Elasticsearch onKubernetes
Deploy and operate production-grade Elasticsearch clusters on Kubernetes with the ECK operator, auto-scaling, rolling upgrades, and enterprise-grade search infrastructure.
Comprehensive Elasticsearch on Kubernetes Services
From ECK operator deployment to production monitoring, we provide end-to-end Elasticsearch on Kubernetes solutions for search-intensive workloads.
- ECK operator installation and CRD setup
- Custom resource definitions for Elasticsearch
- TLS certificate auto-management
- Secure settings via Kubernetes Secrets
- Custom values.yaml for each environment
- Helm release lifecycle management
- Chart versioning and rollback strategy
- GitOps integration (ArgoCD / Flux)
- Dedicated master-eligible node StatefulSets
- Hot-warm-cold data tier architecture
- Ingest node pipeline configuration
- Coordinating-only nodes for search routing
- PVC-backed StatefulSet storage
- SSD StorageClass selection and tuning
- Volume expansion and resize policies
- Local PV vs network-attached storage
- Kibana deployment and configuration on K8s
- Prometheus Elasticsearch Exporter
- Grafana dashboards for cluster health
- Alerting on shard allocation and node status
- Snapshot lifecycle management (SLM) policies
- S3 / GCS / Azure Blob snapshot repositories
- Automated backup scheduling and retention
- Cross-cluster snapshot restore and DR drills
Why Run Elasticsearch on Kubernetes?
Kubernetes provides the orchestration layer that Elasticsearch needs for automated scaling, self-healing, and declarative cluster management in production environments.
Automated Scaling
Scale data, ingest, and coordinating nodes independently based on workload demands. ECK autoscaling policies combine with Kubernetes HPA/VPA to automatically add or remove Elasticsearch pods as indexing or search traffic fluctuates.
Zero-Downtime Rolling Upgrades
ECK orchestrates rolling upgrades one node at a time, handling shard migration, health checks, and version compatibility validation automatically. Your cluster stays available throughout the entire upgrade process.
Self-Healing Infrastructure
Kubernetes automatically restarts failed Elasticsearch pods, reschedules them to healthy nodes, and maintains the desired replica count. Combined with Elasticsearch's shard replication, this delivers robust fault tolerance.
Declarative Cluster Management
Define your entire Elasticsearch topology as Kubernetes custom resources. Version-control your cluster configuration, enable GitOps workflows, and reproduce identical environments across dev, staging, and production.
Elasticsearch on K8s Key Metrics
ECK Architecture on Kubernetes
Understanding the node roles and Kubernetes resources that make up a production Elasticsearch deployment on K8s.
StatefulSet (3 replicas)Dedicated master-eligible nodes handle cluster state, shard allocation, and index metadata management. Run as a 3-node StatefulSet for quorum.
- Cluster state management
- Shard allocation decisions
- Index creation / deletion
- Lightweight resource footprint
StatefulSet (scalable)Data nodes store index shards and execute search and indexing operations. Sized with high storage and memory, scaled horizontally based on data volume.
- Hot / warm / cold tiering
- PVC-backed persistent storage
- CPU and memory intensive
- Horizontal auto-scaling
Deployment (scalable)Ingest nodes run preprocessing pipelines (grok, dissect, enrichment) before documents are indexed. Isolate pipeline load from data node resources.
- Ingest pipeline execution
- Document enrichment
- Grok / dissect parsing
- Independent scaling
Deployment (scalable)Coordinating-only nodes act as smart load balancers, routing search requests and aggregating results across data nodes without holding data.
- Search request routing
- Scatter-gather aggregation
- Client-facing endpoints
- Reduce data node load
Our Elasticsearch on Kubernetes Implementation Process
A proven methodology for deploying production-ready Elasticsearch clusters on Kubernetes with comprehensive testing and validation.
Architecture & Planning
Analyze search and indexing workloads, data volume, and query patterns. Design cluster topology, node roles, storage classes, and resource quotas for your Kubernetes environment.
ECK Deployment
Deploy the ECK operator, configure Elasticsearch custom resources, set up TLS, Kubernetes Secrets for credentials, and provision PersistentVolumes with appropriate StorageClasses.
Integration & Testing
Integrate with ingestion pipelines (Logstash, Beats, Filebeat), deploy Kibana, configure index templates, run failover tests, and benchmark indexing throughput and query latency.
Production & Operations
Go live with monitoring, alerting, snapshot policies, and auto-scaling. Provide runbooks, on-call playbooks, and ongoing support for rolling upgrades and capacity planning.
Elasticsearch on Kubernetes — Frequently Asked Questions
Common questions about deploying and operating Elasticsearch on Kubernetes with ECK.