

Kubernetes has become the platform of choice for modern, containerized applications. However, delivering high-performance, persistent storage that retains the portability and simplicity of Kubernetes is a major challenge—especially for stateful workloads.
This cloud-native storage solution is designed to deliver the performance of local NVMe flash, combined with the flexibility of disaggregated, software-defined storage, and the simplicity of standard TCP/IP networking. It allows developers and operators to run high-performance, stateful applications without compromising Kubernetes agility, resiliency, or efficiency.
Our solution boosts performance, flexibility, and scalability. With technologies like Elastic RAID, Kubernetes integration, and storage flexibility, it optimizes infrastructure. Explore features that ensure seamless operations, fast recovery, and cost efficiency across hybrid and multi-cloud environments.
✔️ Offers the same or better performance as direct-attached NVMe
✔️ No CPU/network overhead from pod migration or application replication
✔️ Utilizes standard 25–100 Gbps Ethernet
✔️ Elastic RAID ensures rapid, local rebuilds without network saturation
✔️ Supports 2x and 3x replication across target nodes
✔️ Runs on any x86 platform with no proprietary components
✔️ Integrates via CSI, using familiar Kubernetes storage APIs
✔️ Fully compatible with major Kubernetes distributions (upstream, OpenShift, Tanzu, etc.)
✔️ Increases flash utilization from 15–25% to much higher efficiency
✔️ Supports QLC NAND through intelligent wear-leveling and reduced write pressure
✔️ Delivers up to 10:1 data reduction with compression and thin provisioning
✔️ Fast clones and snapshots for dynamic environments
✔️ Ideal for CI/CD, data science notebooks, and test environments
Replaced local NVMe with Lightbits NVMe/TCP and CSI stack; achieved better performance, increased resiliency, and reduced hardware sprawl
Enabled secure, persistent volumes for PostgreSQL and Kafka in Kubernetes without modifying network architecture
Accelerated training and inference workloads by using Lightbits storage for large-scale TensorFlow and PyTorch jobs running on Kubernetes, while reducing job restart times after node failures
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