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Jenkins, CircleCI, GitLab CI, GitLab, and Bamboo are the most popular alternatives and competitors to Travis CI.
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What is Travis CI?

Free for open source projects, our CI environment provides multiple runtimes (e.g. Node.js or PHP versions), data stores and so on. Because of this, hosting your project on travis-ci.com means you can effortlessly test your library or applications against multiple runtimes and data stores without even having all of them installed locally.
Travis CI is a tool in the Continuous Integration category of a tech stack.

Travis CI alternatives & related posts

related Jenkins posts

Thierry Schellenbach
Thierry Schellenbach
CEO at Stream · | 23 upvotes · 11.5K views
atStreamStream
Go
Go
Jenkins
Jenkins
GitHub
GitHub
Travis CI
Travis CI
#CodeCollaborationVersionControl
#ContinuousIntegration

Releasing new versions of our services is done by Travis CI. Travis first runs our test suite. Once it passes, it publishes a new release binary to GitHub.

Common tasks such as installing dependencies for the Go project, or building a binary are automated using plain old Makefiles. (We know, crazy old school, right?) Our binaries are compressed using UPX.

Travis has come a long way over the past years. I used to prefer Jenkins in some cases since it was easier to debug broken builds. With the addition of the aptly named “debug build” button, Travis is now the clear winner. It’s easy to use and free for open source, with no need to maintain anything.

#ContinuousIntegration #CodeCollaborationVersionControl

See more
GitHub
GitHub
nginx
nginx
ESLint
ESLint
AVA
AVA
Semantic UI React
Semantic UI React
Redux
Redux
React
React
PostgreSQL
PostgreSQL
ExpressJS
ExpressJS
Node.js
Node.js
FeathersJS
FeathersJS
Heroku
Heroku
Amazon EC2
Amazon EC2
Kubernetes
Kubernetes
Jenkins
Jenkins
Docker Compose
Docker Compose
Docker
Docker
#Frontend
#Stack
#Backend
#Containers
#Containerized

Recently I have been working on an open source stack to help people consolidate their personal health data in a single database so that AI and analytics apps can be run against it to find personalized treatments. We chose to go with a #containerized approach leveraging Docker #containers with a local development environment setup with Docker Compose and nginx for container routing. For the production environment we chose to pull code from GitHub and build/push images using Jenkins and using Kubernetes to deploy to Amazon EC2.

We also implemented a dashboard app to handle user authentication/authorization, as well as a custom SSO server that runs on Heroku which allows experts to easily visit more than one instance without having to login repeatedly. The #Backend was implemented using my favorite #Stack which consists of FeathersJS on top of Node.js and ExpressJS with PostgreSQL as the main database. The #Frontend was implemented using React, Redux.js, Semantic UI React and the FeathersJS client. Though testing was light on this project, we chose to use AVA as well as ESLint to keep the codebase clean and consistent.

See more

related CircleCI posts

Oliver Burn
Oliver Burn
Architect at Atlassian · | 12 upvotes · 64.1K views
atAtlassianAtlassian
Azure Pipelines
Azure Pipelines
jFrog
jFrog
Octopus Deploy
Octopus Deploy
AWS CodePipeline
AWS CodePipeline
CircleCI
CircleCI
Bitbucket
Bitbucket
Jira
Jira

We recently added new APIs to Jira to associate information about Builds and Deployments to Jira issues.

The new APIs were developed using a spec-first API approach for speed and sanity. The details of this approach are described in this blog post, and we relied on using Swagger and associated tools like Swagger UI.

A new service was created for managing the data. It provides a REST API for external use, and an internal API based on GraphQL. The service is built using Kotlin for increased developer productivity and happiness, and the Spring-Boot framework. PostgreSQL was chosen for the persistence layer, as we have non-trivial requirements that cannot be easily implemented on top of a key-value store.

The front-end has been built using React and querying the back-end service using an internal GraphQL API. We have plans of providing a public GraphQL API in the future.

New Jira Integrations: Bitbucket CircleCI AWS CodePipeline Octopus Deploy jFrog Azure Pipelines

See more
Tymoteusz Paul
Tymoteusz Paul
Devops guy at X20X Development LTD · | 11 upvotes · 144.6K views
Amazon EC2
Amazon EC2
LXC
LXC
CircleCI
CircleCI
Docker
Docker
Git
Git
Vault
Vault
Apache Maven
Apache Maven
Slack
Slack
Jenkins
Jenkins
TeamCity
TeamCity
Logstash
Logstash
Kibana
Kibana
Elasticsearch
Elasticsearch
Ansible
Ansible
VirtualBox
VirtualBox
Vagrant
Vagrant

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

related GitLab CI posts

Joshua Dean Küpper
Joshua Dean Küpper
CEO at Scrayos UG (haftungsbeschränkt) · | 6 upvotes · 19.2K views
atScrayos UG (haftungsbeschränkt)Scrayos UG (haftungsbeschränkt)
Jenkins
Jenkins
GitLab Pages
GitLab Pages
GitLab
GitLab
GitLab CI
GitLab CI

We use GitLab CI because of the great native integration as a part of the GitLab framework and the linting-capabilities it offers. The visualization of complex pipelines and the embedding within the project overview made Gitlab CI even more convenient. We use it for all projects, all deployments and as a part of GitLab Pages.

While we initially used the Shell-executor, we quickly switched to the Docker-executor and use it exclusively now.

We formerly used Jenkins but preferred to handle everything within GitLab . Aside from the unification of our infrastructure another motivation was the "configuration-in-file"-approach, that Gitlab CI offered, while Jenkins support of this concept was very limited and users had to resort to using the webinterface. Since the file is included within the repository, it is also version controlled, which was a huge plus for us.

See more
Sebastian Dellwig
Sebastian Dellwig
Tech Lead at Porsche Digital GmbH · | 6 upvotes · 10.2K views
Codeship
Codeship
CircleCI
CircleCI
GitLab CI
GitLab CI

We are using GitLab CI and were very happy with it. The integration of all tools like CI/CD, tickets, etc makes it very easy to stay on top of things. But be aware, Gitlab currently does not have iOS build support. So if you want to exchange that for CircleCI / Codeship to have to invest some effort. We are using a managed Mac OS device and installed the Gitlab runner there, to have iOS builds.

See more

related GitLab posts

Michael Kelly
Michael Kelly
Senior Software Engineer at StackShare · | 14 upvotes · 128.6K views
atACK FoundryACK Foundry
Bitbucket
Bitbucket
GitLab Pages
GitLab Pages
GitLab CI
GitLab CI
GitHub
GitHub
GitLab
GitLab
#OpenSourceCloud

I use GitLab when building side-projects and MVPs. The interface and interactions are close enough to those of GitHub to prevent cognitive switching costs between professional and personal projects hosted on different services.

GitLab also provides a suite of tools including issue/project management, CI/CD with GitLab CI, and validation/landing pages with GitLab Pages. With everything in one place, on an #OpenSourceCloud GitLab makes it easy for me to manage much larger projects on my own, than would be possible with other solutions or tools.

It's petty I know, but I can also read the GitLab code diffs far more easily than diffs on GitHub or Bitbucket...they just look better in my opinion.

See more
Tim Abbott
Tim Abbott
Founder at Zulip · | 13 upvotes · 111.4K views
atZulipZulip
GitLab
GitLab
GitHub
GitHub

I have mixed feelings on GitHub as a product and our use of it for the Zulip open source project. On the one hand, I do feel that being on GitHub helps people discover Zulip, because we have enough stars (etc.) that we rank highly among projects on the platform. and there is a definite benefit for lowering barriers to contribution (which is important to us) that GitHub has such a dominant position in terms of what everyone has accounts with.

But even ignoring how one might feel about their new corporate owner (MicroSoft), in a lot of ways GitHub is a bad product for open source projects. Years after the "Dear GitHub" letter, there are still basic gaps in its issue tracker:

  • You can't give someone permission to label/categorize issues without full write access to a project (including ability to merge things to master, post releases, etc.).
  • You can't let anyone with a GitHub account self-assign issues to themselves.
  • Many more similar issues.

It's embarrassing, because I've talked to GitHub product managers at various open source events about these things for 3 years, and they always agree the thing is important, but then nothing ever improves in the Issues product. Maybe the new management at MicroSoft will fix their product management situation, but if not, I imagine we'll eventually do the migration to GitLab.

We have a custom bot project, http://github.com/zulip/zulipbot, to deal with some of these issues where possible, and every other large project we talk to does the same thing, more or less.

See more
Bamboo logo

Bamboo

247
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247
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Tie automated builds, tests, and releases together in a single workflow
Bamboo logo
VS
Travis CI logo
Compare Bamboo vs Travis CI
Bamboo logo
Bamboo
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Travis CI

related TeamCity posts

Tymoteusz Paul
Tymoteusz Paul
Devops guy at X20X Development LTD · | 11 upvotes · 144.6K views
Amazon EC2
Amazon EC2
LXC
LXC
CircleCI
CircleCI
Docker
Docker
Git
Git
Vault
Vault
Apache Maven
Apache Maven
Slack
Slack
Jenkins
Jenkins
TeamCity
TeamCity
Logstash
Logstash
Kibana
Kibana
Elasticsearch
Elasticsearch
Ansible
Ansible
VirtualBox
VirtualBox
Vagrant
Vagrant

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
Sarah Elson
Sarah Elson
Product Growth at LambdaTest · | 4 upvotes · 1.1K views
atLambdaTestLambdaTest
CircleCI
CircleCI
TeamCity
TeamCity
Cucumber
Cucumber
PHP
PHP
Python
Python
Java
Java
JavaScript
JavaScript
Selenium
Selenium
LambdaTest
LambdaTest
#Hunted
#Producthunt
#Webdriver
#Selenium
#Seleniumgrid

@producthunt LambdaTest Selenium JavaScript Java Python PHP Cucumber TeamCity CircleCI With this new release of LambdaTest automation, you can run tests across an Online Selenium Grid of 2000+ browsers and OS combinations to perform cross browser testing. This saves you from the pain of maintaining the infrastructure and also saves you the licensing costs for browsers and operating systems. #testing #Seleniumgrid #Selenium #testautomation #automation #webdriver #producthunt hunted

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related Appveyor posts

GitHub
GitHub
Appveyor
Appveyor
Travis CI
Travis CI

I recommend using Travis CI and/or Appveyor in all projects.

Projects using these tools have given me confidence to know that I don't cause any breaking changes. Travis CI and Appveyor have functionality to test components of a project across multiple installation projects to ensure that modifications don't break a project. These tools integrate easily with GitHub and are useful in open source projects that must review contributions from many different people.

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related Codeship posts

Sebastian Dellwig
Sebastian Dellwig
Tech Lead at Porsche Digital GmbH · | 6 upvotes · 10.2K views
Codeship
Codeship
CircleCI
CircleCI
GitLab CI
GitLab CI

We are using GitLab CI and were very happy with it. The integration of all tools like CI/CD, tickets, etc makes it very easy to stay on top of things. But be aware, Gitlab currently does not have iOS build support. So if you want to exchange that for CircleCI / Codeship to have to invest some effort. We are using a managed Mac OS device and installed the Gitlab runner there, to have iOS builds.

See more
GitHub
GitHub
Slack
Slack
Semaphore
Semaphore
Codeship
Codeship

When it comes to continuous Integration services, the choice is hard. There are several solutions available and it looks like the dev scene is very split. We've read and reviewed several solutions and we ended up making the choice between Codeship and Semaphore . Although Semaphore is used by slightly more developers, we've experienced a faster and easy flow using Codeship. Both do integrate Slack and GitHub very well, so this is not a point to set them apart. Both have a complex pricing system that is not that easy to calculate and predict. However, out in the wild, we found Codeship to have a better price point at heavy use.

See more

related AWS CodeBuild posts

cazzer
cazzer
Lead Software Engineer · | 2 upvotes · 5.8K views
atVolta IndustriesVolta Industries
AWS CloudFormation
AWS CloudFormation
AWS Lambda
AWS Lambda
AWS CodeBuild
AWS CodeBuild
AWS CodePipeline
AWS CodePipeline

At Volta we use AWS CodePipeline and AWS CodeBuild to automatically ship new AWS Lambda services without any effort. And we do it all with AWS CloudFormation, since configuration is easier to maintain than code.

See more

related Codecov posts

Tim Abbott
Tim Abbott
Founder at Zulip · | 4 upvotes · 4.9K views
atZulipZulip
Coveralls
Coveralls
Codecov
Codecov

We use Codecov because it's a lot better than Coveralls. Both of them provide the useful feature of having nice web-accessible reports of which files have what level of test coverage (though every coverage tool produces reasonably nice HTML in a directory on the local filesystem), and can report on PRs cases where significant new code was added without test coverage.

That said, I'm pretty unhappy with both of them for our use case. The fundamental problem with both of them is that they don't handle the ~1% probability situations with missing data due to networking flakiness well. The reason I think our use case is relevant is that we submit coverage data from multiple jobs (one that runs our frontend test suite and another that runs our backend test suite), and the coverage provider is responsible for combining that data together.

I think the problem is if a test suite runs successfully but due to some operational/networking error between Travis/CircleCI and Codecov the coverage data for part of the codebase doesn't get submitted, Codecov will report a huge coverage drop in a way that is very confusing for our contributors (because they experience it as "why did the coverage drop 12%, all I did was added a test").

We migrated from Coveralls to Codecov because empirically this sort of breakage happened 10x less on Codecov, but it still happens way more often than I'd like.

I wish they put more effort in their retry mechanism and/or providing clearer debugging information (E.g. a big "Missing data" banner) so that one didn't need to be specifically told to ignore Codecov/Coveralls when it reports a giant coverage drop.

See more
Coveralls
Coveralls
Codecov
Codecov

Codecov Although I actually use both codecov and Coveralls, I very much like the graphs I get from codecov, and some of their diagnostic tools.

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related Drone.io posts

Drone.io
Drone.io
Docker
Docker
#DeploymentWorkflow

We use Docker for our #DeploymentWorkflow along with Drone.io

See more
Drone.io
Drone.io

Drone acts as our CI service for testing our application. We also use it as a deployment server for building docker images for production once tests pass on the master branch. The docker image acts as a deployment artifact that Convox can use to deploy.

Our client platform utilizes Electron which is also built and pushed to S3 for download. Drone.io

See more

related Semaphore posts

GitHub
GitHub
Slack
Slack
Semaphore
Semaphore
Codeship
Codeship

When it comes to continuous Integration services, the choice is hard. There are several solutions available and it looks like the dev scene is very split. We've read and reviewed several solutions and we ended up making the choice between Codeship and Semaphore . Although Semaphore is used by slightly more developers, we've experienced a faster and easy flow using Codeship. Both do integrate Slack and GitHub very well, so this is not a point to set them apart. Both have a complex pricing system that is not that easy to calculate and predict. However, out in the wild, we found Codeship to have a better price point at heavy use.

See more

related GoCD posts

Benjamin Poon
Benjamin Poon
QA Manager - Engineering at HBC Digital · | 7 upvotes · 13.5K views
PostgreSQL
PostgreSQL
React
React
ExpressJS
ExpressJS
Docker
Docker
GoCD
GoCD
GitHub
GitHub
Cucumber
Cucumber
JavaScript
JavaScript
Selenium
Selenium
Nightwatchjs
Nightwatchjs

For our digital QA organization to support a complex hybrid monolith/microservice architecture, our team took on the lofty goal of building out a commonized UI test automation framework. One of the primary requisites included a technical minimalist threshold such that an engineer or analyst with fundamental knowledge of JavaScript could automate their tests with greater ease. Just to list a few: - Nightwatchjs - Selenium - Cucumber - GitHub - Go.CD - Docker - ExpressJS - React - PostgreSQL

With this structure, we're able to combine the automation efforts of each team member into a centralized repository while also providing new relevant metrics to business owners.

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related Bitrise posts

Jesus Dario Rivera Rubio
Jesus Dario Rivera Rubio
Telecomm Engineering at Netbeast · | 10 upvotes · 67.3K views
atNetbeastNetbeast
Mailjet
Mailjet
Intercom
Intercom
Amplitude
Amplitude
Firebase
Firebase
GitHub
GitHub
Bitrise
Bitrise
Travis CI
Travis CI
Objective-C
Objective-C
Android SDK
Android SDK
React Native
React Native
#End2end
#SmartHome

We are using React Native in #SmartHome to share the business logic between Android and iOS team and approach users with a unique brand experience. The drawback is that we require lots of native Android SDK and Objective-C modules, so a good part of the invested time is there. The gain for a app that relies less on native communication, sensors and OS tools should be even higher.

Also it helps us set different testing stages: we use Travis CI for the javascript (business logic), Bitrise to run build tests and @Detox for #end2end automated user tests.

We use a microservices structure on top of Zeit's @now that read from firebase. We use JWT auth to authenticate requests among services and from users, following GitHub philosophy of using the same infrastructure than its API consumers. Firebase is used mainly as a key-value store between services and as a backup database for users. We also use its authentication mechanisms.

You can be super locked-in if you also rely on it's analytics, but we use Amplitude for that, which offers us great insights. Intercom for communications with end-user and Mailjet for marketing.

See more
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Bitbucket Pipelines

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An Integrated continuous integration and continuous deployment for Bitbucket
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