Alternatives to Beanstalk logo

Alternatives to Beanstalk

AWS Elastic Beanstalk, Heroku, Beanstalkd, Kubernetes, and Git are the most popular alternatives and competitors to Beanstalk.
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What is Beanstalk and what are its top alternatives?

A single process to commit code, review with the team, and deploy the final result to your customers.
Beanstalk is a tool in the Code Collaboration & Version Control category of a tech stack.

Top Alternatives to Beanstalk

  • AWS Elastic Beanstalk
    AWS Elastic Beanstalk

    Once you upload your application, Elastic Beanstalk automatically handles the deployment details of capacity provisioning, load balancing, auto-scaling, and application health monitoring. ...

  • Heroku
    Heroku

    Heroku is a cloud application platform – a new way of building and deploying web apps. Heroku lets app developers spend 100% of their time on their application code, not managing servers, deployment, ongoing operations, or scaling. ...

  • Beanstalkd
    Beanstalkd

    Beanstalks's interface is generic, but was originally designed for reducing the latency of page views in high-volume web applications by running time-consuming tasks asynchronously. ...

  • Kubernetes
    Kubernetes

    Kubernetes is an open source orchestration system for Docker containers. It handles scheduling onto nodes in a compute cluster and actively manages workloads to ensure that their state matches the users declared intentions. ...

  • 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. ...

  • Visual Studio Code
    Visual Studio Code

    Build and debug modern web and cloud applications. Code is free and available on your favorite platform - Linux, Mac OSX, and Windows. ...

  • Docker
    Docker

    The Docker Platform is the industry-leading container platform for continuous, high-velocity innovation, enabling organizations to seamlessly build and share any application — from legacy to what comes next — and securely run them anywhere ...

Beanstalk alternatives & related posts

AWS Elastic Beanstalk logo

AWS Elastic Beanstalk

2.1K
241
Quickly deploy and manage applications in the AWS cloud.
2.1K
241
PROS OF AWS ELASTIC BEANSTALK
  • 77
    Integrates with other aws services
  • 65
    Simple deployment
  • 44
    Fast
  • 28
    Painless
  • 16
    Free
  • 4
    Well-documented
  • 3
    Independend app container
  • 2
    Postgres hosting
  • 2
    Ability to be customized
CONS OF AWS ELASTIC BEANSTALK
  • 2
    Charges appear automatically after exceeding free quota
  • 1
    Lots of moving parts and config
  • 0
    Slow deployments

related AWS Elastic Beanstalk posts

Julien DeFrance
Principal Software Engineer at Tophatter · | 16 upvotes · 3.2M views

Back in 2014, I was given an opportunity to re-architect SmartZip Analytics platform, and flagship product: SmartTargeting. This is a SaaS software helping real estate professionals keeping up with their prospects and leads in a given neighborhood/territory, finding out (thanks to predictive analytics) who's the most likely to list/sell their home, and running cross-channel marketing automation against them: direct mail, online ads, email... The company also does provide Data APIs to Enterprise customers.

I had inherited years and years of technical debt and I knew things had to change radically. The first enabler to this was to make use of the cloud and go with AWS, so we would stop re-inventing the wheel, and build around managed/scalable services.

For the SaaS product, we kept on working with Rails as this was what my team had the most knowledge in. We've however broken up the monolith and decoupled the front-end application from the backend thanks to the use of Rails API so we'd get independently scalable micro-services from now on.

Our various applications could now be deployed using AWS Elastic Beanstalk so we wouldn't waste any more efforts writing time-consuming Capistrano deployment scripts for instance. Combined with Docker so our application would run within its own container, independently from the underlying host configuration.

Storage-wise, we went with Amazon S3 and ditched any pre-existing local or network storage people used to deal with in our legacy systems. On the database side: Amazon RDS / MySQL initially. Ultimately migrated to Amazon RDS for Aurora / MySQL when it got released. Once again, here you need a managed service your cloud provider handles for you.

Future improvements / technology decisions included:

Caching: Amazon ElastiCache / Memcached CDN: Amazon CloudFront Systems Integration: Segment / Zapier Data-warehousing: Amazon Redshift BI: Amazon Quicksight / Superset Search: Elasticsearch / Amazon Elasticsearch Service / Algolia Monitoring: New Relic

As our usage grows, patterns changed, and/or our business needs evolved, my role as Engineering Manager then Director of Engineering was also to ensure my team kept on learning and innovating, while delivering on business value.

One of these innovations was to get ourselves into Serverless : Adopting AWS Lambda was a big step forward. At the time, only available for Node.js (Not Ruby ) but a great way to handle cost efficiency, unpredictable traffic, sudden bursts of traffic... Ultimately you want the whole chain of services involved in a call to be serverless, and that's when we've started leveraging Amazon DynamoDB on these projects so they'd be fully scalable.

See more

We initially started out with Heroku as our PaaS provider due to a desire to use it by our original developer for our Ruby on Rails application/website at the time. We were finding response times slow, it was painfully slow, sometimes taking 10 seconds to start loading the main page. Moving up to the next "compute" level was going to be very expensive.

We moved our site over to AWS Elastic Beanstalk , not only did response times on the site practically become instant, our cloud bill for the application was cut in half.

In database world we are currently using Amazon RDS for PostgreSQL also, we have both MariaDB and Microsoft SQL Server both hosted on Amazon RDS. The plan is to migrate to AWS Aurora Serverless for all 3 of those database systems.

Additional services we use for our public applications: AWS Lambda, Python, Redis, Memcached, AWS Elastic Load Balancing (ELB), Amazon Elasticsearch Service, Amazon ElastiCache

See more
Heroku logo

Heroku

25.6K
3.2K
Build, deliver, monitor and scale web apps and APIs with a trail blazing developer experience.
25.6K
3.2K
PROS OF HEROKU
  • 703
    Easy deployment
  • 459
    Free for side projects
  • 374
    Huge time-saver
  • 348
    Simple scaling
  • 261
    Low devops skills required
  • 190
    Easy setup
  • 174
    Add-ons for almost everything
  • 153
    Beginner friendly
  • 150
    Better for startups
  • 133
    Low learning curve
  • 48
    Postgres hosting
  • 41
    Easy to add collaborators
  • 30
    Faster development
  • 24
    Awesome documentation
  • 19
    Simple rollback
  • 19
    Focus on product, not deployment
  • 15
    Natural companion for rails development
  • 15
    Easy integration
  • 12
    Great customer support
  • 8
    GitHub integration
  • 6
    Painless & well documented
  • 6
    No-ops
  • 4
    I love that they make it free to launch a side project
  • 4
    Free
  • 3
    Great UI
  • 3
    Just works
  • 2
    PostgreSQL forking and following
  • 2
    MySQL extension
  • 1
    Security
  • 1
    Able to host stuff good like Discord Bot
  • 0
    Sec
CONS OF HEROKU
  • 27
    Super expensive
  • 9
    Not a whole lot of flexibility
  • 7
    No usable MySQL option
  • 7
    Storage
  • 5
    Low performance on free tier
  • 2
    24/7 support is $1,000 per month

related Heroku posts

Russel Werner
Lead Engineer at StackShare · | 32 upvotes · 2.9M 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

See more
Simon Reymann
Senior Fullstack Developer at QUANTUSflow Software GmbH · | 30 upvotes · 11.9M 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
Beanstalkd logo

Beanstalkd

111
74
A simple, fast work queue
111
74
PROS OF BEANSTALKD
  • 23
    Fast
  • 12
    Free
  • 12
    Does one thing well
  • 9
    Scalability
  • 8
    Simplicity
  • 3
    External admin UI developer friendly
  • 3
    Job delay
  • 2
    Job prioritization
  • 2
    External admin UI
CONS OF BEANSTALKD
    Be the first to leave a con

    related Beanstalkd posts

    Frédéric MARAND
    Core Developer at OSInet · | 2 upvotes · 234.9K views

    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
    Kubernetes logo

    Kubernetes

    60.2K
    681
    Manage a cluster of Linux containers as a single system to accelerate Dev and simplify Ops
    60.2K
    681
    PROS OF KUBERNETES
    • 166
      Leading docker container management solution
    • 129
      Simple and powerful
    • 107
      Open source
    • 76
      Backed by google
    • 58
      The right abstractions
    • 25
      Scale services
    • 20
      Replication controller
    • 11
      Permission managment
    • 9
      Supports autoscaling
    • 8
      Simple
    • 8
      Cheap
    • 6
      Self-healing
    • 5
      Open, powerful, stable
    • 5
      Reliable
    • 5
      No cloud platform lock-in
    • 5
      Promotes modern/good infrascture practice
    • 4
      Scalable
    • 4
      Quick cloud setup
    • 3
      Custom and extensibility
    • 3
      Captain of Container Ship
    • 3
      Cloud Agnostic
    • 3
      Backed by Red Hat
    • 3
      Runs on azure
    • 3
      A self healing environment with rich metadata
    • 2
      Everything of CaaS
    • 2
      Gke
    • 2
      Golang
    • 2
      Easy setup
    • 2
      Expandable
    • 2
      Sfg
    CONS OF KUBERNETES
    • 16
      Steep learning curve
    • 15
      Poor workflow for development
    • 8
      Orchestrates only infrastructure
    • 4
      High resource requirements for on-prem clusters
    • 2
      Too heavy for simple systems
    • 1
      Additional vendor lock-in (Docker)
    • 1
      More moving parts to secure
    • 1
      Additional Technology Overhead

    related Kubernetes posts

    Conor Myhrvold
    Tech Brand Mgr, Office of CTO at Uber · | 44 upvotes · 13.1M 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
    Yshay Yaacobi

    Our first experience with .NET core was when we developed our OSS feature management platform - Tweek (https://github.com/soluto/tweek). We wanted to create a solution that is able to run anywhere (super important for OSS), has excellent performance characteristics and can fit in a multi-container architecture. We decided to implement our rule engine processor in F# , our main service was implemented in C# and other components were built using JavaScript / TypeScript and Go.

    Visual Studio Code worked really well for us as well, it worked well with all our polyglot services and the .Net core integration had great cross-platform developer experience (to be fair, F# was a bit trickier) - actually, each of our team members used a different OS (Ubuntu, macos, windows). Our production deployment ran for a time on Docker Swarm until we've decided to adopt Kubernetes with almost seamless migration process.

    After our positive experience of running .Net core workloads in containers and developing Tweek's .Net services on non-windows machines, C# had gained back some of its popularity (originally lost to Node.js), and other teams have been using it for developing microservices, k8s sidecars (like https://github.com/Soluto/airbag), cli tools, serverless functions and other projects...

    See more
    Git logo

    Git

    298.9K
    6.6K
    Fast, scalable, distributed revision control system
    298.9K
    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
    • 28
      Distributed
    • 23
      Small & Fast
    • 18
      Feature based workflow
    • 15
      Staging Area
    • 13
      Most wide-spread VSC
    • 11
      Disposable Experimentation
    • 11
      Role-based codelines
    • 7
      Frictionless Context Switching
    • 6
      Data Assurance
    • 5
      Efficient
    • 4
      Just awesome
    • 3
      Easy branching and merging
    • 3
      Github integration
    • 2
      Compatible
    • 2
      Possible to lose history and commits
    • 2
      Flexible
    • 1
      Team Integration
    • 1
      Easy
    • 1
      Light
    • 1
      Fast, scalable, distributed revision control system
    • 1
      Rebase supported natively; reflog; access to plumbing
    • 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
    • 8
      Worst documentation ever possibly made
    • 5
      Awful merge handling
    • 3
      Unexistent preventive security flows
    • 3
      Rebase hell
    • 2
      Ironically even die-hard supporters screw up badly
    • 2
      When --force is disabled, cannot rebase
    • 1
      Doesn't scale for big data

    related Git posts

    Simon Reymann
    Senior Fullstack Developer at QUANTUSflow Software GmbH · | 30 upvotes · 11.9M 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 · 10.1M 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.

    See more
    GitHub logo

    GitHub

    288K
    10.3K
    Powerful collaboration, review, and code management for open source and private development projects
    288K
    10.3K
    PROS OF GITHUB
    • 1.8K
      Open source friendly
    • 1.5K
      Easy source control
    • 1.3K
      Nice UI
    • 1.1K
      Great for team collaboration
    • 868
      Easy setup
    • 504
      Issue tracker
    • 487
      Great community
    • 483
      Remote team collaboration
    • 449
      Great way to share
    • 442
      Pull request and features planning
    • 147
      Just works
    • 132
      Integrated in many tools
    • 122
      Free Public Repos
    • 116
      Github Gists
    • 113
      Github pages
    • 83
      Easy to find repos
    • 62
      Open source
    • 60
      Easy to find projects
    • 60
      It's free
    • 56
      Network effect
    • 49
      Extensive API
    • 43
      Organizations
    • 42
      Branching
    • 34
      Developer Profiles
    • 32
      Git Powered Wikis
    • 30
      Great for collaboration
    • 24
      It's fun
    • 23
      Clean interface and good integrations
    • 22
      Community SDK involvement
    • 20
      Learn from others source code
    • 16
      Because: Git
    • 14
      It integrates directly with Azure
    • 10
      Standard in Open Source collab
    • 10
      Newsfeed
    • 8
      Fast
    • 8
      Beautiful user experience
    • 8
      It integrates directly with Hipchat
    • 7
      Easy to discover new code libraries
    • 6
      It's awesome
    • 6
      Smooth integration
    • 6
      Cloud SCM
    • 6
      Nice API
    • 6
      Graphs
    • 6
      Integrations
    • 5
      Hands down best online Git service available
    • 5
      Reliable
    • 5
      Quick Onboarding
    • 5
      CI Integration
    • 5
      Remarkable uptime
    • 4
      Security options
    • 4
      Loved by developers
    • 4
      Uses GIT
    • 4
      Free HTML hosting
    • 4
      Easy to use and collaborate with others
    • 4
      Version Control
    • 4
      Simple but powerful
    • 4
      Unlimited Public Repos at no cost
    • 3
      Nice to use
    • 3
      IAM
    • 3
      Ci
    • 3
      Easy deployment via SSH
    • 2
      Free private repos
    • 2
      Good tools support
    • 2
      All in one development service
    • 2
      Never dethroned
    • 2
      Easy source control and everything is backed up
    • 2
      Issues tracker
    • 2
      Self Hosted
    • 2
      IAM integration
    • 2
      Very Easy to Use
    • 2
      Easy to use
    • 2
      Leads the copycats
    • 2
      Free HTML hostings
    • 2
      Easy and efficient maintainance of the projects
    • 2
      Beautiful
    • 1
      Dasf
    • 1
      Profound
    CONS OF GITHUB
    • 55
      Owned by micrcosoft
    • 38
      Expensive for lone developers that want private repos
    • 15
      Relatively slow product/feature release cadence
    • 10
      API scoping could be better
    • 9
      Only 3 collaborators for private repos
    • 4
      Limited featureset for issue management
    • 3
      Does not have a graph for showing history like git lens
    • 2
      GitHub Packages does not support SNAPSHOT versions
    • 1
      No multilingual interface
    • 1
      Takes a long time to commit
    • 1
      Expensive

    related GitHub posts

    Johnny Bell

    I was building a personal project that I needed to store items in a real time database. I am more comfortable with my Frontend skills than my backend so I didn't want to spend time building out anything in Ruby or Go.

    I stumbled on Firebase by #Google, and it was really all I needed. It had realtime data, an area for storing file uploads and best of all for the amount of data I needed it was free!

    I built out my application using tools I was familiar with, React for the framework, Redux.js to manage my state across components, and styled-components for the styling.

    Now as this was a project I was just working on in my free time for fun I didn't really want to pay for hosting. I did some research and I found Netlify. I had actually seen them at #ReactRally the year before and deployed a Gatsby site to Netlify already.

    Netlify was very easy to setup and link to my GitHub account you select a repo and pretty much with very little configuration you have a live site that will deploy every time you push to master.

    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.

    See more

    Context: I wanted to create an end to end IoT data pipeline simulation in Google Cloud IoT Core and other GCP services. I never touched Terraform meaningfully until working on this project, and it's one of the best explorations in my development career. The documentation and syntax is incredibly human-readable and friendly. I'm used to building infrastructure through the google apis via Python , but I'm so glad past Sung did not make that decision. I was tempted to use Google Cloud Deployment Manager, but the templates were a bit convoluted by first impression. I'm glad past Sung did not make this decision either.

    Solution: Leveraging Google Cloud Build Google Cloud Run Google Cloud Bigtable Google BigQuery Google Cloud Storage Google Compute Engine along with some other fun tools, I can deploy over 40 GCP resources using Terraform!

    Check Out My Architecture: CLICK ME

    Check out the GitHub repo attached

    See more
    Visual Studio Code logo

    Visual Studio Code

    181K
    2.3K
    Build and debug modern web and cloud applications, by Microsoft
    181K
    2.3K
    PROS OF VISUAL STUDIO CODE
    • 340
      Powerful multilanguage IDE
    • 308
      Fast
    • 193
      Front-end develop out of the box
    • 158
      Support TypeScript IntelliSense
    • 142
      Very basic but free
    • 126
      Git integration
    • 106
      Intellisense
    • 78
      Faster than Atom
    • 53
      Better ui, easy plugins, and nice git integration
    • 45
      Great Refactoring Tools
    • 44
      Good Plugins
    • 42
      Terminal
    • 38
      Superb markdown support
    • 36
      Open Source
    • 35
      Extensions
    • 26
      Awesome UI
    • 26
      Large & up-to-date extension community
    • 24
      Powerful and fast
    • 22
      Portable
    • 18
      Best code editor
    • 18
      Best editor
    • 17
      Easy to get started with
    • 15
      Lots of extensions
    • 15
      Good for begginers
    • 15
      Crossplatform
    • 15
      Built on Electron
    • 14
      Extensions for everything
    • 14
      Open, cross-platform, fast, monthly updates
    • 14
      All Languages Support
    • 13
      Easy to use and learn
    • 12
      "fast, stable & easy to use"
    • 12
      Extensible
    • 11
      Ui design is great
    • 11
      Totally customizable
    • 11
      Git out of the box
    • 11
      Useful for begginer
    • 11
      Faster edit for slow computer
    • 10
      SSH support
    • 10
      Great community
    • 10
      Fast Startup
    • 9
      Works With Almost EveryThing You Need
    • 9
      Great language support
    • 9
      Powerful Debugger
    • 9
      It has terminal and there are lots of shortcuts in it
    • 8
      Can compile and run .py files
    • 8
      Python extension is fast
    • 7
      Features rich
    • 7
      Great document formater
    • 6
      He is not Michael
    • 6
      Extension Echosystem
    • 6
      She is not Rachel
    • 6
      Awesome multi cursor support
    • 5
      VSCode.pro Course makes it easy to learn
    • 5
      Language server client
    • 5
      SFTP Workspace
    • 5
      Very proffesional
    • 5
      Easy azure
    • 4
      Has better support and more extentions for debugging
    • 4
      Supports lots of operating systems
    • 4
      Excellent as git difftool and mergetool
    • 4
      Virtualenv integration
    • 3
      Better autocompletes than Atom
    • 3
      Has more than enough languages for any developer
    • 3
      'batteries included'
    • 3
      More tools to integrate with vs
    • 3
      Emmet preinstalled
    • 2
      VS Code Server: Browser version of VS Code
    • 2
      CMake support with autocomplete
    • 2
      Microsoft
    • 2
      Customizable
    • 2
      Light
    • 2
      Big extension marketplace
    • 2
      Fast and ruby is built right in
    • 1
      File:///C:/Users/ydemi/Downloads/yuksel_demirkaya_webpa
    CONS OF VISUAL STUDIO CODE
    • 46
      Slow startup
    • 29
      Resource hog at times
    • 20
      Poor refactoring
    • 13
      Poor UI Designer
    • 11
      Weak Ui design tools
    • 10
      Poor autocomplete
    • 8
      Super Slow
    • 8
      Huge cpu usage with few installed extension
    • 8
      Microsoft sends telemetry data
    • 7
      Poor in PHP
    • 6
      It's MicroSoft
    • 3
      Poor in Python
    • 3
      No Built in Browser Preview
    • 3
      No color Intergrator
    • 3
      Very basic for java development and buggy at times
    • 3
      No built in live Preview
    • 3
      Electron
    • 2
      Bad Plugin Architecture
    • 2
      Powered by Electron
    • 1
      Terminal does not identify path vars sometimes
    • 1
      Slow C++ Language Server

    related Visual Studio Code posts

    Yshay Yaacobi

    Our first experience with .NET core was when we developed our OSS feature management platform - Tweek (https://github.com/soluto/tweek). We wanted to create a solution that is able to run anywhere (super important for OSS), has excellent performance characteristics and can fit in a multi-container architecture. We decided to implement our rule engine processor in F# , our main service was implemented in C# and other components were built using JavaScript / TypeScript and Go.

    Visual Studio Code worked really well for us as well, it worked well with all our polyglot services and the .Net core integration had great cross-platform developer experience (to be fair, F# was a bit trickier) - actually, each of our team members used a different OS (Ubuntu, macos, windows). Our production deployment ran for a time on Docker Swarm until we've decided to adopt Kubernetes with almost seamless migration process.

    After our positive experience of running .Net core workloads in containers and developing Tweek's .Net services on non-windows machines, C# had gained back some of its popularity (originally lost to Node.js), and other teams have been using it for developing microservices, k8s sidecars (like https://github.com/Soluto/airbag), cli tools, serverless functions and other projects...

    See more
    Simon Reymann
    Senior Fullstack Developer at QUANTUSflow Software GmbH · | 30 upvotes · 11.9M 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
    Docker logo

    Docker

    175.6K
    3.9K
    Enterprise Container Platform for High-Velocity Innovation.
    175.6K
    3.9K
    PROS OF DOCKER
    • 823
      Rapid integration and build up
    • 692
      Isolation
    • 521
      Open source
    • 505
      Testa­bil­i­ty and re­pro­ducibil­i­ty
    • 460
      Lightweight
    • 218
      Standardization
    • 185
      Scalable
    • 106
      Upgrading / down­grad­ing / ap­pli­ca­tion versions
    • 88
      Security
    • 85
      Private paas environments
    • 34
      Portability
    • 26
      Limit resource usage
    • 17
      Game changer
    • 16
      I love the way docker has changed virtualization
    • 14
      Fast
    • 12
      Concurrency
    • 8
      Docker's Compose tools
    • 6
      Easy setup
    • 6
      Fast and Portable
    • 5
      Because its fun
    • 4
      Makes shipping to production very simple
    • 3
      Highly useful
    • 3
      It's dope
    • 2
      Package the environment with the application
    • 2
      Super
    • 2
      Open source and highly configurable
    • 2
      Simplicity, isolation, resource effective
    • 2
      MacOS support FAKE
    • 2
      Its cool
    • 2
      Does a nice job hogging memory
    • 2
      Docker hub for the FTW
    • 2
      HIgh Throughput
    • 2
      Very easy to setup integrate and build
    • 0
      Asdfd
    CONS OF DOCKER
    • 8
      New versions == broken features
    • 6
      Unreliable networking
    • 6
      Documentation not always in sync
    • 4
      Moves quickly
    • 3
      Not Secure

    related Docker posts

    Simon Reymann
    Senior Fullstack Developer at QUANTUSflow Software GmbH · | 30 upvotes · 11.9M 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 · 10.1M 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.

    See more