juicefs VS typedoc

Support for Kerberos keytab files

JuiceFS under the Apache License 2.0, is a high-performance POSIX file system optimized for cloud-native environments. It stores data in Object Storage (e.g., Amazon S3) and metadata in databases like Redis, MySQL, or TiKV. JuiceFS integrates massive cloud storage with big data, machine learning, and AI applications efficiently, akin to local storage. It features full POSIX and Hadoop compatibility, S3 interface, Kubernetes support, and shared file storage for numerous clients. Some cool features are - strong consistency, scalable performance, data encryption, global file locks, and compression with LZ4 or Zstandard.

To improve the handling process of capacity overrun, the JuiceFS client supports deletion operations in the case of Ceph cluster fullness (see related code changes in JuiceFS Community Edition). Therefore, for newer client versions, there is no need to use set-full-ratio for temporary adjustments.

If you have any questions or would like to learn more, feel free to join discussions about JuiceFS on GitHub and the JuiceFS community on Slack.

The architecture image shows GCS and others, so I suspect it does.

https://github.com/juicedata/juicefs#architecture

See also: JuiceFS: https://juicefs.com/

Adds a DBMS or key-value store for metadata, making the filesystem much faster (POSIX, small overwrites don't have to replace a full object in the GCS/S3 backend).

Almost certainly a better solution if you want to turn your object storage into a mountable filesystem, with the (big) caveat that you can't access the files directly in the bucket (they are not stored transparently).

JuiceFS can do the same thing as s3fs-fuse, but better. Because it supports robust data consistency and caching policies to improve performance.

Firstly, install Typedoc using npm:

Background:The main bottleneck with the TypeDoc default theme especially for large projects is the verbose HTML for the left-hand navigation that linearly grows for each page based on the project size and consumes a massive amount of disk space; see this TypeDoc issue. The DMT caches the left-hand navigation HTML and dynamically creates a shared web component that is utilized across all pages only making a single copy of the navigation HTML. This reduces disk space utilization by up to 90% and also makes doc generation ~80% faster. I also include some style additions and replace the main search index generation using compressed MesssagePack instead of JSON which reduces the search index size by more than 90%.

While the Prim+RPC server is expected to be JavaScript, I'd like to support other languages through JSON Schema. I wrote a tool that translates TypeDoc comments into RPC-specific documentation. My plan is to turn this result into JSON Schema that can be served with the Prim+RPC server. This means you can get typed suggestions (for instance, from an IDE that understands JSON Schema) when writing requests in JSON files (I wrote a little about this here, still a WIP). From this, you could use your favorite HTTP client in the language of your choice, like but still benefit from having typed requests.

Docusaurus has a Typedoc plugin. Also there is a typedoc markdown plugin.

Finally, JSDoc can be used to generate documentation for your code using tools like JSDoc itself and TypeDoc. These tools generate HTML or Markdown documentation based on your JSDoc annotations, making it easier for others to understand how your code works and how to use it.

Since you're using TypeScript, use TypeDoc.

Generates HTML documentation using TypeDoc.

I was thinking of using something like https://typedoc.org to do it, do you have experience with this sort of tools?

TSDoc is more consistent, has cleaner documentation, better tooling (e.g. TypeDoc or ESLint plugin) and better support for data structures (e.g. straightforward enums support).