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Project Vision

KDSS was created to address the growing gap between storage capacity demands and infrastructure budgets. Traditional 3-way replication wastes 200% of raw storage capacity. By leveraging Reed-Solomon erasure coding at its core, KDSS achieves up to 90.6% space efficiency while maintaining the same level of data durability -- enabling organizations to store more data with fewer disks, lower power consumption, and reduced operational costs.

Target Use Cases

  • Large-scale unstructured data storage (media, backups, logs, archives)
  • Cost-sensitive environments requiring high durability without 3x replication overhead
  • Hybrid cloud storage with S3-compatible API and POSIX filesystem access
  • AI/ML training data pipelines requiring high-throughput sequential reads
  • On-premises object storage as an alternative to public cloud services

Technology Stack

Built with proven, high-performance technologies.

Go

Core language for all services. High concurrency, low latency, single binary deployment.

gRPC

High-performance RPC framework for inter-node communication with streaming support.

Protocol Buffers

Efficient binary serialization for metadata and wire protocol definitions.

MongoDB

Flexible document store for metadata management with replica set support.

Reed-Solomon

Erasure coding algorithm for data protection with configurable redundancy levels.

BadgerDB

Embedded key-value store for local index and cache management on storage nodes.

FUSE

Filesystem in Userspace for POSIX-compatible mounting without kernel modules.

Prometheus

Metrics collection and alerting with 32 built-in alert rules for cluster monitoring.

Grafana

Pre-built dashboards for real-time visualization of cluster health and performance.

Roadmap

Upcoming features and milestones for the KDSS project.

Multi-region Replication

Asynchronous cross-region replication for disaster recovery. Replicate EC-encoded data across geographically distributed clusters with configurable consistency policies.

Tiered Storage

Automatic data lifecycle management with hot/warm/cold tiers. Migrate data between NVMe, SSD, and HDD based on access patterns and configurable policies.

Kubernetes Operator

Native Kubernetes operator for declarative cluster management. Automated scaling, rolling upgrades, and CSI driver integration for persistent volumes.

Encryption at Rest

Server-side encryption with AES-256-GCM. Support for external key management systems (KMS) including HashiCorp Vault and AWS KMS integration.

Get Involved

Join the KDSS community and help shape the future of distributed storage.