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RabbitMQ
RabbitMQ

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Serverless

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RabbitMQ vs Serverless: What are the differences?

RabbitMQ: A messaging broker - an intermediary for messaging. RabbitMQ gives your applications a common platform to send and receive messages, and your messages a safe place to live until received; Serverless: The most widely-adopted toolkit for building serverless applications. Build applications comprised of microservices that run in response to events, auto-scale for you, and only charge you when they run. This lowers the total cost of maintaining your apps, enabling you to build more logic, faster. The Framework uses new event-driven compute services, like AWS Lambda, Google CloudFunctions, and more.

RabbitMQ can be classified as a tool in the "Message Queue" category, while Serverless is grouped under "Serverless / Task Processing".

"It's fast and it works with good metrics/monitoring" is the primary reason why developers consider RabbitMQ over the competitors, whereas "API integration " was stated as the key factor in picking Serverless.

RabbitMQ and Serverless are both open source tools. It seems that Serverless with 30.9K GitHub stars and 3.43K forks on GitHub has more adoption than RabbitMQ with 5.95K GitHub stars and 1.78K GitHub forks.

According to the StackShare community, RabbitMQ has a broader approval, being mentioned in 940 company stacks & 548 developers stacks; compared to Serverless, which is listed in 117 company stacks and 44 developer stacks.

What is RabbitMQ?

RabbitMQ gives your applications a common platform to send and receive messages, and your messages a safe place to live until received.

What is Serverless?

Build applications comprised of microservices that run in response to events, auto-scale for you, and only charge you when they run. This lowers the total cost of maintaining your apps, enabling you to build more logic, faster. The Framework uses new event-driven compute services, like AWS Lambda, Google CloudFunctions, and more.
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    What are some alternatives to RabbitMQ and Serverless?
    Kafka
    Kafka is a distributed, partitioned, replicated commit log service. It provides the functionality of a messaging system, but with a unique design.
    ActiveMQ
    Apache ActiveMQ is fast, supports many Cross Language Clients and Protocols, comes with easy to use Enterprise Integration Patterns and many advanced features while fully supporting JMS 1.1 and J2EE 1.4. Apache ActiveMQ is released under the Apache 2.0 License.
    ZeroMQ
    The 0MQ lightweight messaging kernel is a library which extends the standard socket interfaces with features traditionally provided by specialised messaging middleware products. 0MQ sockets provide an abstraction of asynchronous message queues, multiple messaging patterns, message filtering (subscriptions), seamless access to multiple transport protocols and more.
    Amazon SNS
    Amazon Simple Notification Service makes it simple and cost-effective to push to mobile devices such as iPhone, iPad, Android, Kindle Fire, and internet connected smart devices, as well as pushing to other distributed services. Besides pushing cloud notifications directly to mobile devices, SNS can also deliver notifications by SMS text message or email, to Simple Queue Service (SQS) queues, or to any HTTP endpoint.
    Redis
    Redis is an open source, BSD licensed, advanced key-value store. It is often referred to as a data structure server since keys can contain strings, hashes, lists, sets and sorted sets.
    See all alternatives
    Decisions about RabbitMQ and Serverless
    James Cunningham
    James Cunningham
    Operations Engineer at Sentry · | 18 upvotes · 82.2K views
    atSentrySentry
    RabbitMQ
    RabbitMQ
    Celery
    Celery
    #MessageQueue

    As Sentry runs throughout the day, there are about 50 different offline tasks that we execute—anything from “process this event, pretty please” to “send all of these cool people some emails.” There are some that we execute once a day and some that execute thousands per second.

    Managing this variety requires a reliably high-throughput message-passing technology. We use Celery's RabbitMQ implementation, and we stumbled upon a great feature called Federation that allows us to partition our task queue across any number of RabbitMQ servers and gives us the confidence that, if any single server gets backlogged, others will pitch in and distribute some of the backlogged tasks to their consumers.

    #MessageQueue

    See more
    Adam Rabinovitch
    Adam Rabinovitch
    Global Technical Recruiting Lead & Engineering Evangelist at Beamery · | 3 upvotes · 156.8K views
    atBeameryBeamery
    Kafka
    Kafka
    Redis
    Redis
    Elasticsearch
    Elasticsearch
    MongoDB
    MongoDB
    RabbitMQ
    RabbitMQ
    Go
    Go
    Node.js
    Node.js
    Kubernetes
    Kubernetes
    #Microservices

    Beamery runs a #microservices architecture in the backend on top of Google Cloud with Kubernetes There are a 100+ different microservice split between Node.js and Go . Data flows between the microservices over REST and gRPC and passes through Kafka RabbitMQ as a message bus. Beamery stores data in MongoDB with near-realtime replication to Elasticsearch . In addition, Beamery uses Redis for various memory-optimized tasks.

    See more
    Nitzan Shapira
    Nitzan Shapira
    at Epsagon · | 11 upvotes · 93.4K views
    atEpsagonEpsagon
    AWS Lambda
    AWS Lambda
    GitHub
    GitHub
    Java
    Java
    Go
    Go
    Node.js
    Node.js
    npm
    npm
    Serverless
    Serverless
    Python
    Python

    At Epsagon, we use hundreds of AWS Lambda functions, most of them are written in Python, and the Serverless Framework to pack and deploy them. One of the issues we've encountered is the difficulty to package external libraries into the Lambda environment using the Serverless Framework. This limitation is probably by design since the external code your Lambda needs can be usually included with a package manager.

    In order to overcome this issue, we've developed a tool, which we also published as open-source (see link below), which automatically packs these libraries using a simple npm package and a YAML configuration file. Support for Node.js, Go, and Java will be available soon.

    The GitHub respoitory: https://github.com/epsagon/serverless-package-external

    See more
    Michal Nowak
    Michal Nowak
    Co-founder at Evojam · | 7 upvotes · 50.6K views
    atEvojamEvojam
    Azure Functions
    Azure Functions
    Firebase
    Firebase
    AWS Lambda
    AWS Lambda
    Serverless
    Serverless

    In a couple of recent projects we had an opportunity to try out the new Serverless approach to building web applications. It wasn't necessarily a question if we should use any particular vendor but rather "if" we can consider serverless a viable option for building apps. Obviously our goal was also to get a feel for this technology and gain some hands-on experience.

    We did consider AWS Lambda, Firebase from Google as well as Azure Functions. Eventually we went with AWS Lambdas.

    PROS
    • No servers to manage (obviously!)
    • Limited fixed costs – you pay only for used time
    • Automated scaling and balancing
    • Automatic failover (or, at this level of abstraction, no failover problem at all)
    • Security easier to provide and audit
    • Low overhead at the start (with the certain level of knowledge)
    • Short time to market
    • Easy handover - deployment coupled with code
    • Perfect choice for lean startups with fast-paced iterations
    • Augmentation for the classic cloud, server(full) approach
    CONS
    • Not much know-how and best practices available about structuring the code and projects on the market
    • Not suitable for complex business logic due to the risk of producing highly coupled code
    • Cost difficult to estimate (helpful tools: serverlesscalc.com)
    • Difficulty in migration to other platforms (Vendor lock⚠️)
    • Little engineers with experience in serverless on the job market
    • Steep learning curve for engineers without any cloud experience

    More details are on our blog: https://evojam.com/blog/2018/12/5/should-you-go-serverless-meet-the-benefits-and-flaws-of-new-wave-of-cloud-solutions I hope it helps 🙌 & I'm curious of your experiences.

    See more
    RabbitMQ
    RabbitMQ
    Kafka
    Kafka

    The question for which Message Queue to use mentioned "availability, distributed, scalability, and monitoring". I don't think that this excludes many options already. I does not sound like you would take advantage of Kafka's strengths (replayability, based on an even sourcing architecture). You could pick one of the AMQP options.

    I would recommend the RabbitMQ message broker, which not only implements the AMQP standard 0.9.1 (it can support 1.x or other protocols as well) but has also several very useful extensions built in. It ticks the boxes you mentioned and on top you will get a very flexible system, that allows you to build the architecture, pick the options and trade-offs that suite your case best.

    For more information about RabbitMQ, please have a look at the linked markdown I assembled. The second half explains many configuration options. It also contains links to managed hosting and to libraries (though it is missing Python's - which should be Puka, I assume).

    See more
    Julien DeFrance
    Julien DeFrance
    Full Stack Engineering Manager at ValiMail · | 2 upvotes · 12.1K views
    atSmartZipSmartZip
    Amazon SageMaker
    Amazon SageMaker
    Amazon Machine Learning
    Amazon Machine Learning
    AWS Lambda
    AWS Lambda
    Serverless
    Serverless
    #FaaS
    #GCP
    #PaaS

    Which #IaaS / #PaaS to chose? Not all #Cloud providers are created equal. As you start to use one or the other, you'll build around very specific services that don't have their equivalent elsewhere.

    Back in 2014/2015, this decision I made for SmartZip was a no-brainer and #AWS won. AWS has been a leader, and over the years demonstrated their capacity to innovate, and reducing toil. Like no other.

    Year after year, this kept on being confirmed, as they rolled out new (managed) services, got into Serverless with AWS Lambda / FaaS And allowed domains such as #AI / #MachineLearning to be put into the hands of every developers thanks to Amazon Machine Learning or Amazon SageMaker for instance.

    Should you compare with #GCP for instance, it's not quite there yet. Building around these managed services, #AWS allowed me to get my developers on a whole new level. Where they know what's under the hood. Where they know they have these services available and can build around them. Where they care and are responsible for operations and security and deployment of what they've worked on.

    See more
    Frédéric MARAND
    Frédéric MARAND
    Core Developer at OSInet · | 2 upvotes · 88.4K views
    atOSInetOSInet
    RabbitMQ
    RabbitMQ
    Beanstalkd
    Beanstalkd
    Kafka
    Kafka

    I used Kafka originally because it was mandated as part of the top-level IT requirements at a Fortune 500 client. What I found was that it was orders of magnitude more complex ...and powerful than my daily Beanstalkd , and far more flexible, resilient, and manageable than RabbitMQ.

    So for any case where utmost flexibility and resilience are part of the deal, I would use Kafka again. But due to the complexities involved, for any time where this level of scalability is not required, I would probably just use Beanstalkd for its simplicity.

    I tend to find RabbitMQ to be in an uncomfortable middle place between these two extremities.

    See more
    Aviad Mor
    Aviad Mor
    CTO & Co-Founder at Lumigo · | 5 upvotes · 8.8K views
    atLumigoLumigo
    Serverless
    Serverless
    CircleCI
    CircleCI
    AWS Lambda
    AWS Lambda

    Our backend is serverless based, with many AWS Lambda , with CI/CD, using CircleCI and Serverless. This allows to develop with awesome agility and move fast. Since we update our lambdas daily, we needed a way to make sure we did not run into AWS's max limit of versions per lambda. We use the open source in link below to clear them out and stay clear of the limit.

    See more
    Aliadoc Team
    Aliadoc Team
    at aliadoc.com · | 5 upvotes · 59.7K views
    atAliadocAliadoc
    Bitbucket
    Bitbucket
    Visual Studio Code
    Visual Studio Code
    Serverless
    Serverless
    Google Cloud Storage
    Google Cloud Storage
    Google App Engine
    Google App Engine
    Cloud Functions for Firebase
    Cloud Functions for Firebase
    Firebase
    Firebase
    CloudFlare
    CloudFlare
    Create React App
    Create React App
    React
    React
    #Aliadoc

    In #Aliadoc, we're exploring the crowdfunding option to get traction before launch. We are building a SaaS platform for website design customization.

    For the Admin UI and website editor we use React and we're currently transitioning from a Create React App setup to a custom one because our needs have become more specific. We use CloudFlare as much as possible, it's a great service.

    For routing dynamic resources and proxy tasks to feed websites to the editor we leverage CloudFlare Workers for improved responsiveness. We use Firebase for our hosting needs and user authentication while also using several Cloud Functions for Firebase to interact with other services along with Google App Engine and Google Cloud Storage, but also the Real Time Database is on the radar for collaborative website editing.

    We generally hate configuration but honestly because of the stage of our project we lack resources for doing heavy sysops work. So we are basically just relying on Serverless technologies as much as we can to do all server side processing.

    Visual Studio Code definitively makes programming a much easier and enjoyable task, we just love it. We combine it with Bitbucket for our source code control needs.

    See more
    Tim Nolet
    Tim Nolet
    Founder, Engineer & Dishwasher at Checkly · | 5 upvotes · 14.6K views
    atChecklyHQChecklyHQ
    Node.js
    Node.js
    Google Cloud Functions
    Google Cloud Functions
    Azure Functions
    Azure Functions
    Amazon CloudWatch
    Amazon CloudWatch
    Serverless
    Serverless
    AWS Lambda
    AWS Lambda

    AWS Lambda Serverless Amazon CloudWatch Azure Functions Google Cloud Functions Node.js

    In the last year or so, I moved all Checkly monitoring workloads to AWS Lambda. Here are some stats:

    • We run three core functions in all AWS regions. They handle API checks, browser checks and setup / teardown scripts. Check our docs to find out what that means.
    • All functions are hooked up to SNS topics but can also be triggered directly through AWS SDK calls.
    • The busiest function is a plumbing function that forwards data to our database. It is invoked anywhere between 7000 and 10.000 times per hour with an average duration of about 179 ms.
    • We run separate dev and test versions of each function in each region.

    Moving all this to AWS Lambda took some work and considerations. The blog post linked below goes into the following topics:

    • Why Lambda is an almost perfect match for SaaS. Especially when you're small.
    • Why I don't use a "big" framework around it.
    • Why distributed background jobs triggered by queues are Lambda's raison d'être.
    • Why monitoring & logging is still an issue.

    https://blog.checklyhq.com/how-i-made-aws-lambda-work-for-my-saas/

    See more
    Praveen Mooli
    Praveen Mooli
    Technical Leader at Taylor and Francis · | 11 upvotes · 98.6K views
    MongoDB Atlas
    MongoDB Atlas
    Amazon S3
    Amazon S3
    Amazon DynamoDB
    Amazon DynamoDB
    Amazon RDS
    Amazon RDS
    Serverless
    Serverless
    Docker
    Docker
    Terraform
    Terraform
    Travis CI
    Travis CI
    GitHub
    GitHub
    RxJS
    RxJS
    Angular 2
    Angular 2
    AWS Lambda
    AWS Lambda
    Amazon SQS
    Amazon SQS
    Amazon SNS
    Amazon SNS
    Amazon Kinesis Firehose
    Amazon Kinesis Firehose
    Amazon Kinesis
    Amazon Kinesis
    Flask
    Flask
    Python
    Python
    ExpressJS
    ExpressJS
    Node.js
    Node.js
    Spring Boot
    Spring Boot
    Java
    Java
    #Data
    #Devops
    #Webapps
    #Eventsourcingframework
    #Microservices
    #Backend

    We are in the process of building a modern content platform to deliver our content through various channels. We decided to go with Microservices architecture as we wanted scale. Microservice architecture style is an approach to developing an application as a suite of small independently deployable services built around specific business capabilities. You can gain modularity, extensive parallelism and cost-effective scaling by deploying services across many distributed servers. Microservices modularity facilitates independent updates/deployments, and helps to avoid single point of failure, which can help prevent large-scale outages. We also decided to use Event Driven Architecture pattern which is a popular distributed asynchronous architecture pattern used to produce highly scalable applications. The event-driven architecture is made up of highly decoupled, single-purpose event processing components that asynchronously receive and process events.

    To build our #Backend capabilities we decided to use the following: 1. #Microservices - Java with Spring Boot , Node.js with ExpressJS and Python with Flask 2. #Eventsourcingframework - Amazon Kinesis , Amazon Kinesis Firehose , Amazon SNS , Amazon SQS, AWS Lambda 3. #Data - Amazon RDS , Amazon DynamoDB , Amazon S3 , MongoDB Atlas

    To build #Webapps we decided to use Angular 2 with RxJS

    #Devops - GitHub , Travis CI , Terraform , Docker , Serverless

    See more
    Interest over time
    Reviews of RabbitMQ and Serverless
    Review ofRabbitMQRabbitMQ

    I developed one of the largest queue based medical results delivery systems in the world, 18,000+ queues and still growing over a decade later all using MQSeries, later called Websphere MQ. When I left that company I started using RabbitMQ after doing some research on free offerings.. it works brilliantly and is incredibly flexible from small scale single instance use to large scale multi-server - multi-site architectures.

    If you can think in queues then RabbitMQ should be a viable solution for integrating disparate systems.

    How developers use RabbitMQ and Serverless
    Avatar of Cloudify
    Cloudify uses RabbitMQRabbitMQ

    The poster child for scalable messaging systems, RabbitMQ has been used in countless large scale systems as the messaging backbone of any large cluster, and has proven itself time and again in many production settings.

    Avatar of Chris Saylor
    Chris Saylor uses RabbitMQRabbitMQ

    Rabbit acts as our coordinator for all actions that happen during game time. All worker containers connect to rabbit in order to receive game events and emit their own events when applicable.

    Avatar of Clarabridge Engage
    Clarabridge Engage uses RabbitMQRabbitMQ

    Used as central Message Broker; off-loading tasks to be executed asynchronous, used as communication tool between different microservices, used as tool to handle peaks in incoming data, etc.

    Avatar of Analytical Informatics
    Analytical Informatics uses RabbitMQRabbitMQ

    RabbitMQ is the enterprise message bus for our platform, providing infrastructure for managing our ETL queues, real-time event notifications for applications, and audit logging.

    Avatar of Packet
    Packet uses RabbitMQRabbitMQ

    RabbitMQ is an all purpose queuing service for our stack. We use it for user facing jobs as well as keeping track of behind the scenes jobs.

    Avatar of betterPT
    betterPT uses ServerlessServerless

    We use AWS Lambda / Serverless as a Facade for out integrations with EMRs.

    Avatar of JimmyCode
    JimmyCode uses ServerlessServerless

    Oh yeah! We run on lambdas.

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