OpenEBS is a CNCF sandbox project providing container-native persistent storage for Kubernetes. This repository is the project's coordination hub: it contains the umbrella Helm chart for deploying OpenEBS (LocalPV hostpath/LVM/ZFS and Mayastor replicated engines), the kubectl-openebs plugin binary for inspecting and managing volumes and nodes, and the openebs-upgrade job for Helm-based upgrades and Mayastor data-plane rolling restarts. It also houses the OpenEBS Enhancement Proposals (OEPs), CI/CD workflows, and release automation. The repo is primarily an application repository rather than a data/research repository; its many markdown design documents are engineering proposals, not analysis artifacts. The main entry points are plugin/src/main.rs, openebs-upgrade/src/bin/upgrade-job/main.rs, and charts/Chart.yaml. The upgrade path uses trait-based Helm upgraders and Kubernetes pre-upgrade hooks, while the plugin dispatches engine-specific operations through a common Operations enum. Externally, it depends on the Kubernetes API, Helm, and several engine submodules/repositories (Mayastor, localpv-lvm, localpv-zfs). Maintenance is active: the last commit is recent, Dependabot is configured, and the CI pipeline includes linting, image building, Trivy scanning, and release workflows. Technical drift is low overall, though the project's reliance on git submodules and Nix-pinned dependencies creates coordination risk across the broader OpenEBS ecosystem.
RocksDict is a persistent key-value store for Python, backed by the RocksDB embedded database. It provides a Pythonic dictionary-like interface (`Rdict`) for storing and retrieving data that exceeds memory capacity, with support for arbitrary Python objects via pickle or raw bytes. The system is implemented as a Rust extension (using PyO3/maturin) that interacts with the RocksDB C++ library via FFI, offering high performance and durability. The architecture separates concerns into a safe Rust core and a thin Python binding layer. The Rust core implements resource management (via `DbReferenceHolder` to handle RocksDB reference counts and background work cleanup), centralized FFI error handling (through the `ffi_try` macro), and a flexible encoding layer (`encoder.rs`) that supports both raw bytes and pickled Python objects with type tags for efficient deserialization. Configuration persistence is handled via `RocksDictConfig`, which serializes database options to JSON for automatic reloading, enabling seamless recovery of tuned settings. Key features include column families, snapshots, write batches, checkpoints, and SST file ingestion, making it suitable for a wide range of applications from caching to large-scale data storage. The project is actively maintained with comprehensive CI coverage across multiple Python versions and platforms, demonstrating a commitment to reliability and cross-platform compatibility.