A vendor-agnostic container storage orchestration engine providing persistent storage for Docker, Kubernetes, and Mesos.
REX-Ray is a container storage orchestration engine that provides persistent storage for cloud-native workloads running on Docker, Kubernetes, and Mesos. It solves the problem of stateful container storage by abstracting storage operations across multiple cloud providers and on-premise systems. The tool enables consistent volume management across different container platforms.
DevOps engineers and platform teams managing containerized applications that require persistent storage across cloud providers and on-premise infrastructure.
Developers choose REX-Ray for its vendor-agnostic approach to container storage, supporting multiple storage platforms through a single orchestration layer. Its flexibility as CLI, service, and Docker plugin makes it adaptable to various deployment scenarios.
REX-Ray is a container storage orchestration engine enabling persistence for cloud native workloads
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Supports multiple providers like AWS EBS, Google Persistent Disk, and Azure, abstracting storage operations from specific cloud APIs, as shown in the detailed provider table.
Provides persistent storage for Docker, Kubernetes, and Mesos, enabling consistent volume management across different orchestration systems.
Available as a CLI tool, Linux service, Go package, and Docker plugin, making it adaptable to various operational scenarios, from local development to production.
Runs on major Linux distributions and macOS for CLI, with service support for Ubuntu, Debian, CentOS, and CoreOS, enhancing cross-platform usability.
The README notes CSI integration is planned for late 2018, so it may not keep pace with evolving container storage standards, limiting compatibility with newer systems.
Requires setting environment variables and provider-specific credentials, which can be error-prone and cumbersome, especially in multi-cloud setups.
Windows is not supported for service mode, as per the OS support table, restricting its use in environments with Windows-based container workloads.