ScyllaDB onKubernetes
In short: Running ScyllaDB on Kubernetes means using the Scylla Operator to deploy ScyllaCluster custom resources as rack-aware StatefulSets, ideally on local-NVMe PersistentVolumes to feed its shard-per-core architecture. The operator handles scaling, streaming rebalance, and rolling upgrades, while Scylla Manager runs scheduled S3 backups and repairs for DR.
Deploy ScyllaDB on Kubernetes with shard-per-core architecture, Scylla Operator automation, and close-to-hardware performance for cloud-native, high-throughput workloads at scale.
Comprehensive ScyllaDB on Kubernetes Services
From Scylla Operator deployment to production monitoring, we provide end-to-end ScyllaDB on Kubernetes solutions for high-performance workloads.
- Scylla Operator installation and CRD setup
- ScyllaCluster custom resource configuration
- Rack-aware pod placement and topology
- Automated rolling upgrades and repairs
- Custom values.yaml for environment tuning
- Multi-environment chart configurations
- Helm release lifecycle management
- GitOps integration with ArgoCD/Flux
- Shard-per-core CPU pinning configuration
- DPDK network stack integration
- IRQ balancing and NUMA awareness
- Resource requests and limits tuning
- Local NVMe SSD provisioning
- PersistentVolumeClaim configuration
- AWS i3/i4i instance optimization
- StorageClass and CSI driver setup
- Scylla Monitoring Stack deployment
- Grafana dashboards for per-shard metrics
- Prometheus ServiceMonitor integration
- Alerting rules and incident response
- Scylla Manager deployment on K8s
- Scheduled S3 snapshot backups
- Cross-datacenter repair scheduling
- Point-in-time restore procedures
Why Choose ScyllaDB on Kubernetes?
ScyllaDB brings close-to-hardware performance to Kubernetes with its shard-per-core architecture, Cassandra compatibility, and 10x throughput advantage.
Shard-Per-Core Architecture
Each CPU core runs an independent shard with its own memory, I/O queues, and network connections. This eliminates lock contention and context switching, delivering predictable low-latency performance even under heavy load.
Cassandra-Compatible
ScyllaDB is a drop-in replacement for Apache Cassandra, supporting CQL, the same drivers, and SSTable format. Migrate existing Cassandra workloads to ScyllaDB on Kubernetes without application changes.
10x Throughput
Written in C++ with a userspace I/O scheduler and optional DPDK network stack, ScyllaDB delivers up to 10x the throughput of Cassandra with significantly lower P99 tail latencies on the same hardware.
Close-to-Hardware Performance
ScyllaDB's Seastar framework bypasses the kernel for I/O and networking, running entirely in userspace. On Kubernetes, this translates to maximum utilization of underlying node resources with minimal overhead.
ScyllaDB on K8s Key Metrics
ScyllaDB vs Cassandra on Kubernetes
Compare ScyllaDB and Apache Cassandra when running on Kubernetes to understand the performance and operational advantages.
Our ScyllaDB on Kubernetes Implementation Process
A proven methodology for deploying production-ready ScyllaDB clusters on Kubernetes with full observability and automation.
Infrastructure Assessment
Evaluate Kubernetes cluster resources, node instance types, storage options, and network topology. Design rack-aware placement and resource allocation strategy for ScyllaDB pods.
Operator & Cluster Deployment
Install the Scylla Operator, configure ScyllaCluster CRDs, set up Helm charts, and deploy ScyllaDB with shard-per-core CPU pinning, NVMe storage, and DPDK networking.
Monitoring & Backup Setup
Deploy the Scylla Monitoring Stack with Grafana dashboards, configure Scylla Manager for automated backups to S3, and set up alerting rules for proactive incident response.
Validation & Go-Live
Run performance benchmarks, validate failover and scaling behavior, execute data migration if needed, and cut over to production with runbooks and 24/7 support.
ScyllaDB on Kubernetes — Frequently Asked Questions
Common questions about deploying and managing ScyllaDB clusters on Kubernetes.