log storage
- Network access from log sources
## Lab and production boundaries
The Compose file is a local disposable lab with Elasticsearch security disabled; loopback binding does not make it appropriate for shared networks. Production needs verified compatible patched versions, authentication/TLS between components, least-privilege ingestion and reviewed retention. A read-only docker.sock mount still exposes daemon API capabilities; omit it or use a restricted proxy. Redact secrets/PII before ingestion and restrict dashboards/exported logs. Watcher/webhook creation sends recurring external messages and requires the corresponding user instruction. ILM snippets are version-dependent and need a correctly bootstrapped rollover alias/data stream; date-named Logstash indices do not automatically satisfy that contract.
## Docker Deployment
```yaml
# docker-compose.yml
version: '3.8'
services:
elasticsearch:
image: docker.elastic.co/elasticsearch/elasticsearch:8.11.0
environment:
- discovery.type=single-node
- xpack.security.enabled=false
- "ES_JAVA_OPTS=-Xms1g -Xmx1g"
ports:
- "127.0.0.1:9200:9200"
volumes:
- elasticsearch-data:/usr/share/elasticsearch/data
logstash:
image: docker.elastic.co/logstash/logstash:8.11.0
volumes:
- ./logstash/pipeline:/usr/share/logstash/pipeline
- ./logstash/config:/usr/share/logstash/config
ports:
- "127.0.0.1:5044:5044"
- "127.0.0.1:5000:5000"
depends_on:
- elasticsearch
kibana:
image: docker.elastic.co/kibana/kibana:8.11.0
ports:
- "127.0.0.1:5601:5601"
environment:
- ELASTICSEARCH_HOSTS=http://elasticsearch:9200
depends_on:
- elasticsearch
filebeat:
image: docker.elastic.co/beats/filebeat:8.11.0
user: root
volumes:
- ./filebeat/filebeat.yml:/usr/share/filebeat/filebeat.yml:ro
- /var/lib/docker/containers:/var/lib/docker/containers:ro
- /var/run/docker.sock:/var/run/docker.sock:ro
depends_on:
- logstash
volumes:
elasticsearch-data:
```
## Elasticsearch Configuration
### Index Templates
```json
PUT _index_template/logs-template
{
"index_patterns": ["logs-*"],
"template": {
"settings": {
"number_of_shards": 1,
"number_of_replicas": 1,
"index.lifecycle.name": "logs-policy"
},
"mappings": {
"properties": {
"@timestamp": { "type": "date" },
"message": { "type": "text" },
"level": { "type": "keyword" },
"service": { "type": "keyword" },
"host": { "type": "keyword" },
"trace_id": { "type": "keyword" }
}
}
}
}
```
### Index Lifecycle Management
```json
PUT _ilm/policy/logs-policy
{
"policy": {
"phases": {
"hot": {
"min_age": "0ms",
"actions": {
"rollover": {
"max_size": "50GB",
"max_age": "1d"
}
}
},
"warm": {
"min_age": "7d",
"actions": {
"shrink": { "number_of_shards": 1 },
"forcemerge": { "max_num_segments": 1 }
}
},
"cold": {
"min_age": "30d",
"actions": {
"freeze": {}
}
},
"delete": {
"min_age": "90d",
"actions": {
"delete": {}
}
}
}
}
}
```
## Logstash Pipeline
### Basic Pipeline
```ruby
# logstash/pipeline/main.conf
input {
beats {
port => 5044
}
tcp {
port => 5000
codec => json_lines
}
}
filter {
# Parse JSON logs
if [message] =~ /^\{/ {
json {
source => "message"
}
}
# Parse timestamp
date {
match => ["timestamp", "ISO8601", "yyyy-MM-dd HH:mm:ss"]
target => "@timestamp"
}
# Add environment tag
mutate {
add_field => { "environment" => "production" }
}
# Grok pattern for nginx logs
if [type] == "nginx" {
grok {
match => {
"message" => '%{IPORHOST:client_ip} - %{USER:user} \[%{HTTPDATE:timestamp}\] "%{WORD:method} %{URIPATHPARAM:request} HTTP/%{NUMBER:http_version}" %{NUMBER:status} %{NUMBER:bytes}'
}
}
}
}
output {
elasticsearch {
hosts => ["elasticsearch:9200"]
index => "logs-%{+YYYY.MM.dd}"
}
}
```
### Advanced Filtering
```ruby
filter {
# Parse application logs
grok {
match => {
"message" => "%{TIMESTAMP_ISO8601:timestamp} %{LOGLEVEL:level} \[%{DATA:service}\] %{GREEDYDATA:log_message}"
}
}
# Extract trace ID from message
if [log_message] =~ /trace_id=/ {
grok {
match => { "log_message" => "trace_id=%{UUID:trace_id}" }
}
}
# GeoIP lookup
if [client_ip] {
geoip {
source => "client_ip"
target => "geoip"
}
}
# Drop debug logs in production
if [level] == "DEBUG" and [environment] == "production" {
drop {}
}
# Enrich with lookup
translate {
field => "status"
destination => "status_description"
dictionary => {
"200" => "OK"
"404" => "Not Found"
"500" => "Internal Server Error"
}
}
}
```
## Filebeat Configuration
```yaml
# filebeat/filebeat.yml
filebeat.inputs:
- type: container
paths:
- '/var/lib/docker/containers/*/*.log'
processors:
- add_docker_metadata:
host: "unix:///var/run/docker.sock"
- type: log
enabled: true
paths:
- /var/log/nginx/*.log
tags: ["nginx"]
fields:
type: nginx
output.logstash:
hosts: ["logstash:5044"]
logging.level: info
logging.to_files: true
logging.files:
path: /var/log/filebeat
name: filebeat
keepfiles: 7
```
## Elasticsearch Queries
### Basic Queries
```json
// Search all logs
GET logs-*/_search
{
"query": {
"match_all": {}
}
}
// Search by keyword
GET logs-*/_search
{
"query": {
"match": {
"message": "error"
}
}
}
// Filter by field
GET logs-*/_search
{
"query": {
"bool": {
"must": [
{ "match": { "level": "ERROR" } },
{ "range": { "@timestamp": { "gte": "now-1h" } } }
],
"filter": [
{ "term": { "service": "api-gateway" } }
]
}
}
}
```
### Aggregations
```json
// Count by log level
GET logs-*/_search
{
"size": 0,
"aggs": {
"log_levels": {
"terms": { "field": "level" }
}
}
}
// Error rate over time
GET logs-*/_search
{
"size": 0,
"aggs": {
"errors_over_time": {
"date_histogram": {
"field": "@timestamp",
"fixed_interval": "5m"
},
"aggs": {
"error_count": {
"filter": { "term": { "level": "ERROR" } }
}
}
}
}
}
```
## Kibana Setup
### Index Patterns
1. Go to Stack Management → Index Patterns
2. Create pattern: `logs-*`
3. Set time field: `@timestamp`
### Saved Searches
Create saved searches for common queries:
- `level:ERROR` - All errors
- `service:api-gateway AND level:ERROR` - API gateway errors
- `response_time:>1000` - Slow requests
### Visualizations
Common visualization types:
- **Line Chart**: Error rate over time
- **Pie Chart**: Distribution by log level
- **Data Table**: Top error messages
- **Metric**: Total error count
### Dashboard Example
Create dashboard with:
1. Total log count (Metric)
2. Error rate trend (Line chart)
3. Logs by service (Pie chart)
4. Recent errors (Data table)
5. Log stream (Discover panel)
## Alerting
### Watcher (X-Pack)
```json
PUT _watcher/watch/error_alert
{
"trigger": {
"schedule": { "interval": "5m" }
},
"input": {
"search": {
"request": {
"indices": ["logs-*"],
"body": {
"query": {
"bool": {
"must": [
{ "match": { "level": "ERROR" } },
{ "range": { "@timestamp": { "gte": "now-5m" } } }
]
}
}
}
}
}
},
"condition": {
"compare": { "ctx.payload.hits.total.value": { "gt": 100 } }
},
"actions": {
"notify_slack": {
"webhook": {
"scheme": "https",
"host": "hooks.slack.com",
"port": 443,
"method": "post",
"path": "/services/xxx",
"body": "{\"text\": \"High error rate detected: {{ctx.payload.hits.total.value}} errors in last 5 minutes\"}"
}
}
}
}
```
## Common Issues
### Issue: High Disk Usage
**Problem**: Elasticsearch consuming too much disk
**Solution**: Implement ILM policies, reduce retention
### Issue: Slow Searches
**Problem**: Queries taking too long
**Solution**: Optimize index settings, add more shards, use filters
### Issue: Log Parsing Failures
**Problem**: Logs not parsed correctly
**Solution**: Test grok patterns, check for log format changes
### Issue: Memory Pressure
**Problem**: Elasticsearch OOM errors
**Solution**: Increase heap size (max 50% of RAM), limit field data
## Best Practices
- Implement index lifecycle management
- Use index templates for consistent mappings
- Parse logs at ingestion time
- Limit stored fields to reduce storage
- Use data streams for time-series data
- Monitor cluster health
- Implement proper security (X-Pack)
- Regular index maintenance
## Related Skills
- loki-logging (`loki-logging`) - Alternative logging stack
- prometheus-grafana (`prometheus-grafana`) - Metrics monitoring
- audit-logging (`audit-logging`) - Compliance logging
## Limitations
- Guidance executes against real environments: confirm target, blast radius, and rollback plan before applying anything.
- Never deploy to production without explicit approval. Docs-only import: upstream scripts and templates not bundled.
### Example
```bash
git status && git diff --stat
kubectl diff -f manifest.yaml
```
> Adapted from [BagelHole/DevOps-Security-Agent-Skills](https://github.com/BagelHole/DevOps-Security-Agent-Skills) (MIT); frontmatter, When to Use/Limitations, and safety boundaries added for upstream compliance. Docs-only import: helper scripts and templates not bundled.
---
name: elk-stack
description: Deploy and manage the ELK Stack (Elasticsearch, Logstash, Kibana) for
log aggregation and analysis.
category: devops
risk: critical
source: https://github.com/BagelHole/DevOps-Security-Agent-Skills
source_repo: BagelHole/DevOps-Security-Agent-Skills
source_type: community
date_added: '2026-09-20'
license: MIT
license_source: https://github.com/BagelHole/DevOps-Security-Agent-Skills/blob/main/LICENSE
compatibility: Requires the relevant platform CLIs (kubectl, helm, terraform, git,
CI runners) and authorized access to the target environment. Docs-only; helper scripts
and templates not bundled.
metadata:
author: devops-skills
version: '1.0'
---
# ELK Stack
Centralize and analyze logs with Elasticsearch, Logstash, and Kibana.
## When to Use This Skill
Use this skill when:
- Centralizing logs from multiple sources
- Building log search and analytics platforms
- Creating log-based dashboards and alerts
- Implementing full-text search for logs
- Processing and transforming log data
## Prerequisites
- Docker or server infrastructure
- Sufficient disk space for log storage
- Network access from log sources
## Lab and production boundaries
The Compose file is a local disposable lab with Elasticsearch security disabled; loopback binding does not make it appropriate for shared networks. Production needs verified compatible patched versions, authentication/TLS between components, least-privilege ingestion and reviewed retention. A read-only docker.sock mount still exposes daemon API capabilities; omit it or use a restricted proxy. Redact secrets/PII before ingestion and restrict dashboards/exported logs. Watcher/webhook creation sends recurring external messages and requires the corresponding user instruction. ILM snippets are version-dependent and need a correctly bootstrapped rollover alias/data stream; date-named Logstash indices do not automatically satisfy that contract.
## Docker Deployment
```yaml
# docker-compose.yml
version: '3.8'
services:
elasticsearch:
image: docker.elastic.co/elasticsearch/elasticsearch:8.11.0
environment:
- discovery.type=single-node
- xpack.security.enabled=false
- "ES_JAVA_OPTS=-Xms1g -Xmx1g"
ports:
- "127.0.0.1:9200:9200"
volumes:
- elasticsearch-data:/usr/share/elasticsearch/data
logstash:
image: docker.elastic.co/logstash/logstash:8.11.0
volumes:
- ./logstash/pipeline:/usr/share/logstash/pipeline
- ./logstash/config:/usr/share/logstash/config
ports:
- "127.0.0.1:5044:5044"
- "127.0.0.1:5000:5000"
depends_on:
- elasticsearch
kibana:
image: docker.elastic.co/kibana/kibana:8.11.0
ports:
- "127.0.0.1:5601:5601"
environment:
- ELASTICSEARCH_HOSTS=http://elasticsearch:9200
depends_on:
- elasticsearch
filebeat:
image: docker.elastic.co/beats/filebeat:8.11.0
user: root
volumes:
- ./filebeat/filebeat.yml:/usr/share/filebeat/filebeat.yml:ro
- /var/lib/docker/containers:/var/lib/docker/containers:ro
- /var/run/docker.sock:/var/run/docker.sock:ro
depends_on:
- logstash
volumes:
elasticsearch-data:
```
## Elasticsearch Configuration
### Index Templates
```json
PUT _index_template/logs-template
{
"index_patterns": ["logs-*"],
"template": {
"settings": {
"number_of_shards": 1,
"number_of_replicas": 1,
"index.lifecycle.name": "logs-policy"
},
"mappings": {
"properties": {
"@timestamp": { "type": "date" },
"message": { "type": "text" },
"level": { "type": "keyword" },
"service": { "type": "keyword" },
"host": { "type": "keyword" },
"trace_id": { "type": "keyword" }
}
}
}
}
```
### Index Lifecycle Management
```json
PUT _ilm/policy/logs-policy
{
"policy": {
"phases": {
"hot": {
"min_age": "0ms",
"actions": {
"rollover": {
"max_size": "50GB",
"max_age": "1d"
}
}
},
"warm": {
"min_age": "7d",
"actions": {
"shrink": { "number_of_shards": 1 },
"forcemerge": { "max_num_segments": 1 }
}
},
"cold": {
"min_age": "30d",
"actions": {
"freeze": {}
}
},
"delete": {
"min_age": "90d",
"actions": {
"delete": {}
}
}
}
}
}
```
## Logstash Pipeline
### Basic Pipeline
```ruby
# logstash/pipeline/main.conf
input {
beats {
port => 5044
}
tcp {
port => 5000
codec => json_lines
}
}
filter {
# Parse JSON logs
if [message] =~ /^\{/ {
json {
source => "message"
}
}
# Parse timestamp
date {
match => ["timestamp", "ISO8601", "yyyy-MM-dd HH:mm:ss"]
target => "@timestamp"
}
# Add environment tag
mutate {
add_field => { "environment" => "production" }
}
# Grok pattern for nginx logs
if [type] == "nginx" {
grok {
match => {
"message" => '%{IPORHOST:client_ip} - %{USER:user} \[%{HTTPDATE:timestamp}\] "%{WORD:method} %{URIPATHPARAM:request} HTTP/%{NUMBER:http_version}" %{NUMBER:status} %{NUMBER:bytes}'
}
}
}
}
output {
elasticsearch {
hosts => ["elasticsearch:9200"]
index => "logs-%{+YYYY.MM.dd}"
}
}
```
### Advanced Filtering
```ruby
filter {
# Parse application logs
grok {
match => {
"message" => "%{TIMESTAMP_ISO8601:timestamp} %{LOGLEVEL:level} \[%{DATA:service}\] %{GREEDYDATA:log_message}"
}
}
# Extract trace ID from message
if [log_message] =~ /trace_id=/ {
grok {
match => { "log_message" => "trace_id=%{UUID:trace_id}" }
}
}
# GeoIP lookup
if [client_ip] {
geoip {
source => "client_ip"
target => "geoip"
}
}
# Drop debug logs in production
if [level] == "DEBUG" and [environment] == "production" {
drop {}
}
# Enrich with lookup
translate {
field => "status"
destination => "status_description"
dictionary => {
"200" => "OK"
"404" => "Not Found"
"500" => "Internal Server Error"
}
}
}
```
## Filebeat Configuration
```yaml
# filebeat/filebeat.yml
filebeat.inputs:
- type: container
paths:
- '/var/lib/docker/containers/*/*.log'
processors:
- add_docker_metadata:
host: "unix:///var/run/docker.sock"
- type: log
enabled: true
paths:
- /var/log/nginx/*.log
tags: ["nginx"]
fields:
type: nginx
output.logstash:
hosts: ["logstash:5044"]
logging.level: info
logging.to_files: true
logging.files:
path: /var/log/filebeat
name: filebeat
keepfiles: 7
```
## Elasticsearch Queries
### Basic Queries
```json
// Search all logs
GET logs-*/_search
{
"query": {
"match_all": {}
}
}
// Search by keyword
GET logs-*/_search
{
"query": {
"match": {
"message": "error"
}
}
}
// Filter by field
GET logs-*/_search
{
"query": {
"bool": {
"must": [
{ "match": { "level": "ERROR" } },
{ "range": { "@timestamp": { "gte": "now-1h" } } }
],
"filter": [
{ "term": { "service": "api-gateway" } }
]
}
}
}
```
### Aggregations
```json
// Count by log level
GET logs-*/_search
{
"size": 0,
"aggs": {
"log_levels": {
"terms": { "field": "level" }
}
}
}
// Error rate over time
GET logs-*/_search
{
"size": 0,
"aggs": {
"errors_over_time": {
"date_histogram": {
"field": "@timestamp",
"fixed_interval": "5m"
},
"aggs": {
"error_count": {
"filter": { "term": { "level": "ERROR" } }
}
}
}
}
}
```
## Kibana Setup
### Index Patterns
1. Go to Stack Management → Index Patterns
2. Create pattern: `logs-*`
3. Set time field: `@timestamp`
### Saved Searches
Create saved searches for common queries:
- `level:ERROR` - All errors
- `service:api-gateway AND level:ERROR` - API gateway errors
- `response_time:>1000` - Slow requests
### Visualizations
Common visualization types:
- **Line Chart**: Error rate over time
- **Pie Chart**: Distribution by log level
- **Data Table**: Top error messages
- **Metric**: Total error count
### Dashboard Example
Create dashboard with:
1. Total log count (Metric)
2. Error rate trend (Line chart)
3. Logs by service (Pie chart)
4. Recent errors (Data table)
5. Log stream (Discover panel)
## Alerting
### Watcher (X-Pack)
```json
PUT _watcher/watch/error_alert
{
"trigger": {
"schedule": { "interval": "5m" }
},
"input": {
"search": {
"request": {
"indices": ["logs-*"],
"body": {
"query": {
"bool": {
"must": [
{ "match": { "level": "ERROR" } },
{ "range": { "@timestamp": { "gte": "now-5m" } } }
]
}
}
}
}
}
},
"condition": {
"compare": { "ctx.payload.hits.total.value": { "gt": 100 } }
},
"actions": {
"notify_slack": {
"webhook": {
"scheme": "https",
"host": "hooks.slack.com",
"port": 443,
"method": "post",
"path": "/services/xxx",
"body": "{\"text\": \"High error rate detected: {{ctx.payload.hits.total.value}} errors in last 5 minutes\"}"
}
}
}
}
```
## Common Issues
### Issue: High Disk Usage
**Problem**: Elasticsearch consuming too much disk
**Solution**: Implement ILM policies, reduce retention
### Issue: Slow Searches
**Problem**: Queries taking too long
**Solution**: Optimize index settings, add more shards, use filters
### Issue: Log Parsing Failures
**Problem**: Logs not parsed correctly
**Solution**: Test grok patterns, check for log format changes
### Issue: Memory Pressure
**Problem**: Elasticsearch OOM errors
**Solution**: Increase heap size (max 50% of RAM), limit field data
## Best Practices
- Implement index lifecycle management
- Use index templates for consistent mappings
- Parse logs at ingestion time
- Limit stored fields to reduce storage
- Use data streams for time-series data
- Monitor cluster health
- Implement proper security (X-Pack)
- Regular index maintenance
## Related Skills
- loki-logging (`loki-logging`) - Alternative logging stack
- prometheus-grafana (`prometheus-grafana`) - Metrics monitoring
- audit-logging (`audit-logging`) - Compliance logging
## Limitations
- Guidance executes against real environments: confirm target, blast radius, and rollback plan before applying anything.
- Never deploy to production without explicit approval. Docs-only import: upstream scripts and templates not bundled.
### Example
```bash
git status && git diff --stat
kubectl diff -f manifest.yaml
```
> Adapted from [BagelHole/DevOps-Security-Agent-Skills](https://github.com/BagelHole/DevOps-Security-Agent-Skills) (MIT); frontmatter, When to Use/Limitations, and safety boundaries added for upstream compliance. Docs-only import: helper scripts and templates not bundled.
Imported SKILL.md format for Claude Code, Codex and Cursor. Review the complete instructions and required tools before use. Package integrity checked; individual agent behavior has not been tested.