librdkafka
firecracker
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librdkafka | firecracker | |
---|---|---|
18 | 75 | |
7,292 | 24,084 | |
1.2% | 2.0% | |
8.3 | 9.9 | |
4 days ago | 2 days ago | |
C | Rust | |
GNU General Public License v3.0 or later | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
librdkafka
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Do you use Rust in your professional career?
recent PR: https://github.com/confluentinc/librdkafka/pull/4275
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JR, quality Random Data from the Command line, part I
# Kafka configuration # https://github.com/confluentinc/librdkafka/blob/master/CONFIGURATION.md bootstrap.servers= security.protocol=SASL_SSL sasl.mechanisms=PLAIN sasl.username= sasl.password= compression.type=gzip compression.level=9 statistics.interval.ms=1000
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A Critical Detail about Kafka Partitioners
But what about Kafka producer clients in other languages? The excellent librdkafka project is a C/C++ implementation of Kafka clients and is widely used for non-JVM Kafka applications. Additionally, Kafka clients in other languages (Python, C#) build on top of it. The default partitioner for librdkafka uses the CRC32 hash function to get the correct partition for a key.
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Horizontally scaling Kafka consumers with rendezvous hashing
We could have made some changes at the librdkafka level (see this), but we didn’t really want to pursue this (at least not yet).
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Events with same key going to different partitions
You want records with the same key to always land on the same partition, so you need all the clients to use the same hashing algorithm. The easiest way to do that is to make sure the librdkafka client uses the java compatible murmur2_random hash algorithm. See “Partitioner” section here: https://github.com/confluentinc/librdkafka/blob/master/CONFIGURATION.md
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Getting sum type values from a map
As my first "real world" (ish) project in Vlang, I'm trying to copy https://github.com/confluentinc/confluent-kafka-go, which is a Go wrapper for Kafka C client library, https://github.com/edenhill/librdkafka
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Installing node-rdkafka on M1 for use with SASL
If you're using Kafka in a Node.js app, it's likely that you'll need node-rdkafka. This is a library that wraps the librdkafka library and makes it available in Node.js. According to the project's README, "All the complexity of balancing writes across partitions and managing (possibly ever-changing) brokers should be encapsulated in the library."
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Introduction to Key Apache KafkaⓇ Concepts
# Parse the configuration. # See https://github.com/edenhill/librdkafka/blob/master/CONFIGURATION.md config_parser = ConfigParser() config_parser.read_file(args.config_file) config = dict(config_parser['default']) # Create Producer instance producer = Producer(config)
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video analytics on edge
• git clone https://github.com/edenhill/librdkafka.git
- librdkafka - the Apache Kafka C/C++ client library
firecracker
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Lambda Internals: Why AWS Lambda Will Not Help With Machine Learning
This architecture leverages microVMs for rapid scaling and high-density workloads. But does it work for GPU? The answer is no. You can look at the old 2019 GitHub issue and the comments to it to get the bigger picture of why it is so.
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Show HN: Add AI code interpreter to any LLM via SDK
Hi, I'm the CEO of the company that built this SDK.
We're a company called E2B [0]. We're building and open-source [1] secure environments for running untrusted AI-generated code and AI agents. We call these environments sandboxes and they are built on top of micro VM called Firecracker [2].
You can think of us as giving small cloud computers to LLMs.
We recently created a dedicated SDK for building custom code interpreters in Python or JS/TS. We saw this need after a lot of our users have been adding code execution capabilities to their AI apps with our core SDK [3]. These use cases were often centered around AI data analysis so code interpreter-like behavior made sense
The way our code interpret SDK works is by spawning an E2B sandbox with Jupyter Server. We then communicate with this Jupyter server through Jupyter Kernel messaging protocol [4].
We don't do any wrapping around LLM, any prompting, or any agent-like framework. We leave all of that on users. We're really just a boring code execution layer that sats at the bottom that we're building specifically for the future software that will be building another software. We work with any LLM. Here's how we added code interpreter to Claude [5].
Our long-term plan is to build an automated AWS for AI apps and agents.
Happy to answer any questions and hear feedback!
[0] https://e2b.dev/
[1] https://github.com/e2b-dev
[2] https://github.com/firecracker-microvm/firecracker
[3] https://e2b.dev/docs
[4] https://jupyter-client.readthedocs.io/en/latest/messaging.ht...
[5] https://github.com/e2b-dev/e2b-cookbook/blob/main/examples/c...
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Fly.it Has GPUs Now
As far as I know, Fly uses Firecracker for their VMs. I've been following Firecracker for a while now (even using it in a project), and they don't support GPUs out of the box (and have no plan to support it [1]).
I'm curious to know how Fly figured their own GPU support with Firecracker. In the past they had some very detailed technical posts on how they achieved certain things, so I'm hoping we'll see one on their GPU support in the future!
[1]: https://github.com/firecracker-microvm/firecracker/issues/11...
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MotorOS: a Rust-first operating system for x64 VMs
I pass through a GPU and USB hub to a VM running on a machine in the garage. An optical video cable and network compatible USB extender brings the interface to a different room making it my primary “desktop” computer (and an outdated laptop as a backup device). Doesn’t get more silent and cool than this. Another VM on the garage machine gets a bunch of hard drives passed through to it.
That said, hardware passthrough/VFIO is likely out of the current realistic scope for this project. VM boot times can be optimized if you never look for hardware to initialize in the first place. Though they are still likely initializing a network interface of some sort.
“MicroVM” seems to be a term used when as much as possible is stripped from a VM, such as with https://github.com/firecracker-microvm/firecracker
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Virtual Machine as a Core Android Primitive
According to their own FAQ it is indeed: https://github.com/firecracker-microvm/firecracker/blob/main...
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Sandboxing a .NET Script
What about microVMs like firecracker?
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We Replaced Firecracker with QEMU
Dynamic memory management - Firecracker's RAM footprint starts low, but once a workload inside allocates RAM, Firecracker will never return it to the host system. After running several workloads inside, you end up with an idling VM that consumes 32 GB of RAM on the host, even though it doesn't need any of it.
Firecracker has a balloon device you can inflate (ie: acquire as much memory inside the VM as possible) and then deflate... returning the memory to the host.
https://github.com/firecracker-microvm/firecracker/blob/main...
- I'm looking for a virtual machine that prioritizes privacy and does not include tracking or telemetry.
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Neverflow: Set of C macros that guard against buffer overflows
Very few things in those companies are being written in Rust, and half of those projects chose Rust around ideological reasons rather than technical, with plenty of 'unsafe' thrown in for performance reasons
https://github.com/firecracker-microvm/firecracker/search?q=...
The fact that 'unsafe' even exists in Rust means it's no better than C with some macros.
Don't get me wrong, Rust has it's place, like all the other languages that came about for various reasons, but it's not going to gain wide adoption.
Future of programming consists of 2 languages - something like C that has a small instruction set for adopting to new hardware, and something that is very high level, higher than Python with LLM in the background. Everything in the middle is fodder.
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Do you use Rust in your professional career?
https://github.com/firecracker-microvm/firecracker is the one that comes to mind, but most of these are internal.
What are some alternatives?
CVE-2022-27254 - PoC for vulnerability in Honda's Remote Keyless System(CVE-2022-27254)
cloud-hypervisor - A Virtual Machine Monitor for modern Cloud workloads. Features include CPU, memory and device hotplug, support for running Windows and Linux guests, device offload with vhost-user and a minimal compact footprint. Written in Rust with a strong focus on security.
sarama - Sarama is a Go library for Apache Kafka. [Moved to: https://github.com/IBM/sarama]
bottlerocket - An operating system designed for hosting containers
Karafka - Ruby and Rails efficient multithreaded Kafka processing framework
gvisor - Application Kernel for Containers
kafka-go - Kafka library in Go
libkrun - A dynamic library providing Virtualization-based process isolation capabilities
rsyslog - a Rocket-fast SYStem for LOG processing
krunvm - Create microVMs from OCI images
rust-kafka-101 - Getting started with Rust and Kafka
deno - A modern runtime for JavaScript and TypeScript.