Alternatives to ActiveMQ logo

Alternatives to ActiveMQ

RabbitMQ, Kafka, Apollo, IBM MQ, and ZeroMQ are the most popular alternatives and competitors to ActiveMQ.
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What is ActiveMQ and what are its top alternatives?

ActiveMQ is a popular open-source message broker written in Java that provides JMS (Java Message Service) support. It offers features such as high availability, message persistence, clustering, and support for various messaging protocols. However, some limitations of ActiveMQ include complex setup and configuration, potential performance issues under heavy loads, and lack of robust monitoring capabilities.

  1. RabbitMQ: RabbitMQ is a robust message broker that supports multiple messaging protocols such as AMQP, MQTT, and STOMP. Key features include high availability, clustering, and flexible routing capabilities. Pros include strong community support, extensive documentation, and a variety of client libraries. Cons compared to ActiveMQ include a steeper learning curve for beginners and more limited support for JMS.

  2. Kafka: Apache Kafka is a distributed streaming platform known for its high throughput and low latency. It is capable of handling real-time data feeds and offers features like fault tolerance, horizontal scalability, and support for complex event processing. Pros of Kafka include excellent performance, fault tolerance, and scalability, while cons include a more specialized use case compared to ActiveMQ and a different messaging model.

  3. NATS: NATS is a lightweight and high-performance messaging system that focuses on simplicity and speed. It offers features like publish-subscribe messaging, request-reply patterns, and support for clustering. Pros of NATS include simplicity, speed, and ease of use, while cons compared to ActiveMQ include less advanced features and a smaller community.

  4. Apache Pulsar: Apache Pulsar is a cloud-native, distributed messaging system that offers features like multi-tenancy, geo-replication, and support for a wide range of messaging patterns. Pros of Pulsar include scalability, performance, and support for modern cloud architectures, while cons compared to ActiveMQ include a newer project with potentially less mature features.

  5. Amazon SQS: Amazon Simple Queue Service (SQS) is a fully managed message queuing service provided by AWS. It offers features like high availability, durability, and scalability without the need for managing infrastructure. Pros of SQS include ease of use, reliability, and integration with other AWS services, while cons compared to ActiveMQ include vendor lock-in and potentially higher costs.

  6. Redis: Redis is an in-memory data structure store that can be used as a message broker with its pub/sub capabilities. It offers features like high performance, data persistence, and support for various data types. Pros of Redis include speed, simplicity, and versatility, while cons compared to ActiveMQ include less advanced messaging features and persistence options.

  7. ZeroMQ: ZeroMQ is a lightweight messaging library that enables fast, asynchronous messaging between applications. It provides features like various messaging patterns, high performance, and low latency. Pros of ZeroMQ include speed, flexibility, and simplicity, while cons compared to ActiveMQ include less built-in support for advanced messaging features and clustering.

  8. IBM MQ: IBM MQ is a messaging middleware that provides reliable messaging between applications and systems. It offers features like guaranteed message delivery, scalability, and support for various platforms. Pros of IBM MQ include enterprise-grade reliability, extensive platform support, and robust security features, while cons compared to ActiveMQ include potential higher costs and a more complex setup process.

  9. HornetQ: HornetQ is an open-source messaging system that provides JMS support and high-performance messaging capabilities. It offers features like clustering, message redistribution, and support for large message sizes. Pros of HornetQ include performance, JMS support, and clustering capabilities, while cons compared to ActiveMQ include potential issues with documentation and community support.

  10. RocketMQ: Apache RocketMQ is a distributed messaging and streaming platform that offers features like reliability, scalability, and support for real-time message processing. Pros of RocketMQ include performance, high availability, and support for big data scenarios, while cons compared to ActiveMQ include potentially less mature features and a smaller community.

Top Alternatives to ActiveMQ

  • RabbitMQ
    RabbitMQ

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

  • Kafka
    Kafka

    Kafka is a distributed, partitioned, replicated commit log service. It provides the functionality of a messaging system, but with a unique design. ...

  • Apollo
    Apollo

    Build a universal GraphQL API on top of your existing REST APIs, so you can ship new application features fast without waiting on backend changes. ...

  • IBM MQ
    IBM MQ

    It is a messaging middleware that simplifies and accelerates the integration of diverse applications and business data across multiple platforms. It offers proven, enterprise-grade messaging capabilities that skillfully and safely move information. ...

  • ZeroMQ
    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. ...

  • JavaScript
    JavaScript

    JavaScript is most known as the scripting language for Web pages, but used in many non-browser environments as well such as node.js or Apache CouchDB. It is a prototype-based, multi-paradigm scripting language that is dynamic,and supports object-oriented, imperative, and functional programming styles. ...

  • Git
    Git

    Git is a free and open source distributed version control system designed to handle everything from small to very large projects with speed and efficiency. ...

  • GitHub
    GitHub

    GitHub is the best place to share code with friends, co-workers, classmates, and complete strangers. Over three million people use GitHub to build amazing things together. ...

ActiveMQ alternatives & related posts

RabbitMQ logo

RabbitMQ

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Open source multiprotocol messaging broker
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PROS OF RABBITMQ
  • 234
    It's fast and it works with good metrics/monitoring
  • 79
    Ease of configuration
  • 59
    I like the admin interface
  • 50
    Easy to set-up and start with
  • 21
    Durable
  • 18
    Intuitive work through python
  • 18
    Standard protocols
  • 10
    Written primarily in Erlang
  • 8
    Simply superb
  • 6
    Completeness of messaging patterns
  • 3
    Scales to 1 million messages per second
  • 3
    Reliable
  • 2
    Distributed
  • 2
    Supports MQTT
  • 2
    Better than most traditional queue based message broker
  • 2
    Supports AMQP
  • 1
    Clusterable
  • 1
    Clear documentation with different scripting language
  • 1
    Great ui
  • 1
    Inubit Integration
  • 1
    Better routing system
  • 1
    High performance
  • 1
    Runs on Open Telecom Platform
  • 1
    Delayed messages
  • 1
    Reliability
  • 1
    Open-source
CONS OF RABBITMQ
  • 9
    Too complicated cluster/HA config and management
  • 6
    Needs Erlang runtime. Need ops good with Erlang runtime
  • 5
    Configuration must be done first, not by your code
  • 4
    Slow

related RabbitMQ posts

James Cunningham
Operations Engineer at Sentry · | 18 upvotes · 1.7M views
Shared insights
on
CeleryCeleryRabbitMQRabbitMQ
at

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

Around the time of their Series A, Pinterest’s stack included Python and Django, with Tornado and Node.js as web servers. Memcached / Membase and Redis handled caching, with RabbitMQ handling queueing. Nginx, HAproxy and Varnish managed static-delivery and load-balancing, with persistent data storage handled by MySQL.

See more
Kafka logo

Kafka

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21.7K
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Distributed, fault tolerant, high throughput pub-sub messaging system
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PROS OF KAFKA
  • 126
    High-throughput
  • 119
    Distributed
  • 92
    Scalable
  • 86
    High-Performance
  • 66
    Durable
  • 38
    Publish-Subscribe
  • 19
    Simple-to-use
  • 18
    Open source
  • 12
    Written in Scala and java. Runs on JVM
  • 9
    Message broker + Streaming system
  • 4
    KSQL
  • 4
    Avro schema integration
  • 4
    Robust
  • 3
    Suport Multiple clients
  • 2
    Extremely good parallelism constructs
  • 2
    Partioned, replayable log
  • 1
    Simple publisher / multi-subscriber model
  • 1
    Fun
  • 1
    Flexible
CONS OF KAFKA
  • 32
    Non-Java clients are second-class citizens
  • 29
    Needs Zookeeper
  • 9
    Operational difficulties
  • 5
    Terrible Packaging

related Kafka posts

Nick Rockwell
SVP, Engineering at Fastly · | 46 upvotes · 3.4M views

When I joined NYT there was already broad dissatisfaction with the LAMP (Linux Apache HTTP Server MySQL PHP) Stack and the front end framework, in particular. So, I wasn't passing judgment on it. I mean, LAMP's fine, you can do good work in LAMP. It's a little dated at this point, but it's not ... I didn't want to rip it out for its own sake, but everyone else was like, "We don't like this, it's really inflexible." And I remember from being outside the company when that was called MIT FIVE when it had launched. And been observing it from the outside, and I was like, you guys took so long to do that and you did it so carefully, and yet you're not happy with your decisions. Why is that? That was more the impetus. If we're going to do this again, how are we going to do it in a way that we're gonna get a better result?

So we're moving quickly away from LAMP, I would say. So, right now, the new front end is React based and using Apollo. And we've been in a long, protracted, gradual rollout of the core experiences.

React is now talking to GraphQL as a primary API. There's a Node.js back end, to the front end, which is mainly for server-side rendering, as well.

Behind there, the main repository for the GraphQL server is a big table repository, that we call Bodega because it's a convenience store. And that reads off of a Kafka pipeline.

See more
Ashish Singh
Tech Lead, Big Data Platform at Pinterest · | 38 upvotes · 3M views

To provide employees with the critical need of interactive querying, we’ve worked with Presto, an open-source distributed SQL query engine, over the years. Operating Presto at Pinterest’s scale has involved resolving quite a few challenges like, supporting deeply nested and huge thrift schemas, slow/ bad worker detection and remediation, auto-scaling cluster, graceful cluster shutdown and impersonation support for ldap authenticator.

Our infrastructure is built on top of Amazon EC2 and we leverage Amazon S3 for storing our data. This separates compute and storage layers, and allows multiple compute clusters to share the S3 data.

We have hundreds of petabytes of data and tens of thousands of Apache Hive tables. Our Presto clusters are comprised of a fleet of 450 r4.8xl EC2 instances. Presto clusters together have over 100 TBs of memory and 14K vcpu cores. Within Pinterest, we have close to more than 1,000 monthly active users (out of total 1,600+ Pinterest employees) using Presto, who run about 400K queries on these clusters per month.

Each query submitted to Presto cluster is logged to a Kafka topic via Singer. Singer is a logging agent built at Pinterest and we talked about it in a previous post. Each query is logged when it is submitted and when it finishes. When a Presto cluster crashes, we will have query submitted events without corresponding query finished events. These events enable us to capture the effect of cluster crashes over time.

Each Presto cluster at Pinterest has workers on a mix of dedicated AWS EC2 instances and Kubernetes pods. Kubernetes platform provides us with the capability to add and remove workers from a Presto cluster very quickly. The best-case latency on bringing up a new worker on Kubernetes is less than a minute. However, when the Kubernetes cluster itself is out of resources and needs to scale up, it can take up to ten minutes. Some other advantages of deploying on Kubernetes platform is that our Presto deployment becomes agnostic of cloud vendor, instance types, OS, etc.

#BigData #AWS #DataScience #DataEngineering

See more
Apollo logo

Apollo

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GraphQL server for Express, Connect, Hapi, Koa and more
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PROS OF APOLLO
  • 12
    From the creators of Meteor
  • 8
    Great documentation
  • 3
    Open source
  • 2
    Real time if use subscription
CONS OF APOLLO
  • 1
    File upload is not supported
  • 1
    Increase in complexity of implementing (subscription)

related Apollo posts

Zach Holman

Oof. I have truly hated JavaScript for a long time. Like, for over twenty years now. Like, since the Clinton administration. It's always been a nightmare to deal with all of the aspects of that silly language.

But wowza, things have changed. Tooling is just way, way better. I'm primarily web-oriented, and using React and Apollo together the past few years really opened my eyes to building rich apps. And I deeply apologize for using the phrase rich apps; I don't think I've ever said such Enterprisey words before.

But yeah, things are different now. I still love Rails, and still use it for a lot of apps I build. But it's that silly rich apps phrase that's the problem. Users have way more comprehensive expectations than they did even five years ago, and the JS community does a good job at building tools and tech that tackle the problems of making heavy, complicated UI and frontend work.

Obviously there's a lot of things happening here, so just saying "JavaScript isn't terrible" might encompass a huge amount of libraries and frameworks. But if you're like me, yeah, give things another shot- I'm somehow not hating on JavaScript anymore and... gulp... I kinda love it.

See more
Nick Rockwell
SVP, Engineering at Fastly · | 46 upvotes · 3.4M views

When I joined NYT there was already broad dissatisfaction with the LAMP (Linux Apache HTTP Server MySQL PHP) Stack and the front end framework, in particular. So, I wasn't passing judgment on it. I mean, LAMP's fine, you can do good work in LAMP. It's a little dated at this point, but it's not ... I didn't want to rip it out for its own sake, but everyone else was like, "We don't like this, it's really inflexible." And I remember from being outside the company when that was called MIT FIVE when it had launched. And been observing it from the outside, and I was like, you guys took so long to do that and you did it so carefully, and yet you're not happy with your decisions. Why is that? That was more the impetus. If we're going to do this again, how are we going to do it in a way that we're gonna get a better result?

So we're moving quickly away from LAMP, I would say. So, right now, the new front end is React based and using Apollo. And we've been in a long, protracted, gradual rollout of the core experiences.

React is now talking to GraphQL as a primary API. There's a Node.js back end, to the front end, which is mainly for server-side rendering, as well.

Behind there, the main repository for the GraphQL server is a big table repository, that we call Bodega because it's a convenience store. And that reads off of a Kafka pipeline.

See more
IBM MQ logo

IBM MQ

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Enterprise-grade messaging middleware
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PROS OF IBM MQ
  • 3
    Reliable for banking transactions
  • 3
    Useful for big enteprises
  • 2
    Secure
  • 1
    Broader connectivity - more protocols, APIs, Files etc
  • 1
    Many deployment options (containers, cloud, VM etc)
  • 1
    High Availability
CONS OF IBM MQ
  • 2
    Cost

related IBM MQ posts

Shared insights
on
Azure Service BusAzure Service BusIBM MQIBM MQ

Want to get the differences in features and enhancement, pros and cons, and also how to Migrate from IBM MQ to Azure Service Bus.

See more
ZeroMQ logo

ZeroMQ

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581
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Fast, lightweight messaging library that allows you to design complex communication system without much effort
260
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PROS OF ZEROMQ
  • 23
    Fast
  • 20
    Lightweight
  • 11
    Transport agnostic
  • 7
    No broker required
  • 4
    Low level APIs are in C
  • 4
    Low latency
  • 1
    Open source
  • 1
    Publish-Subscribe
CONS OF ZEROMQ
  • 5
    No message durability
  • 3
    Not a very reliable system - message delivery wise
  • 1
    M x N problem with M producers and N consumers

related ZeroMQ posts

Shared insights
on
MongoDBMongoDBZeroMQZeroMQSpring BootSpring Boot

In our Spring Boot application, which encompasses various projects, we employ ZeroMQ (ZMQ) for communication via a req/resp pattern. Recently, I observed that data is persisted in the MongoDB database before being transmitted to other applications. I've identified a method to monitor changes to the database, and I'm contemplating whether to utilize this monitoring approach to detect changes and execute the necessary instructions.

Which approach is more advisable in this scenario: leveraging the database monitoring mechanism or sticking with the current ZMQ req/resp communication?

Essentially, I'm seeking guidance on whether to rely on database monitoring for change detection and subsequent actions or to continue with the existing ZMQ communication pattern.

See more
Meili Triantafyllidi
Software engineer at Digital Science · | 6 upvotes · 443.4K views
Shared insights
on
Amazon SQSAmazon SQSRabbitMQRabbitMQZeroMQZeroMQ

Hi, we are in a ZMQ set up in a push/pull pattern, and we currently start to have more traffic and cases that the service is unavailable or stuck. We want to: * Not loose messages in services outages * Safely restart service without losing messages (ZeroMQ seems to need to close the socket in the receiver before restart manually)

Do you have experience with this setup with ZeroMQ? Would you suggest RabbitMQ or Amazon SQS (we are in AWS setup) instead? Something else?

Thank you for your time

See more
JavaScript logo

JavaScript

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8.1K
Lightweight, interpreted, object-oriented language with first-class functions
351.1K
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PROS OF JAVASCRIPT
  • 1.7K
    Can be used on frontend/backend
  • 1.5K
    It's everywhere
  • 1.2K
    Lots of great frameworks
  • 896
    Fast
  • 745
    Light weight
  • 425
    Flexible
  • 392
    You can't get a device today that doesn't run js
  • 286
    Non-blocking i/o
  • 237
    Ubiquitousness
  • 191
    Expressive
  • 55
    Extended functionality to web pages
  • 49
    Relatively easy language
  • 46
    Executed on the client side
  • 30
    Relatively fast to the end user
  • 25
    Pure Javascript
  • 21
    Functional programming
  • 15
    Async
  • 13
    Full-stack
  • 12
    Its everywhere
  • 12
    Future Language of The Web
  • 12
    Setup is easy
  • 11
    JavaScript is the New PHP
  • 11
    Because I love functions
  • 10
    Like it or not, JS is part of the web standard
  • 9
    Expansive community
  • 9
    Can be used in backend, frontend and DB
  • 9
    Easy
  • 9
    Everyone use it
  • 8
    Most Popular Language in the World
  • 8
    Can be used both as frontend and backend as well
  • 8
    Powerful
  • 8
    For the good parts
  • 8
    No need to use PHP
  • 8
    Easy to hire developers
  • 7
    Love-hate relationship
  • 7
    Agile, packages simple to use
  • 7
    Its fun and fast
  • 7
    Hard not to use
  • 7
    Nice
  • 7
    Versitile
  • 7
    Evolution of C
  • 7
    Photoshop has 3 JS runtimes built in
  • 7
    It's fun
  • 7
    Popularized Class-Less Architecture & Lambdas
  • 7
    Supports lambdas and closures
  • 6
    Can be used on frontend/backend/Mobile/create PRO Ui
  • 6
    1.6K Can be used on frontend/backend
  • 6
    Client side JS uses the visitors CPU to save Server Res
  • 6
    It let's me use Babel & Typescript
  • 6
    Easy to make something
  • 5
    What to add
  • 5
    Clojurescript
  • 5
    Stockholm Syndrome
  • 5
    Function expressions are useful for callbacks
  • 5
    Scope manipulation
  • 5
    Everywhere
  • 5
    Client processing
  • 5
    Promise relationship
  • 4
    Because it is so simple and lightweight
  • 4
    Only Programming language on browser
  • 1
    Easy to learn
  • 1
    Not the best
  • 1
    Hard to learn
  • 1
    Easy to understand
  • 1
    Test
  • 1
    Test2
  • 1
    Subskill #4
  • 0
    Hard 彤
CONS OF JAVASCRIPT
  • 22
    A constant moving target, too much churn
  • 20
    Horribly inconsistent
  • 15
    Javascript is the New PHP
  • 9
    No ability to monitor memory utilitization
  • 8
    Shows Zero output in case of ANY error
  • 7
    Thinks strange results are better than errors
  • 6
    Can be ugly
  • 3
    No GitHub
  • 2
    Slow

related JavaScript posts

Zach Holman

Oof. I have truly hated JavaScript for a long time. Like, for over twenty years now. Like, since the Clinton administration. It's always been a nightmare to deal with all of the aspects of that silly language.

But wowza, things have changed. Tooling is just way, way better. I'm primarily web-oriented, and using React and Apollo together the past few years really opened my eyes to building rich apps. And I deeply apologize for using the phrase rich apps; I don't think I've ever said such Enterprisey words before.

But yeah, things are different now. I still love Rails, and still use it for a lot of apps I build. But it's that silly rich apps phrase that's the problem. Users have way more comprehensive expectations than they did even five years ago, and the JS community does a good job at building tools and tech that tackle the problems of making heavy, complicated UI and frontend work.

Obviously there's a lot of things happening here, so just saying "JavaScript isn't terrible" might encompass a huge amount of libraries and frameworks. But if you're like me, yeah, give things another shot- I'm somehow not hating on JavaScript anymore and... gulp... I kinda love it.

See more
Conor Myhrvold
Tech Brand Mgr, Office of CTO at Uber · | 44 upvotes · 10.1M views

How Uber developed the open source, end-to-end distributed tracing Jaeger , now a CNCF project:

Distributed tracing is quickly becoming a must-have component in the tools that organizations use to monitor their complex, microservice-based architectures. At Uber, our open source distributed tracing system Jaeger saw large-scale internal adoption throughout 2016, integrated into hundreds of microservices and now recording thousands of traces every second.

Here is the story of how we got here, from investigating off-the-shelf solutions like Zipkin, to why we switched from pull to push architecture, and how distributed tracing will continue to evolve:

https://eng.uber.com/distributed-tracing/

(GitHub Pages : https://www.jaegertracing.io/, GitHub: https://github.com/jaegertracing/jaeger)

Bindings/Operator: Python Java Node.js Go C++ Kubernetes JavaScript OpenShift C# Apache Spark

See more
Git logo

Git

290K
174.3K
6.6K
Fast, scalable, distributed revision control system
290K
174.3K
+ 1
6.6K
PROS OF GIT
  • 1.4K
    Distributed version control system
  • 1.1K
    Efficient branching and merging
  • 959
    Fast
  • 845
    Open source
  • 726
    Better than svn
  • 368
    Great command-line application
  • 306
    Simple
  • 291
    Free
  • 232
    Easy to use
  • 222
    Does not require server
  • 27
    Distributed
  • 22
    Small & Fast
  • 18
    Feature based workflow
  • 15
    Staging Area
  • 13
    Most wide-spread VSC
  • 11
    Role-based codelines
  • 11
    Disposable Experimentation
  • 7
    Frictionless Context Switching
  • 6
    Data Assurance
  • 5
    Efficient
  • 4
    Just awesome
  • 3
    Github integration
  • 3
    Easy branching and merging
  • 2
    Compatible
  • 2
    Flexible
  • 2
    Possible to lose history and commits
  • 1
    Rebase supported natively; reflog; access to plumbing
  • 1
    Light
  • 1
    Team Integration
  • 1
    Fast, scalable, distributed revision control system
  • 1
    Easy
  • 1
    Flexible, easy, Safe, and fast
  • 1
    CLI is great, but the GUI tools are awesome
  • 1
    It's what you do
  • 0
    Phinx
CONS OF GIT
  • 16
    Hard to learn
  • 11
    Inconsistent command line interface
  • 9
    Easy to lose uncommitted work
  • 7
    Worst documentation ever possibly made
  • 5
    Awful merge handling
  • 3
    Unexistent preventive security flows
  • 3
    Rebase hell
  • 2
    When --force is disabled, cannot rebase
  • 2
    Ironically even die-hard supporters screw up badly
  • 1
    Doesn't scale for big data

related Git posts

Simon Reymann
Senior Fullstack Developer at QUANTUSflow Software GmbH · | 30 upvotes · 9.3M views

Our whole DevOps stack consists of the following tools:

  • GitHub (incl. GitHub Pages/Markdown for Documentation, GettingStarted and HowTo's) for collaborative review and code management tool
  • Respectively Git as revision control system
  • SourceTree as Git GUI
  • Visual Studio Code as IDE
  • CircleCI for continuous integration (automatize development process)
  • Prettier / TSLint / ESLint as code linter
  • SonarQube as quality gate
  • Docker as container management (incl. Docker Compose for multi-container application management)
  • VirtualBox for operating system simulation tests
  • Kubernetes as cluster management for docker containers
  • Heroku for deploying in test environments
  • nginx as web server (preferably used as facade server in production environment)
  • SSLMate (using OpenSSL) for certificate management
  • Amazon EC2 (incl. Amazon S3) for deploying in stage (production-like) and production environments
  • PostgreSQL as preferred database system
  • Redis as preferred in-memory database/store (great for caching)

The main reason we have chosen Kubernetes over Docker Swarm is related to the following artifacts:

  • Key features: Easy and flexible installation, Clear dashboard, Great scaling operations, Monitoring is an integral part, Great load balancing concepts, Monitors the condition and ensures compensation in the event of failure.
  • Applications: An application can be deployed using a combination of pods, deployments, and services (or micro-services).
  • Functionality: Kubernetes as a complex installation and setup process, but it not as limited as Docker Swarm.
  • Monitoring: It supports multiple versions of logging and monitoring when the services are deployed within the cluster (Elasticsearch/Kibana (ELK), Heapster/Grafana, Sysdig cloud integration).
  • Scalability: All-in-one framework for distributed systems.
  • Other Benefits: Kubernetes is backed by the Cloud Native Computing Foundation (CNCF), huge community among container orchestration tools, it is an open source and modular tool that works with any OS.
See more
Tymoteusz Paul
Devops guy at X20X Development LTD · | 23 upvotes · 8.3M views

Often enough I have to explain my way of going about setting up a CI/CD pipeline with multiple deployment platforms. Since I am a bit tired of yapping the same every single time, I've decided to write it up and share with the world this way, and send people to read it instead ;). I will explain it on "live-example" of how the Rome got built, basing that current methodology exists only of readme.md and wishes of good luck (as it usually is ;)).

It always starts with an app, whatever it may be and reading the readmes available while Vagrant and VirtualBox is installing and updating. Following that is the first hurdle to go over - convert all the instruction/scripts into Ansible playbook(s), and only stopping when doing a clear vagrant up or vagrant reload we will have a fully working environment. As our Vagrant environment is now functional, it's time to break it! This is the moment to look for how things can be done better (too rigid/too lose versioning? Sloppy environment setup?) and replace them with the right way to do stuff, one that won't bite us in the backside. This is the point, and the best opportunity, to upcycle the existing way of doing dev environment to produce a proper, production-grade product.

I should probably digress here for a moment and explain why. I firmly believe that the way you deploy production is the same way you should deploy develop, shy of few debugging-friendly setting. This way you avoid the discrepancy between how production work vs how development works, which almost always causes major pains in the back of the neck, and with use of proper tools should mean no more work for the developers. That's why we start with Vagrant as developer boxes should be as easy as vagrant up, but the meat of our product lies in Ansible which will do meat of the work and can be applied to almost anything: AWS, bare metal, docker, LXC, in open net, behind vpn - you name it.

We must also give proper consideration to monitoring and logging hoovering at this point. My generic answer here is to grab Elasticsearch, Kibana, and Logstash. While for different use cases there may be better solutions, this one is well battle-tested, performs reasonably and is very easy to scale both vertically (within some limits) and horizontally. Logstash rules are easy to write and are well supported in maintenance through Ansible, which as I've mentioned earlier, are at the very core of things, and creating triggers/reports and alerts based on Elastic and Kibana is generally a breeze, including some quite complex aggregations.

If we are happy with the state of the Ansible it's time to move on and put all those roles and playbooks to work. Namely, we need something to manage our CI/CD pipelines. For me, the choice is obvious: TeamCity. It's modern, robust and unlike most of the light-weight alternatives, it's transparent. What I mean by that is that it doesn't tell you how to do things, doesn't limit your ways to deploy, or test, or package for that matter. Instead, it provides a developer-friendly and rich playground for your pipelines. You can do most the same with Jenkins, but it has a quite dated look and feel to it, while also missing some key functionality that must be brought in via plugins (like quality REST API which comes built-in with TeamCity). It also comes with all the common-handy plugins like Slack or Apache Maven integration.

The exact flow between CI and CD varies too greatly from one application to another to describe, so I will outline a few rules that guide me in it: 1. Make build steps as small as possible. This way when something breaks, we know exactly where, without needing to dig and root around. 2. All security credentials besides development environment must be sources from individual Vault instances. Keys to those containers should exist only on the CI/CD box and accessible by a few people (the less the better). This is pretty self-explanatory, as anything besides dev may contain sensitive data and, at times, be public-facing. Because of that appropriate security must be present. TeamCity shines in this department with excellent secrets-management. 3. Every part of the build chain shall consume and produce artifacts. If it creates nothing, it likely shouldn't be its own build. This way if any issue shows up with any environment or version, all developer has to do it is grab appropriate artifacts to reproduce the issue locally. 4. Deployment builds should be directly tied to specific Git branches/tags. This enables much easier tracking of what caused an issue, including automated identifying and tagging the author (nothing like automated regression testing!).

Speaking of deployments, I generally try to keep it simple but also with a close eye on the wallet. Because of that, I am more than happy with AWS or another cloud provider, but also constantly peeking at the loads and do we get the value of what we are paying for. Often enough the pattern of use is not constantly erratic, but rather has a firm baseline which could be migrated away from the cloud and into bare metal boxes. That is another part where this approach strongly triumphs over the common Docker and CircleCI setup, where you are very much tied in to use cloud providers and getting out is expensive. Here to embrace bare-metal hosting all you need is a help of some container-based self-hosting software, my personal preference is with Proxmox and LXC. Following that all you must write are ansible scripts to manage hardware of Proxmox, similar way as you do for Amazon EC2 (ansible supports both greatly) and you are good to go. One does not exclude another, quite the opposite, as they can live in great synergy and cut your costs dramatically (the heavier your base load, the bigger the savings) while providing production-grade resiliency.

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With the selection of these tools I was able to build out my application, connect it to a realtime database, and deploy to a live environment all with $0 spent.

If you're looking to build out a small app I suggest giving these tools a go as you can get your idea out into the real world for absolutely no cost.

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Russel Werner
Lead Engineer at StackShare · | 32 upvotes · 2.2M views

StackShare Feed is built entirely with React, Glamorous, and Apollo. One of our objectives with the public launch of the Feed was to enable a Server-side rendered (SSR) experience for our organic search traffic. When you visit the StackShare Feed, and you aren't logged in, you are delivered the Trending feed experience. We use an in-house Node.js rendering microservice to generate this HTML. This microservice needs to run and serve requests independent of our Rails web app. Up until recently, we had a mono-repo with our Rails and React code living happily together and all served from the same web process. In order to deploy our SSR app into a Heroku environment, we needed to split out our front-end application into a separate repo in GitHub. The driving factor in this decision was mostly due to limitations imposed by Heroku specifically with how processes can't communicate with each other. A new SSR app was created in Heroku and linked directly to the frontend repo so it stays in-sync with changes.

Related to this, we need a way to "deploy" our frontend changes to various server environments without building & releasing the entire Ruby application. We built a hybrid Amazon S3 Amazon CloudFront solution to host our Webpack bundles. A new CircleCI script builds the bundles and uploads them to S3. The final step in our rollout is to update some keys in Redis so our Rails app knows which bundles to serve. The result of these efforts were significant. Our frontend team now moves independently of our backend team, our build & release process takes only a few minutes, we are now using an edge CDN to serve JS assets, and we have pre-rendered React pages!

#StackDecisionsLaunch #SSR #Microservices #FrontEndRepoSplit

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