Search Results for "cluster"

...It runs with zero runtime dependencies and uses its own storage, which makes deployment simpler than stitching together multiple external systems. Diom can operate as a single node or as a highly available cluster, depending on the service requirements. It is useful for backend developers who want reusable infrastructure components with clean APIs and fewer operational moving parts.

linfa aims to provide a comprehensive toolkit to build Machine Learning applications with Rust. Kin in spirit to Python's scikit-learn, it focuses on common preprocessing tasks and classical ML algorithms for your everyday ML tasks.

...Daft runs locally with a lightweight multithreaded backend. When your local machine is no longer sufficient, it scales seamlessly to run out-of-core on a distributed cluster. Underneath its Python API, Daft is built in blazing fast Rust code. Rust powers Daft’s vectorized execution and async I/O, allowing Daft to outperform frameworks such as Spark.

OpenResearch is a local-first workspace that turns coding agents into research agents capable of running structured scientific workflows. It works with Claude Code, Codex, OpenCode, and Cursor while letting each research direction use an independent session and Git worktree. Agents can review literature, propose hypotheses, modify code, launch experiments, inspect results, and generate research artifacts. Experiments are tracked through a Git-native tree that preserves lineage and immutable...

...You can reduce your log storage costs by ~140x compared to Elasticsearch by using OpenObserve. Below are the results when we pushed logs from our production Kubernetes cluster to Elasticsearch and OpenObserve using fluent bit. OpenObserve stored data in Amazon s3 and Elasticsearch stored data on Amazon EBS volumes.