# RabbitMQ RabbitMQ is a free, open-source messaging and streaming broker for efficient, reliable communication between applications, with client libraries for programming languages. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## How LlamaIndex uses Temporal to scale reliable document orchestration DevFeed: [How LlamaIndex uses Temporal to scale reliable document orchestration]() Original publisher: [Read original article]() Author: Adrian Lyjak Published: 2026-09-01T00:00:00Z Content type: article Language: en Sources: [Temporal Blog]() Topics: [llamaindex](), [Orchestration](), [RabbitMQ](), [Concurrency]() Tags: [api](), [concurrency](), [llamaindex](), [orchestration](), [rabbitmq](), [scale](), [temporal](), [temporal-voices]() ### AI overview This article explains how LlamaIndex moved document-processing workloads from RabbitMQ to Temporal. It describes the complexity of processing documents page by page and reports that Temporal helped the team improve durability and concurrency while processing tens of millions of pages per day for the Batch API. ### Source excerpt Learn how LlamaIndex moved from RabbitMQ to Temporal to make LlamaParse more durable, improve concurrency, and process tens of millions of pages per day. ## Kafka vs RabbitMQ vs SQS DevFeed: [Kafka vs RabbitMQ vs SQS]() Original publisher: [Read original article]() Author: Ashish Pratap Singh Published: 2026-07-02T03:31:11Z Content type: comparison Language: en Sources: [AlgoMaster Newsletter]() Topics: [Amazon Simple Queue Service (SQS)](), [Kafka](), [RabbitMQ](), [Messaging](), [Back end]() Tags: [backend](), [kafka](), [messaging](), [queues](), [rabbitmq](), [sqs]() ### AI overview This comparison examines Kafka, RabbitMQ, and Amazon SQS for asynchronous systems. It explains that Kafka uses an append-only log with consumer offsets and replay, RabbitMQ routes messages through exchanges and queues with acknowledgments, and SQS provides managed queue-based messaging that consumers poll. ### Source excerpt Most backend systems eventually need one service to hand off work to another asynchronously. ## Трейсинг в hh.ru: как мы выросли от 1 тысячи до 1 миллиона событий в секунду без семплирования DevFeed: [Трейсинг в hh.ru: как мы выросли от 1 тысячи до 1 миллиона событий в секунду без семплирования]() Original publisher: [Read original article]() Author: Heruvimka (hh.ru, Конференции Олега Бунина (Онтико)) Published: 2025-09-16T09:00:45Z Content type: article Language: ru Sources: [HeadHunter RU]() Topics: [observability](), [telemetry](), [SRE](), [Kafka](), [nginx](), [Apache Cassandra](), [OpenTelemetry](), [RabbitMQ]() Tags: [cassandra](), [devops](), [jaeger](), [kafka](), [nginx](), [observability](), [opentelemetry](), [operational-intelligence](), [rabbitmq](), [request](), [sre](), [tag-1e4ee1f65f5a](), [tag-68e701e78517](), [tag-73eb9b712998](), [tag-75f84211cab4](), [tag-8f8626975338](), [tag-9abb13e52060](), [tag-b92bf5906bbd](), [tag-d9df843a1803](), [tag-dfac9042ce7b](), [tracing]() ### AI overview This Russian developer article describes how hh.ru built and rebuilt its tracing and observability architecture as its data volume increased. The supplied text states that the system handles 24,000 RPS, one million spans per second, and 5,000 service instances, and introduces a log-based tracing design using Request-Id propagation. ### Source excerpt В каждой компании есть необходимость выстроить систему observability. В hh.ru мы перестраивали архитектуру под большее количество данных несколько раз -- сейчас имеем на входе 24к RPS, 1 миллион спанов в секунду, 5к инстансов сервисов. Если вы -- инженер, который находится в процессе построения или перестройки собственной системы трейсинга, этот доклад -- для вас. Привет, Хабр! Я -- Александр Казанцев, уже более десяти лет в разработке. Когда-то был инженером на пивзаводе и могу рассказать, из чего делают пенное; но сегодня -- о другом. Читать далее ## Blog: Integrate Runtime Security into Your Environment with Falcosidekick DevFeed: [Blog: Integrate Runtime Security into Your Environment with Falcosidekick]() Original publisher: [Read original article]() Published: 2023-10-24T00:00:00Z Content type: article Language: en Sources: [Falco - Falco](), [Falco - The Falco blog]() Topics: [Falco](), [Security](), [threat detection](), [Kubernetes](), [Cloud Native Ecosystem](), [Open Source](), [Tooling](), [AWS Lambda](), [Cloud Functions](), [Cloud Run](), [Kafka](), [RabbitMQ]() Tags: [aws-lambda](), [cloud-functions](), [cloud-native](), [cloud-run](), [falco](), [falcosidekick](), [integrations](), [kafka](), [kubernetes](), [notifications](), [rabbitmq](), [runtime-security](), [security](), [tool]() ### AI overview This article explains how Falcosidekick extends Falco's limited default output options by forwarding runtime-security events to services such as Slack, PagerDuty, email, AWS Lambda, cloud functions, and message queues. It describes configurable notifications and automated responses for suspicious activity in cloud, container, and Kubernetes environments. ### Source excerpt If you're looking to integrate runtime security into your existing environment, Falco is an obvious choice. Falco is a Cloud Native Computing Foundation backed open source project that provides real-time threat detection for cloud, container, and Kubernetes workloads. With over 80 million downloads Falco has been adopted by some of the largest companies in the world. However, what many Falco users discover early on is that Falco's default event output is rather limited. Out of the box, Falco can only send output to five different endpoints: syslog, stdout, stderr, and gRPC or HTTPS endpoints. While these outputs might be enough to get you started, most practitioners want to integrate Falco with the tooling they already use. This is where Falcosidekick comes in. Falcosidekick is a companion (i.e. a side-kick ;)) project for Falco that allows Falco events to be forwarded to 60 different services (with more being added all the time) allowing practitioners to monitor and react to Falco events with the tools they are already using. For example, if you'd like to receive immediate notifications of suspicious activity you can forward Falco events to chat programs such as Slack or Telegram, alerting platforms like PagerDuty or AlertManager, or, of course, email. In order to minimize noise, you can expressly set the level on which to notify, for example, warning-level events might be delivered via email, while critical or higher-level events are sent via chat or directed to your alerting platform. If you want to programmatically address certain events, Falcosidekick integrates with a bunch of different services including functions as a service platforms like AWS Lambda, GCP Cloud Run and Cloud Functions, or Knative. Alerts can also be sent to message queues like Amazon SNS, Apache Kafka, or RabbitMQ. These integrations offer almost endless possibilities for building out response systems for events. For instance, let's say you're running Falco on your Kubernetes cluster, and F ## So That One Time You Played With Docker DevFeed: [So That One Time You Played With Docker]() Original publisher: [Read original article]() Author: Fuzzygroup Published: 2020-07-20T00:00:00Z Content type: article Language: en Sources: [Scott Johnson]() Topics: [Docker](), [Terminal](), [MongoDB](), [RabbitMQ]() Tags: [cpu](), [docker](), [mongodb](), [open-source](), [processes](), [rabbitmq]() ### AI overview A personal technical account of using Docker to run an open-source stack for a medical-sector project. After leaving the containers running for more than two weeks, the author noticed system slowness and high CPU usage, then stopped the containers. ### Source excerpt layout: post title: So That One Time You Played with Docker for hte So that one time, at band camp - wait; wrong movie, this is a technical blog post about Docker ... I recently helped a friend doing some federal work in the medical field get a better understanding of Docker and how Docker can mess about with open source licensing. We got up a "open source" stack of tooling using a bunch of heavy weight tools: Mongo Memcached A big Python app Rabbit MQ And then, as you so often do, we finished up and I got distracted by the next bit of crazy nerd-fu that runs about in my life (server down; wifi crisis; son needing help with his PC; who can remember) and then I went back to my desk, closed my terminal prompt and never thought much more about this. Lately I've been noticing some slowness on my machine and I just happened to run docker ps and what do I see but: docker ps CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES b93fbedc58d2 data_streamer_to_sqs_ruby "ruby ./main.rb" 29 seconds ago Up 27 seconds nice_torvalds 605da7fe5159 dsarchive/dsa_girder:latest "/bin/sh -c 'sudo -E..." 2 weeks ago Up 3 hours 0.0.0.0:8080->8080/tcp dsa_girder 0b0eb7730fb0 dsarchive/dsa_worker:latest "/bin/sh -c 'sudo -E..." 2 weeks ago Up 3 hours dsa_worker df6fd902c11b memcached:latest "docker-entrypoint.s..." 2 weeks ago Up 3 hours 11211/tcp dsa_memcached dc7f57778b4e mongo:latest "docker-entrypoint.s..." 2 weeks ago Up 3 hours 27017/tcp dsa_mongodb 863768f4f33f rabbitmq:management "docker-entrypoint.s..." 2 weeks ago Up 3 hours 4369/tcp, 5671-5672/tcp, 15671-15672/tcp, 25672/tcp dsa_rabbitmq Yep. That's the whole set of processes that I was using for my federal friend. Sigh. They've been happily sucking up CPU for more than 2 weeks. grumble The solution: docker stop 863768f4f33f dc7f57778b4e df6fd902c11b 0b0eb7730fb0 605da7fe5159 ## How we scaled Wisembly's infrastructure : moving from our Elephant to RabbitMQ DevFeed: [How we scaled Wisembly's infrastructure : moving from our Elephant to RabbitMQ]() Original publisher: [Read original article]() Author: Guillaume POTIER Published: 2015-07-02T13:31:56Z Content type: article Language: en Sources: [eFounders]() Topics: [RabbitMQ](), [Socket.IO](), [WebSocket](), [real-time](), [MySQL](), [Node.js](), [PHP](), [Redis](), [Software as a service]() Tags: [backend](), [growth](), [mysql](), [node-js](), [php](), [rabbitmq](), [real-time](), [redis](), [saas](), [startup](), [tech](), [websockets]() ### AI overview This article describes how Wisembly evolved its infrastructure as usage grew. It focuses on using RabbitMQ on the backend to communicate between application components and servers, after earlier use of Node.js, Socket.IO, PHP, MySQL, Redis, and WebSockets. ### Source excerpt Hi, I'm Guillaume, I am the CTO and co-founder of Wisembly, a SaaS solution facilitating interactions during your big meetings and events. We recently launched a beta of our new product: Solid to help you make your every-day-meetings more productive and actionable. This is the story of how we improved our performance by changing and adding elements to our stack over the time. I'll particularly focus on how using RabbitMQ on the backend to communicate between different stack and servers improved our life. Where we once were Here are the building blocks for our tech team's philosophy: start small, DRY (Don't Repeat Yourself) and YAGNI (You Ain't Gonna Need It). Back in 2012, when we implemented real-time websockets communications with Node.js and Socket.io, we had a pretty small stack: everything fullstack on Symfony2 with MySQL as single storage and some tiny parts of Backbone.js here and there to power up our application. One year later I presented these slides at the Symfony2 Live Paris 2013 explaining how we implemented Elephant in raw PHP to communicate from our Symfony2 backend with our distant socket.io push server. https://medium.com/media/dfdfc12635e346b3ceb1b2838fda5808/href As I said, our stack was pretty minimal at the time. We didn't feel the need to complexify it for the sake of the socket.io push server. So we looked at websockets and found a pretty way to implement them, connect and emit events with our Open Source library. It did the job, we open-sourced something cool (more than 500 stargazers now and still active!), on our way to live happily ever after :)... Or did we? Where we are now Quite recently, as the business was growing, more and more push events were sent every minute on the various customer meetings we handle daily. For example, we have a specific feature for very interactive seminars where more than 500 users can answer a live poll. Oftentimes, all the attendees submit their answers during the same 10-to-20-second time window, right after ## Choosing a message queue for Python on Ubuntu on a VPS DevFeed: [Choosing a message queue for Python on Ubuntu on a VPS]() Original publisher: [Read original article]() Author: Graham King Published: 2009-08-10T05:05:13Z Content type: comparison Language: en Sources: [Graham King]() Topics: [Messaging](), [RabbitMQ](), [NumPy](), [Ubuntu](), [Redis]() Tags: [comparison](), [gearman](), [message-queue](), [python](), [queue](), [rabbitmq](), [redis](), [software](), [ubuntu]() ### AI overview A comparison of RabbitMQ, Gearman, Beanstalkd, and Redis as message queues for Python web applications running on Ubuntu VPS environments. It considers Python compatibility, memory usage, reliability, and suitability for background work. ### Source excerpt Queuing up the best message options: A straightforward comparison of popular message queues.