Configure ELK Stack for Production

ELK Stack Configuration guides log-management setup across Elasticsearch, Logstash, and Kibana. It connects cluster discovery and resource settings with ingestion pipelines, index mappings, retention phases, secure access, and monitoring. The examples are configuration patterns for building a reliable, scalable, and secure logging solution.

Elasticsearch guidance covers production cluster parameters, heap sizing, multi-node discovery, index lifecycle management, and dedicated master nodes for larger clusters. The sample configuration defines node roles, network ports, discovery hosts, memory locking, index buffer allocation, transport and HTTP encryption, and monitoring collection. A log index template specifies shard and replica settings, lifecycle linkage, a rollover alias, and mappings for timestamp, severity, message, host, and service fields.

Logstash follows an input-filter-output design. Its multi-input example accepts Beats, TCP syslog, and HTTP webhook traffic. Conditional filters parse syslog with grok, derive a service field, decode JSON messages, add IP geolocation, and remove unwanted fields. Output routes events into dated Elasticsearch indices, with a conditional debug stream. Error handling and dead letter queues are part of the pipeline design guidance.

The lifecycle example lays out hot, warm, cold, and delete phases, including rollover limits, age thresholds, allocation, and priority changes. Kibana configuration covers its server, encrypted Elasticsearch connections, system credentials, encryption settings, certificates, and file logging.

Use this skill when creating or tuning a centralized ELK logging environment with multiple log formats, retention needs, and access controls. The operational guidance calls for staging tests before configuration reaches production, backups for critical indices, and monitoring of the stack's own components.

The examples contain environment-specific cluster names, paths, credentials references, and resource settings. They require adaptation to the deployment rather than being treated as universally suitable values. Production security calls for authentication, authorization, RBAC, and encrypted communications across the components.

Inputs include node topology, log sources, field schemas, retention requirements, certificates, authentication settings, and ingestion volume. Outputs are Elasticsearch, Logstash, and Kibana configuration patterns plus index templates and lifecycle policies. Pipeline settings can separate workload processing:

- pipeline.id: main
  path.config: "/usr/share/logstash/pipeline/logstash.conf"
  pipeline.workers: 4
  pipeline.batch.size: 1000
  pipeline.batch.delay: 50

Operational checks include cluster health, CPU, memory, disk use, and ingestion rates. Tuning covers refresh intervals, shard sizes, worker counts, and hot-warm-cold storage architecture. Credential rotation, network segmentation, firewall rules, audit logging, trusted certificates, centralized component logs, and index aliases complement the configuration examples.

The patterns connect Beats, TCP, and HTTP inputs to Logstash and Elasticsearch, with Kibana accessing the cluster over HTTPS. Ansible and Puppet support configuration management for keeping deployments consistent.