#elk-stack

Implement centralized logging with ELK Stack (Elasticsearch, Logstash, Kibana) for comprehensive log analysis and troubleshooting. ELK Stack architecture: 1. Elasticsearch: distributed search engine, 3-node cluster minimum, data replication factor 1. 2. Logstash: log processing pipeline, input plugins, filters, output destinations. 3. Kibana: data visualization, dashboard creation, alerting, user authentication. 4. Beats: lightweight data shippers (Filebeat, Metricbeat, Packetbeat, Auditbeat). Log collection strategy: 1. Application logs: structured JSON logging, log levels (DEBUG, INFO, WARN, ERROR), correlation IDs. 2. System logs: syslog collection, OS metrics, service status, security events. 3. Infrastructure logs: load balancer access logs, database query logs, container logs. Data lifecycle management: 1. Index management: daily indices, rollover based on size (50GB) or age (1 day). 2. Retention policies: hot (7 days), warm (30 days), cold (90 days), delete after 1 year. 3. Storage optimization: compression, field exclusion, index patterns. Security and access control: 1. X-Pack Security: role-based access, field-level security, audit logging. 2. Encryption: TLS for data in transit, encryption at rest for sensitive data. Monitoring and alerting: 1. Performance metrics: indexing rate (target 10k docs/sec), query response time (<1s). 2. Cluster health: green/yellow/red status monitoring, shard allocation, disk usage. Alert configuration: Watcher for threshold-based alerts, Slack/email notifications, escalation procedures for critical events.