Free Database Audit

Request the Free Audit

StarRocks on Kubernetes

StarRocks on Kubernetes

In short: Running StarRocks on Kubernetes means using the StarRocks Operator to deploy its MPP node types — metadata FE and data-storing BE nodes as StatefulSets with PersistentVolumeClaims, and operator-managed, HPA-scaled CN compute nodes. The operator handles service discovery, rolling upgrades, and rebalancing, with BACKUP/RESTORE to S3 for DR.

Deploy production-grade StarRocks on Kubernetes with the StarRocks Operator, automated scaling of FE/BE/CN nodes, and cloud-native elasticity for sub-second analytical workloads.

Get Started TodayView Architecture
Sub-Second
Analytics
MPP
Engine
MySQL
Compatible

What We Deliver

Comprehensive StarRocks on Kubernetes Services

From operator deployment to production monitoring, we provide end-to-end StarRocks on Kubernetes solutions for cloud-native analytics environments.

StarRocks Operator Deployment

StarRocks Operator setup and configuration for automated cluster lifecycle management on Kubernetes

  • StarRocks Operator installation and CRD setup
  • Custom Resource configuration for FE/BE/CN
  • RBAC and namespace configuration
  • Operator upgrade and version management

Helm Chart Management

Chart customization, values tuning, and upgrade strategies for reproducible StarRocks deployments

  • Helm chart customization and templating
  • Values file tuning for production workloads
  • Chart version upgrade strategies
  • GitOps integration with ArgoCD / Flux

Cluster Management on K8s

FE, BE, and CN node management with topology-aware scheduling and resource optimization

  • FE node HA with leader election
  • BE node scaling and data rebalancing
  • CN compute node auto-scaling
  • Anti-affinity and topology spread

Storage & Persistence

PVCs, StorageClasses, CSI drivers, and high-IOPS volumes for StarRocks data on Kubernetes

  • PVC and StorageClass configuration
  • CSI driver setup (EBS, PD, Ceph)
  • Volume expansion and snapshots
  • High-IOPS storage for analytical workloads

Monitoring & Observability

Prometheus, Grafana, and built-in metrics for full observability of StarRocks clusters on K8s

  • Prometheus ServiceMonitor setup
  • Grafana dashboard provisioning
  • StarRocks built-in metrics integration
  • Alertmanager rules and routing

Backup & Disaster Recovery

Automated backups to S3/HDFS, volume snapshots, and cross-region restore for data protection

  • StarRocks BACKUP/RESTORE automation
  • S3-compatible snapshot storage
  • Scheduled and on-demand backups
  • Cross-region restore testing

Three-Tier Topology

StarRocks Architecture on Kubernetes

Understand the three-tier StarRocks architecture and how each component maps to Kubernetes primitives for optimal performance and reliability.

Query Planning & Metadata

FE Nodes (Frontend)

SQL parsing, query planning, and metadata management

SQL parsing and query optimization
Metadata management and catalog
Leader election for HA
MySQL protocol compatibility
Query scheduling and coordination
User authentication and authorization
Persistent storage for metadata
Deployed as StatefulSet with 3+ replicas

Role: Query coordinator and metadata store

Data Storage & Execution

BE Nodes (Backend)

Data storage, indexing, and vectorized query execution

Columnar data storage engine
Vectorized query execution
Local data caching and indexing
Data ingestion and compaction
Tablet replica management
MPP distributed execution
High-IOPS persistent volumes
Deployed as StatefulSet with PVCs

Role: Data storage and query execution

Elastic Compute

CN Nodes (Compute)

Stateless compute workers for elastic query processing

Stateless compute-only workers
Elastic horizontal scaling
No persistent storage required
Query execution offloading
External table query processing
Data lake federation compute
HPA-based auto-scaling
Operator-managed StatefulSet with HPA-driven elastic scaling

Role: Elastic compute for query bursts

Methodology

Our StarRocks on Kubernetes Implementation Process

A proven methodology for deploying production-ready StarRocks on Kubernetes with comprehensive testing and validation.

01

Assessment & Planning

Evaluate your analytical workload requirements, data volumes, query patterns, and Kubernetes environment. Select the right node topology, storage backend, and resource allocation for FE/BE/CN nodes.

02

Operator & Cluster Setup

Deploy the StarRocks Operator via Helm. Configure custom resources for FE, BE, and CN nodes with appropriate StatefulSets, persistent volumes, networking, and security contexts for production readiness.

03

Data Loading & Validation

Load data using Stream Load, Broker Load, or Routine Load. Validate query performance, test failover scenarios, and benchmark analytical workloads to ensure sub-second response times.

04

Production & Operations

Go live with full monitoring, alerting, automated backups, and runbooks. Provide team training on operator management, CN auto-scaling, day-2 operations, and 24/7 support.

FAQ

StarRocks on Kubernetes — Frequently Asked Questions

Common questions about running StarRocks on Kubernetes in production environments.

Get started

Ready to Run StarRocks on Kubernetes?

Let our experts deploy and manage production StarRocks on Kubernetes with operator-driven automation, elastic CN scaling, and sub-second analytical performance.

Start Your ProjectSchedule Consultation

Related StarRocks Services

Explore more ways our StarRocks experts can help with your database infrastructure.

StarRocks ConsultingStarRocks MigrationStarRocks Performance TuningStarRocks Use Cases
View all StarRocks services