aperture
Centrifugo
aperture | Centrifugo | |
---|---|---|
28 | 31 | |
590 | 7,924 | |
1.7% | 1.4% | |
9.8 | 8.9 | |
3 days ago | 3 days ago | |
Go | Go | |
Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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aperture
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Defcon: Meta's system for preventing overload with graceful feature degradation
Anyone interested in load shedding and graceful degradation with request prioritization should check out the Aperture OSS project.
https://github.com/fluxninja/aperture
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Queues Don't Fix Overload
I agree that queues can problem especially when misconfigured. But some amount of queuing is necessary, to absorb short spikes in demand vs capacity. Also, queues can be helpful to re-order requests based on criticality which won't be possible with zero queue size - in which case we have to immediately drop a request or admit it without considering it's priority.
I think it is beneficial to re-think how we tune queues. Instead of setting a queue size, we should be tuning the max permissible latency in the queue which is what a request timeout actually is. That way, you stay within the acceptable response time SLA while keeping only the serve-able requests in the queue.
Aperture, an open-source load management platform took this approach. Each request specifies a timeout for which it is willing to stay in the queue. And weighted fair queuing scheduler then allocates the capacity (a request quota or max number of in-flight request) across requests based on the priority and tokens (request heaviness) of each request.
Read more about the WFQ scheduler in Aperture: https://docs.fluxninja.com/concepts/scheduler
Link to Aperture's GitHub: https://github.com/fluxninja/aperture
Would love to hear your thoughts on our approach!
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Kelsey Hightower's Twitter Spaces on Rate Limits & Flow Control
For those keen to dive deeper, I highly recommend exploring both the Twitter Space and Aperture: [Twitter Spaces]: https://twitter.com/kelseyhightower/status/1689355284802629633?s=20 [GitHub repo]: https://github.com/fluxninja/aperture
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Graceful Behavior at Capacity
Very interesting blog post! Our team has been working intensively in this area for the last couple of years - flow control, load shedding, controllability (PID control), and so on.
We have open-sourced our work at - https://github.com/fluxninja/aperture
We would love feedback from folks reading this blog post!
Disclaimer: I am one of the co-authors of the Aperture project. There are several interesting ideas we have built into this project and I will be happy to dive into the technical details as well.
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Why Adaptive Rate Limiting Is a Game-Changer
It's a blog on an open-source project that precisely tells you how to implement adaptive rate limiting.
Just click around a bit:
- https://github.com/fluxninja/aperture
- https://docs.fluxninja.com/use-cases/adaptive-service-protec...
Note: I am one of the authors' of this project.
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Show HN: Review GitHub PRs with AI/LLMs
At the time of writing, the first sample image on that page is this:
https://coderabbit.ai/assets/section-1-f9a48066.png
which recommends adding a "maxIterations" counter to the "for len(executedComponents) ..." loop here:
https://github.com/fluxninja/aperture/blob/26e00ea818c7c28da...
HOWEVER
- the review has failed to notice the logic using "numExecutedBefore" (around line 377) that already prevents the specific bug it is suggesting a fix for
- the suggested change decrements "maxIterations" inside the "for ... range circuit.components {" loop which means it isn't counting iterations, it's counting components
This kind of suggestion is particularly nasty because it's unlikely that the test suite populates enough components to hit "maxIterations" - so an inattentive reader could accept it, get a green build, and then deploy a production bug!
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June 25th, 2023 Deno Deploy Postmortem
The need an adaptive protection system like Aperture[0] to mitigate overloads.
[0]: https://github.com/fluxninja/aperture
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Jsonnet – The Data Templating Language
It’s customized to our policy spec. But you can learn from this and adapt it to your spec.
https://github.com/fluxninja/aperture/blob/main/scripts/json...
- Show HN: Aperture – Unified Reliability Management for Microservices
- Failure Mitigation for Microservices: An Intro to Aperture
Centrifugo
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WebSockets vs. Server-Sent-Events vs. Long-Polling vs. WebRTC vs. WebTransport
Hello, I am author of https://github.com/centrifugal/centrifugo. Our users can choose from WebSocket, EventSource, WebTransport (experimental stabilize in the future). WebRTC is out of scope as the main purpose is central server based real-time json/binary messaging, and WebRTC makes things much more complex since it shines for peer-to-peer and rich media communications.
What I'd like to add is that Centrifugo also supports HTTP-streaming – not mentioned by the OP – but this is a transport which has advantages over Eventsource - like possibility to send POST body on initial request from web browser (with SSE you can not), it supports binary, and with Readable Streams browser API it's widely supported by modern browsers.
Another thing I'd like to mention about Centrifugo - it supports bidirectional WebSocket fallbacks with EventSource and HTTP-streaming, and does this without sticky sessions requirement. I guess nobody else have this at this point. See https://centrifugal.dev/blog/2022/07/19/centrifugo-v4-releas.... Which solves one more practical concern. Sticky sessions is an optimization in Centrifugo case, not a requirement.
If you are interested in topic, we also have a post about WebSocket scalability - https://centrifugal.dev/blog/2020/11/12/scaling-websocket - it covers some design decisions made in Centrifugo.
- Centrifugo v5.1.0 released, with new powers for real-time messaging tasks, now with proxy GRPC subscription streams – similar to WebSocketd but over the network
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Integrating websockets into my current app
Check out https://github.com/centrifugal/centrifugo - it was initially designed to be a standalone language-agnostic real-time messaging server. So it may be used with Django without radical change in the existing application and using ASGI. It can also provide a much better performance if you care about it.
- Millions of Active WebSockets with Node.js
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Show HN: DriftDB is an open source WebSocket back end for real-time apps
https://github.com/centrifugal/centrifugo
It's a complete solution, including server, admin panel and client library.
We're an European company and use OVH, Hetzner and others.
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Laravel Websockets vs Soketi vs Laravel Echo Server
Hello! Theoretically you can take a look at https://github.com/centrifugal/centrifugo - which is a standalone self-hosted real-time messaging server. It does not have native support for Laravel and not compatible with Pusher protocol, though integrating with any backend system, including Laravel: see the blog post https://centrifugal.dev/blog/2021/12/14/laravel-multi-room-chat-tutorial, also has some helper packages:
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Is Python a good option to implement Websockets?
Hello, it's also possible to design an app in a way that its core will be built with Python, but WebSocket part delegated to something external and efficient like https://github.com/centrifugal/centrifugo – the benefit of the approach is that application business logic is completely decoupled from the real-time transport layer. This may lead to a scalable design with graceful degradation. I think this is especially useful when you already have backend built with Django and need to handle millions of concurrent connections.
- Centrifugo – real-time messaging server (WebSocket, etc.) which scales well and integrates with any backend. SDKs for browser and mobile development included
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What is the coolest Go open source projects you have seen?
Centrifugo https://centrifugal.dev/ https://github.com/centrifugal/centrifugo
- Golang updating the front-end with almost real-time events from the backend server
What are some alternatives?
rules_jsonnet - Jsonnet rules for Bazel
Socket.io - Realtime application framework (Node.JS server)
slo-exporter - Slo-exporter computes standardized SLI and SLO metrics based on events coming from various data sources.
NATS - Golang client for NATS, the cloud native messaging system.
awesome-sre-tools - A curated list of Site Reliability and Production Engineering Tools
Confluent Kafka Golang Client - Confluent's Apache Kafka Golang client
now-boltwall - Vercel lambda deployment for a Nodejs Lightning-powered Paywall
Mercure - 🪽 An open, easy, fast, reliable and battery-efficient solution for real-time communications
ai-pr-reviewer - AI-based Pull Request Summarizer and Reviewer with Chat Capabilities.
laravel-websockets - Websockets for Laravel. Done right.
etleneum - the centralized smart contract platform
soketi - Next-gen, Pusher-compatible, open-source WebSockets server. Simple, fast, and resilient. 📣