Testing distributed systems under hard failures like network partitions and instance termination is critical, but it's also important we test them under less catastrophic conditions because this is what they most often experience. Comcast is a tool designed to simulate common network problems like latency, bandwidth restrictions, and dropped/reordered/corrupted packets.



Comcast - Simulating shitty network connections so you can build better systems.

Small Go package for fast high-level image processing using libvips via C bindings, providing a simple programmatic API. bimg is able to output images as JPEG, PNG and WEBP formats, including transparent conversion across them.

bimg - Small Go package for fast high-level image processing powered by libvips C library

Weaviate is an open-source vector database. It allows you to store data objects and vector embeddings from your favorite ML-models, and scale seamlessly into billions of data objects.
Weaviate offers Semantic Search, Question-Answer Extraction, Classification, Customizable Models (PyTorch/TensorFlow/Keras), etc. Built from scratch in Go, Weaviate stores both objects and vectors, allowing for combining vector search with structured filtering and the fault tolerance of a cloud-native database. It is all accessible through GraphQL, REST, and various client-side programming languages.
Weaviate provides out-of-the-box modules for NLP / semantic search, automatic classification, and image similarity search. It has a modular setup that allows you to use your ML models inside Weaviate. You can also use out-of-the-box ML models (e.g., SBERT, ResNet, fasttext, etc.). It typically performs nearest neighbor (NN) searches of millions of objects in considerably less than 100ms.&nbsp;
Weaviate allows for efficient, combined vector and scalar searches. For example, "articles related to the COVID-19 pandemic published within the past 7 days." Weaviate stores both objects and vectors and ensures the retrieval of both is always efficient. There is no need for a third-party object storage. Within Weaviate, all individual data objects are based on a class property structure where a vector represents each data object. You can connect data objects (like in a traditional graph) and search for data objects in the vector space.

Weaviate is an open-source vector database. It allows you to store data objects and vector embeddings from your favorite ML-models, and scale seamlessly into billions of data objects.

Weaviate - Vector database that is robust, scalable, cloud-native, and fast



Podgrab is a is a self-hosted podcast manager which automatically downloads latest podcast episodes. It is a light-weight application built using GO. It works best if you already know which podcasts you want to monitor. However there is a podcast search system powered by iTunes built into Podgrab.
 
Its feature include: 
<ul>
<li>Download/Archive complete podcast</li>
<li>Auto-download new episodes</li>
<li>Tag/Label podcasts into groups</li>
<li>Download on demand</li>
<li>Podcast Discovery - Search and Add podcasts using iTunes API</li>
<li>Full-fledged podcast player - Play downloaded files or stream from original source. Play single episodes, full podcasts and podcast groups(tags)</li>
<li>Add using direct RSS feed URL / OMPL import / Search</li>
<li>Basic Authentication</li>
<li>Existing episode file detection - Prevent re-downloading files if already present</li>
<li>Easy OPML import/export</li>
<li>Customizable episode names</li>
<li>Dark Mode</li>
<li>Self Hosted / Open Source</li>
<li>Docker support</li>
</ul>

Podgrab is a is a self-hosted podcast manager which automatically downloads latest podcast episodes. It is a light-weight application built using GO. It works best if you already know which podcasts you want to monitor. However there is a podcast search system powered by iTunes built into Podgrab.

Podgrab -  A self-hosted podcast manager to download episodes as soon as they become live 

This is a library and command-line tool to read, write, and generally work with DICOM medical image files in native Go. The goal is to build a full-featured, high-performance, and readable DICOM parser for the Go community.
<ul>
<li>Parse multi-frame DICOM imagery (both encapsulated and native pixel data)</li>
<li> Channel-based streaming of <code>Frame</code>s to a client as they are parsed out of the dicom</li>
<li> Cleaner Go Element and Dataset representations (in the absense of Go generics)</li>
<li> Better support for icon image sets in addition to primary image sets</li>
<li> Write and encode Datasets back to DICOM files</li>
<li> Enhanced testing and benchmarking support</li>
<li> Modern, canonical Go.</li>
</ul>

This is a library and command-line tool to read, write, and generally work with DICOM medical image files in native Go. The goal is to build a full-featured, high-performance, and readable DICOM parser for the Go community.

dicom - High Performance DICOM Medical Image Parser in Go

GoToSocial is a Fediverse server project, written in Golang. It provides an alternative to existing projects such as Mastodon, Pleroma, Friendica, PixelFed etc. One of the key differences between GoToSocial and those other projects is that GoToSocial doesn't include an integrated front-end (ie., a webapp). Instead, like the Matrix.org's Synapse project, it provides only a server implementation and a well-documented API. On this API, developers are free to build any front-end implementation or mobile application that they wish.

GoToSocial - Fediverse server project

kind is a tool for running local Kubernetes clusters using Docker container "nodes". kind was primarily designed for testing Kubernetes itself, but may be used for local development or CI.
kind is divided into go packages implementing most of the functionality, a command line for users, and a &ldquo;node&rdquo; base image. The intent is that the kind the suite of packages should eventually be importable and reusable by other tools (e.g. <a href="https://github.com/kubernetes/test-infra/tree/master/kubetest" target="_blank" rel="noopener">kubetest</a>) while the CLI provides a quick way to use and debug these packages.
&nbsp;

kind is a tool for running local Kubernetes clusters using Docker container “nodes”. kind was primarily designed for testing Kubernetes itself, but may be used for local development or CI.

Kubernetes IN Docker - local clusters for testing Kubernetes

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Projects

Comcast - Simulating shitty network connections so you can build better systems.

bimg - Small Go package for fast high-level image processing powered by libvips C library

Weaviate - Vector database that is robust, scalable, cloud-native, and fast

Podgrab - A self-hosted podcast manager to download episodes as soon as they become live

dicom - High Performance DICOM Medical Image Parser in Go

GoToSocial - Fediverse server project

Kubernetes IN Docker - local clusters for testing Kubernetes

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Comcast - Simulating shitty network connections so you can build better systems.

bimg - Small Go package for fast high-level image processing powered by libvips C library

Weaviate - Vector database that is robust, scalable, cloud-native, and fast

Podgrab - A self-hosted podcast manager to download episodes as soon as they become live

dicom - High Performance DICOM Medical Image Parser in Go

GoToSocial - Fediverse server project

Kubernetes IN Docker - local clusters for testing Kubernetes

TechStack

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