Dragonfly onKubernetes
In short: Running Dragonfly on Kubernetes means using the Dragonfly Operator to provision Dragonfly custom resources as StatefulSets, Services, and PersistentVolumeClaims for snapshot/AOF persistence. The operator manages primary-replica replication with automatic failover for HA, plus rolling zero-downtime updates — exposing a Redis- and Memcached-compatible API for drop-in migration.
Deploy Dragonfly on Kubernetes for a modern, multi-threaded in-memory datastore with Redis-compatible API, 25x throughput over Redis, and lower memory usage — fully managed with the Dragonfly Operator.
Comprehensive Dragonfly on Kubernetes Services
From initial deployment to production optimization, we provide end-to-end Dragonfly on Kubernetes solutions for high-performance in-memory workloads.
- Dragonfly Operator CRD installation
- Custom resource configuration
- RBAC and service account setup
- Namespace isolation and multi-tenancy
- Helm chart customization and tuning
- Values file management per environment
- Chart versioning and rollback strategy
- GitOps integration (ArgoCD / Flux)
- Primary-replica replication setup
- Automatic failover orchestration
- Pod anti-affinity and topology spread
- Multi-AZ deployment strategies
- RDB-compatible snapshot configuration
- Append-only file (AOF) persistence
- PVC storage class optimization
- Fork-free snapshot (no memory spike)
- Prometheus metrics exporter setup
- Grafana dashboard templates
- Alertmanager rules for key metrics
- Resource usage and latency tracking
- Redis-to-Dragonfly replication setup
- Application endpoint cutover planning
- Data validation and consistency checks
- Rollback strategy and testing
Why Choose Dragonfly on Kubernetes?
Dragonfly delivers a modern, multi-threaded alternative to Redis with dramatically higher throughput, lower memory usage, and full Redis API compatibility — all on Kubernetes.
Multi-Threaded Architecture
Unlike single-threaded Redis, Dragonfly utilizes all available CPU cores with a shared-nothing, per-thread memory design. Each thread manages its own keyspace partition, eliminating lock contention and delivering linear scaling with core count.
Redis & Memcached Compatible
Dragonfly supports both Redis (RESP) and Memcached protocols. Existing applications, client libraries, and tooling work without modification. Switch from Redis or Memcached with zero code changes.
25x Throughput Over Redis
Benchmarks show Dragonfly achieving up to 25x the throughput of Redis on equivalent hardware. This is achieved through multi-threading, io_uring for async I/O, and a cache-friendly dashtable hash structure.
Lower Memory Usage
Dragonfly uses more efficient memory encoding and eliminates the fork-based snapshot overhead that causes Redis memory to spike during BGSAVE. The same dataset typically uses significantly less RAM in Dragonfly.
Dragonfly Key Metrics
Dragonfly vs Redis on Kubernetes
Understanding the architectural differences that make Dragonfly a compelling alternative to Redis for high-throughput Kubernetes workloads.
Our Dragonfly on Kubernetes Implementation Process
A proven methodology for deploying production-ready Dragonfly on Kubernetes with comprehensive testing and validation.
Assessment & Planning
Analyze your current Redis/Memcached workload, throughput requirements, and data model. Design the Dragonfly topology, resource requests, and storage strategy for Kubernetes.
Operator & Deployment
Install the Dragonfly Operator, deploy Dragonfly instances via Helm or CRDs, configure persistence, resource limits, and network policies on your Kubernetes cluster.
Migration & Testing
Replicate data from Redis to Dragonfly, validate application compatibility, run load tests to confirm throughput gains, and test failover scenarios.
Production & Monitoring
Cut over production traffic to Dragonfly, enable Prometheus monitoring and Grafana dashboards, configure alerting, and provide ongoing operational support.
Dragonfly on Kubernetes — Frequently Asked Questions
Common questions about Dragonfly deployment, migration from Redis, and Kubernetes integration.